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TYP: annotate plotting._matplotlib.misc
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MEMBER
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QST: is the new behavior of GroupByRolling for MultiIndex in v1.1.1 intended?
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| 2020-09-01T00:06:15Z
| 2020-09-07T21:06:29Z
| 2020-09-07T21:06:29Z
|
NONE
| null |
#### Question about pandas
Let's say we have a `Series` with `MultiIndex` like the below.
```python
>>> pser = pd.Series(
... [1, 2, 3, 2],
... index=pd.MultiIndex.from_tuples([("a", "x"), ("a", "y"), ("b", "z"), ("c", "z")]),
... name="a",
... )
>>> pser
a x 1
y 2
b z 3
c z 2
Name: a, dtype: int64
```
Then, when I use `GroupByRolling`, In the version of pandas <= 1.0.5 shows result as below.
(Let's focus on the level of `MultiIndex` in the examples below)
```python
>>> pser.groupby(pser).rolling(2).max()
a
1 a x NaN
2 a y NaN
c z 2.0
3 b z NaN
Name: a, dtype: float64
>>> pser.groupby(pser).rolling(2).max().index
MultiIndex([(1, 'a', 'x'),
(2, 'a', 'y'),
(2, 'c', 'z'),
(3, 'b', 'z')],
names=['a', None, None])
>>> pser.groupby(pser).rolling(2).max().index.nlevels # It keeps the index level.
3
```
However, In the pandas 1.1.0, the result seems different from the previous version as below.
(The level of `MultiIndex` is decreased after performing)
```python
>>> pser.groupby(pser).rolling(2).max()
a
1 (a, x) NaN
2 (a, y) NaN
(c, z) 2.0
3 (b, z) NaN
Name: a, dtype: float64
>>> pser.groupby(pser).rolling(2).max().index
MultiIndex([(1, ('a', 'x')),
(2, ('a', 'y')),
(2, ('c', 'z')),
(3, ('b', 'z'))],
names=['a', None])
>>> pser.groupby(pser).rolling(2).max().index.nlevels # index level changed from 3 to 2
2
```
Is it intended behavior in pandas 1.1.1. ??
Thanks :)
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| 36,019
|
BUG: Read_Parquet replacing values with None
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| 2020-09-01T01:18:23Z
| 2020-12-15T18:41:48Z
| 2020-12-15T18:41:48Z
|
NONE
| null |
Tried reading a parquet file with data below. However, I see that some of the topics are replaced with None in the dataframe and I'm not sure what's causing this. This happens for only some rows.
example.parquet:
{
"id": "035f57ed-ef07-4ec1-b8d4-04453b9b8fa1",
"topics": [
"GOVERNMENT",
"ECONOMY",
"POLITICS"
]
},...
```
import pandas as pd
s3_path = 's3://test-bucket/example.parquet'
df = pd.read_parquet(s3_path)
df[['id', 'topics']][df['id'] == '035f57ed-ef07-4ec1-b8d4-04453b9b8fa1'].values
result:
array([['035f57ed-ef07-4ec1-b8d4-04453b9b8fa1',
array(['GOVERNMENT', 'ECONOMY', None], dtype=object)]],
dtype=object)
```
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MDExOlB1bGxSZXF1ZXN0NDc2NzQ5NTgw
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REF: implement Block._replace_list
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| 1
| 2020-09-01T01:30:38Z
| 2020-09-02T00:55:52Z
| 2020-09-01T23:31:10Z
|
MEMBER
| null |
So we can re-use BlockManager.apply for the block iteration.
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- [x] closes #36024
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
pandas\io\excel\_xlwt.py:52: error: Need type annotation for 'style_dict' (hint: "style_dict: Dict[<type>, <type>] = ...") [var-annotated]
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- [X] closes #36002
- [X] tests added / passed
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- [ ] whatsnew entry
Removed outdated example in documentation for pd.Interval (string endpoints are not allowed anymore).
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remove trailing commas for #35925
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CONTRIBUTOR
| null |
- [x] pandas/io/parquet.py
- [x] pandas/io/parsers.py
- [x] pandas/io/pytables.py
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BUG: wrong plotting in x-axis when index set to date
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[] | null | 1
| 2020-09-01T08:12:25Z
| 2020-09-04T19:42:36Z
| 2020-09-04T19:42:36Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
in `mydata` i have't no any data between `2000-01-03` to `2020-01-01`
but pandas wrong plotting in x-axis when index set to date
```python
d1 = [ '2000-01-01', 5 ]
d2 = [ '2000-01-02', -5 ]
d3 = [ '2020-01-02', 5 ]
mydata = pd.DataFrame( [d1,d2,d3] , columns=["DATE","DATA"] )
mydata["DATE"] = pd.to_datetime( mydata["DATE"] )
mydata = mydata.set_index("DATE")
mydata.plot()
```
#### Expected Output
```python
d1 = [ '2000-01-01', 5 ]
d2 = [ '2000-01-02', -5 ]
d3 = [ '2020-01-02', 5 ]
mydata = pd.DataFrame( [d1,d2,d3] , columns=["DATE","DATA"] )
# mydata["DATE"] = pd.to_datetime( mydata["DATE"] )
mydata = mydata.set_index("DATE")
mydata.plot()
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.8.1.final.0
python-bits : 64
OS : Linux
OS-release : 4.9.0-7-amd64
Version : #1 SMP Debian 4.9.110-1 (2018-07-05)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.utf8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.18.2
pytz : 2019.3
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.13.0
pandas_datareader: None
bs4 : 4.9.0
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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MDU6SXNzdWU2ODk5NzY5NjU=
| 36,031
|
BUG: Mean of zeros turn out to be non-zero
|
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| 6
| 2020-09-01T09:19:09Z
| 2020-09-15T22:20:48Z
| 2020-09-15T22:20:48Z
|
NONE
| null |
- [ ] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
'''Two examples of a time-weighted rolling average, both of which should result in a final value of 0.'''
import pandas as pd
def succeeding_test():
df = pd.DataFrame(
{"A": [300239975158033.0, -0.0, -0.0]},
index=[
pd.Timestamp("19700101 09:00:00"),
pd.Timestamp("19700101 09:00:03"),
pd.Timestamp("19700101 09:00:06"),
],
)
v = df.resample("1s").ffill().rolling("3s", closed="left", min_periods=3).mean().values[-1]
assert v == 0
def failing_test():
df = pd.DataFrame(
{"A": [3002399751580331.0, -0.0, -0.0]}, # First value is a single digit longer.
index=[
pd.Timestamp("19700101 09:00:00"),
pd.Timestamp("19700101 09:00:03"),
pd.Timestamp("19700101 09:00:06"),
],
)
v = df.resample("1s").ffill().rolling("3s", closed="left", min_periods=3).mean().values[-1]
assert v == 0 # v turns out to be == -0.3333333
```
#### Problem description
In both these cases, the final rolling mean value is the mean of three zeros, but in the `failing_test`, this does not result in a zero value. I am expecting the `failing_test` to have the same behaviour as the `succeeding_test`. The difference lies in the magnitude of the first value in the df, but that shouldn't affect the last mean, as it falls outside the rolling window for that value.
#### Expected Output
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.6.9.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-42-generic
Version : #46-Ubuntu SMP Fri Jul 10 00:24:02 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.16.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 46.1.1
Cython : None
pytest : 4.6.11
hypothesis : 4.57.1
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.1
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : None
xarray : 0.16.0
xlrd : 1.2.0
xlwt : None
numba : 0.47.0
</details>
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BUG: .dt.isocalendar().year
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| 0
| 2020-09-01T09:47:42Z
| 2020-09-04T20:29:25Z
| 2020-09-04T20:29:25Z
|
NONE
| null |
#### Code Sample, a copy-pastable example
```python
import pandas as pd
df = pd.DataFrame(
{
"Date": [
pd.to_datetime("2016-01-01"),
pd.to_datetime("2016-01-04"),
pd.to_datetime("2016-01-05"),
pd.to_datetime("2016-01-06"),
pd.to_datetime("2016-01-07"),
pd.to_datetime("2016-01-08"),
]
}
)
df["Date"].dt.isocalendar().year
```
#### Problem description
new function .dt.isocalendar().year returns wrong value for the day of pd.to_datetime('2016-01-08'). It is supposed to return 2016 but 2017
please check on that
|
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MDU6SXNzdWU2OTAwMzE4OTQ=
| 36,033
|
Coverting bug by null values from csv into panda nan to a python list
|
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[] | null | 3
| 2020-09-01T10:37:24Z
| 2020-09-03T11:33:24Z
| 2020-09-03T11:25:59Z
|
NONE
| null |
Hello,
I read a csv file with panda and convert it to a python list.
The problem is that panda convert the null values from the csv to nan values.
After that I convert the panda dataframe to a python nested list and got nan values inside the python list that have the float type.
Code:
`for chunk in pd.read_csv(pfad_incoming + record, chunksize=1000000, delimiter=';', quotechar="'", escapechar='"'):
batch = [chunk.columns.values.tolist()] + chunk.values.tolist()`
A column:
[5000000026661893028, 26661987940, '2020-07-09 10:40:10.435000', 1, nan, nan, nan, nan, nan, nan, nan, nan, 'v5', nan]
The type of the nan values:
<class 'float'>
Is that a bug? In the python list, however, should nan be None, right?
Regards,
Phil
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MDExOlB1bGxSZXF1ZXN0NDc2OTkzNTEx
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|
TYP: Postponed Evaluation of Annotations (PEP 563)
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| 4
| 2020-09-01T10:47:32Z
| 2020-09-03T08:51:04Z
| 2020-09-02T21:31:48Z
|
MEMBER
| null |
a few files as POC/for discussion
from https://www.python.org/dev/peps/pep-0563/
> PEP 3107 added support for arbitrary annotations on parts of a function definition. Just like default values, annotations are evaluated at function definition time. This creates a number of issues for the type hinting use case:
> - forward references: when a type hint contains names that have not been defined yet, that definition needs to be expressed as a string literal;
> - type hints are executed at module import time, which is not computationally free.
> Postponing the evaluation of annotations solves both problems.
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CI: pin s3fs for Windows py37_np18 on 1.1.x
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MDU6SXNzdWU2OTAxNzU3Njk=
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|
BUG: The exception is arisen when `apply` takes functions with equal names
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| 2020-09-01T14:09:34Z
| 2020-09-07T10:20:20Z
| null |
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
import pandas
pdf = pandas.DataFrame([[4, 9]] * 3, columns=['A', 'B'])
pdf.apply(["sum", "sum"])
SpecificationError: Function names must be unique if there is no new column names assigned
```
#### Problem description
Could anyone please explain? Is it normal behavior?
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
pandas : 1.1.1
numpy : 1.18.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 41.2.0
Cython : None
pytest : 5.4.2
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.7.3
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : 3.6.1
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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MDU6SXNzdWU2OTAxODU2MDI=
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|
BUG: transform zscore - weird behavior for not rounded floats
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| 2020-09-01T14:22:00Z
| 2020-09-04T08:33:09Z
| 2020-09-04T08:33:09Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
```
import pandas as pd
import numpy as np
from scipy import stats #1.15
from functools import partial
scorer = partial(stats.zscore, nan_policy='omit')
n = -0.405465999999999999999999999999999999999999999999999999
a = [np.nan, np.nan, np.nan, np.nan, n, n, n]
df = pd.DataFrame({'c1': ['a', 'a', 'a', 'a', 'a', 'a', 'a'], 'c2': a})
df.groupby(['c1'])['c2'].transform(scorer)
```
Gives:
```
0 NaN
1 NaN
2 NaN
3 NaN
4 -1.0
5 -1.0
6 -1.0
Name: c2, dtype: float64
```
#### Problem description
It should give result like for e.g. `n=0.5` when it works as expected.
I've checked and `n = -0.405465999999999999999999999999999999999999999999999999` and `stats.zscore(np.array(a))` and it worked correctly so I suppose issue is within pandas.
A little background about `stats.zscore` from `scipy`:
- returns `np.nan` for `nans` (`nan_policy`)
- if rest element of vector are the same it should return `np.nan` due to division by 0 (std deviation is zero)
Long `n` is just for easy reproduction, issue happened with real data. My temporary workaround is to round values.
#### Expected Output
```
/usr/local/lib/python3.6/dist-packages/scipy/stats/stats.py:2419: RuntimeWarning: invalid value encountered in true_divide
return (a - mns) / sstd
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
5 NaN
6 NaN
```
#### Output of ``pd.show_versions()``
1.1.1
<details>
[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]
</details>
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MDExOlB1bGxSZXF1ZXN0NDc3MTI2ODEx
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|
BUG: 35977 Adding regex support for ExtensionBlock replace method
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| 2021-02-11T01:38:59Z
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|
CONTRIBUTOR
| null |
- [x] closes #35977
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
Overrides replace method to add support of regex in ExtensionBlock . If input to_replace is a regex we convert data type of block to Object and calls object replace method which supports regex otherwise we call replace method of super class Block.
```ipython
In [2]: b.replace(r'^\s*$', pd.NA, regex=True, inplace=True)
...: print(b)
a b
0 a d
1 b <NA>
2 c <NA>
In [3]: b.replace(r'^\s*$', pd.NA, regex=True, inplace=False)
Out[3]:
a b
0 a d
1 b <NA>
2 c <NA>
```
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MDExOlB1bGxSZXF1ZXN0NDc3MTQxNDQy
| 36,039
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Backport PR #35938 on branch 1.1.x (REGR: Fix comparison broadcasting over array of Intervals)
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NONE
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Backport PR #35938: REGR: Fix comparison broadcasting over array of Intervals
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BUG: Rolling min_periods not working on groupby object
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| 5
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| 2020-10-10T22:30:51Z
| 2020-10-10T22:30:51Z
|
CONTRIBUTOR
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
df = pd.DataFrame({
'segment': 'A',
'data': range(10)
})
df.rolling(5, center=True, min_periods=1).max()
df.groupby('segment').rolling(5, center=True, min_periods=1).max().reset_index(drop=True)
```
#### Problem description
For the DataFrame above, with a single segment 'A', the result of `df.rolling(5, center=True, min_periods=1).max()` should be identical to that of `df.groupby('segment').rolling(5, center=True, min_periods=1).max().reset_index(drop=True)`. Instead, the latter operation has NaNs in the last two positions of the data column.
#### Expected Output
Both operations should return the sequence `[2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 9.0, 9.0]`. Instead, `df.groupby('segment').rolling(5, center=True, min_periods=1).max().reset_index(drop=True)` returns `[2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, NaN, NaN]`
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.7.7.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Thu Jun 18 20:49:00 PDT 2020; root:xnu-6153.141.1~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.0
pip : 20.1.1
setuptools : 47.3.0.post20200616
Cython : None
pytest : 6.0.0
hypothesis : None
sphinx : 3.1.1
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.15.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.0
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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| 36,041
|
Backport PR #35999 on branch 1.1.x (BUG: None in Float64Index raising TypeError, should return False)
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| 0
| 2020-09-01T15:03:13Z
| 2020-09-01T16:57:17Z
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NONE
| null |
Backport PR #35999: BUG: None in Float64Index raising TypeError, should return False
|
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|
BUG: `apply` behaviour changed when using function that returns tuple
|
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| 2020-09-01T19:34:46Z
| 2020-09-01T19:34:26Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import seaborn as sns
import pandas as pd
import numpy as np
def get_mean_sd(column):
return np.mean(column), np.std(column)
iris = sns.load_dataset("iris")[["sepal_length", "sepal_width", "petal_length", "petal_width"]]
iris.apply(get_mean_sd)
```
#### Problem description
In version 1.0, the result was a pandas series of tuples, whereas in 1.1 the result is a data frame, thus breaking existing code that depends on apply.
The result from 1.1 is
```
sepal_length sepal_width petal_length petal_width
0 5.843333 3.057333 3.758000 1.199333
1 0.825301 0.434411 1.759404 0.759693
```
#### Expected Output
The output from version 1.0 was:
```
sepal_length (5.843333333333334, 0.8253012917851409)
sepal_width (3.0573333333333337, 0.4344109677354946)
petal_length (3.7580000000000005, 1.759404065775303)
petal_width (1.1993333333333336, 0.7596926279021594)
dtype: object
```
#### Output of ``pd.show_versions()``
<details>
For 1.0.3:
INSTALLED VERSIONS
------------------
commit : None
python : 3.8.2.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-1127.18.2.el7.x86_64
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.utf-8
LANG : en_US.utf-8
LOCALE : en_US.UTF-8
pandas : 1.0.3
numpy : 1.18.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.0.2
setuptools : 46.4.0.post20200518
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.13.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.2.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None
For 1.1.1:
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.8.2.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-1127.18.2.el7.x86_64
Version : #1 SMP Sun Jul 26 15:27:06 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.utf-8
LANG : en_US.utf-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.18.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.0.2
setuptools : 46.4.0.post20200518
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.13.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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| 690,252,361
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MDExOlB1bGxSZXF1ZXN0NDc3MTcyNDE3
| 36,043
|
DOC: add semicolons to suppress text repr of matplotlib objects in visualization.rst
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| 7
| 2020-09-01T15:46:11Z
| 2020-10-10T17:28:56Z
| 2020-10-10T17:28:43Z
|
CONTRIBUTOR
| null |
add semicolons (";") after the plotting function to suppress unnecessary debug messages similar to:
<matplotlib.axes._subplots.AxesSubplot at 0x7fe278bb5160>
- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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MDU6SXNzdWU2OTAyNzkyMTE=
| 36,044
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BUG: Set type check is too strict when creating Series from dict keys
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| 2
| 2020-09-01T16:20:39Z
| 2020-09-05T23:13:45Z
| 2020-09-05T23:13:45Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
from pandas import Series
Series({'a': 1, 'b': 2}.keys())
```
#### Problem description
Since Python 3.7 dictionaries are ordered, and therefore their keys are also ordered. In older pandas versions (prior to 1.1?) it was possible to create a `Series` from keys of a dictionary. A fix to #32582 intended to prevent an issue with sets seems to be breaking the creation of `Series` from keys of a dictionary.
Currently the following is raised:
```python
/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
325 data = data.copy()
326 else:
--> 327 data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
328
329 data = SingleBlockManager.from_array(data, index)
/pandas/core/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
450 subarr = _try_cast(arr, dtype, copy, raise_cast_failure)
451 elif isinstance(data, abc.Set):
--> 452 raise TypeError("Set type is unordered")
453 elif lib.is_scalar(data) and index is not None and dtype is not None:
454 data = maybe_cast_to_datetime(data, dtype)
TypeError: Set type is unordered
```
#### Expected Output
Same as of `Series(list({'a': 1, 'b': 2}.keys()))`, i.e.:
```
0 a
1 b
dtype: object
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.7.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-42-generic
Version : #46-Ubuntu SMP Fri Jul 10 00:24:02 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.1.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 19.2.3
setuptools : 41.2.0
Cython : None
pytest : 5.3.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.12.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
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MDExOlB1bGxSZXF1ZXN0NDc3MjE3MTQ4
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|
BUG: NDFrame.replace wrong exception type, wrong return when size==0
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| 1
| 2020-09-01T17:04:47Z
| 2020-09-02T16:57:21Z
| 2020-09-02T03:19:27Z
|
MEMBER
| null |
- [ ] closes #xxxx
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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MDExOlB1bGxSZXF1ZXN0NDc3MjM4NDY5
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|
REF: simplify CSVFormatter
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| 4
| 2020-09-01T17:49:29Z
| 2020-11-06T15:35:00Z
| 2020-09-09T10:33:11Z
|
MEMBER
| null |
- [ ] closes #xxxx
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Refactor CSVFormatter
----------------------
1. Put data validation in setters
2. Extract helper methods and properties
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MDU6SXNzdWU2OTAzNDY2Mjk=
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BUG: Series.__mod__ behaves different with >1e4 rows
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| 2
| 2020-09-01T18:14:14Z
| 2020-09-30T20:27:08Z
| 2020-09-30T20:27:08Z
|
NONE
| null |
- [√] I have checked that this issue has not already been reported.
- [√] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
# Your code here
import pandas as pd
ts = pd.Series([-2,-2,-2])
ts = pd.concat(5000 * [ts])
(ts[:10001]%4).iloc[-1]
(ts[:10000]%4).iloc[-1]
```
Gives
-2
2
#### Problem description
According to basic python module operations and previous versions of pandas, the module operation should always give a non-negative value, but when a Series larger than 10000 rows, the negative value module array operation gives a negative value.
#### Expected Output
2
2
#### Output of ``pd.show_versions()``
1.1.1
<details>
</details>
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CI: pin setuptools on 1.1.x
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| 1
| 2020-09-01T18:42:16Z
| 2020-09-02T09:23:22Z
| 2020-09-01T23:27:11Z
|
MEMBER
| null |
top answer on stack overflow is to pin https://stackoverflow.com/questions/63663362/django-python3-on-install-i-get-parent-module-setuptools-not-loaded
also see https://github.com/MacPython/pandas-wheels/pull/97#issuecomment-684938715
Note: 50.0.1 released a hour ago but still the same. https://dev.azure.com/pandas-dev/pandas/_build/results?buildId=41325&view=logs&j=a67b4c4c-cd2e-5e3c-a361-de73ac9c05f9&t=9a6bfc0f-544f-57f9-291f-bf4b75b05642
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| 4
| 2020-09-01T20:56:01Z
| 2020-09-07T05:14:36Z
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|
CONTRIBUTOR
| null |
- [x] closes #36032
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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MDExOlB1bGxSZXF1ZXN0NDc3MzQwMTkz
| 36,051
|
BUG: frame._item_cache not cleared when Series is altered
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| 4
| 2020-09-01T21:16:16Z
| 2020-09-02T16:55:54Z
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|
MEMBER
| null |
- [x] closes #33675
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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| 690,463,211
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MDExOlB1bGxSZXF1ZXN0NDc3MzQ4Mjk1
| 36,052
|
CLN remove unnecessary trailing commas in pandas/io
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| 9
| 2020-09-01T21:28:54Z
| 2020-09-03T20:04:49Z
| 2020-09-03T16:33:47Z
|
CONTRIBUTOR
| null |
@MarcoGorelli can you review this PR this is related to issue #35925, if this looks good to you I can open another PR
- [x] pandas/io/sas/sas_xport.py
- [x] pandas/io/stata.py
- [x] passes `black pandas`
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MDExOlB1bGxSZXF1ZXN0NDc3MzYyOTIx
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CLN: _wrap_applied_output
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| 2020-09-01T22:05:45Z
| 2020-09-01T23:56:26Z
| 2020-09-01T23:17:23Z
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MEMBER
| null |
- [ ] closes #xxxx
- [ ] tests added / passed
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- [ ] whatsnew entry
2nd step toward #35412. In this, the order of the largest if-else is switched with the condition negated. We can then drop the else entirely, resulting in much of the function having one less level of nesting.
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| 690,484,716
|
MDExOlB1bGxSZXF1ZXN0NDc3MzY2MDgz
| 36,054
|
BUG: Don't raise when constructing Series from ordered set
|
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| 2
| 2020-09-01T22:14:11Z
| 2020-09-06T12:58:55Z
| 2020-09-05T23:13:46Z
|
MEMBER
| null |
- [x] closes #36044
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
This may or may not be a regression, since before the change that caused the error to be raised the output was still wrong (same bug that motivated the initial patch):
```python
In [2]: keys = {'a': 1, 'b': 2}.keys()
In [3]: pd.Series(keys)
Out[3]:
0 (a, b)
1 (a, b)
dtype: object
```
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MDExOlB1bGxSZXF1ZXN0NDc3MzY4NDY5
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STY/WIP: check for private imports/lookups
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| 2020-09-12T21:34:28Z
| 2020-09-12T21:30:33Z
|
MEMBER
| null |
Mostly this is an amalgam of #33479, #33394, and #33393.
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|
conda install -c anaconda pandas=1.1.1 fails in Windows
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[] | null | 1
| 2020-09-01T22:59:12Z
| 2020-09-03T10:47:35Z
| 2020-09-02T12:30:47Z
|
NONE
| null |
#### Question about pandas
I am trying to update Pandas in a venv under Windows 10 using miniconda. I have Pandas 1.0.3 installed.
I think part of the issue is there are pip installed packages in the environment
This is unavoidable; some things I use cannot be installed by conda
Is the only solution to build a new env from scratch, get pandas in there, then try to install remaining dependencies?
Here is my current env:
```
conda list
# packages in environment at C:\Users\bbate\Miniconda3\envs\keras-gpu-2:
#
# Name Version Build Channel
_anaconda_depends 2019.03 py37_0
_py-xgboost-mutex 2.0 cpu_0
absl-py 0.9.0 pypi_0 pypi
adjusttext 0.7.3 pypi_0 pypi
alabaster 0.7.12 py37_0
alembic 1.4.0 py_0 conda-forge
anaconda custom py37_1
anaconda-client 1.7.2 py37_0
anaconda-project 0.8.4 py_0
argh 0.26.2 py37_0
arrow 0.15.6 py37hc8dfbb8_1 conda-forge
asn1crypto 0.24.0 py37_3 intel
astor 0.8.1 pypi_0 pypi
astroid 2.3.3 py37_0
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atomicwrites 1.3.0 py37_1
attrs 19.3.0 py_0
autopep8 1.4.4 py_0
babel 2.8.0 py_0
backcall 0.1.0 py37_0
backports 1.0 py_2
backports.os 0.1.1 py37_0
backports.shutil_get_terminal_size 1.0.0 py37_2
bcrypt 3.1.7 py37he774522_0
beautifulsoup4 4.8.2 py37_0
binaryornot 0.4.4 py_1 conda-forge
bitarray 1.2.1 py37he774522_0
bkcharts 0.2 py37_0
blas 1.0 mkl
bleach 3.1.0 py37_0
blosc 1.16.3 h7bd577a_0
bokeh 2.1.0 py37hc8dfbb8_0 conda-forge
boost-cpp 1.72.0 h0caebb8_0 conda-forge/label/cf202003
boto 2.49.0 py37_0
boto3 1.9.66 py37_0 anaconda
botocore 1.12.189 py_0
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bzip2 1.0.8 he774522_0
ca-certificates 2020.7.22 0 anaconda
cachetools 4.0.0 pypi_0 pypi
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certifi 2020.6.20 py37_0 anaconda
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chardet 3.0.4 py37_3 intel
click 7.0 py37_0
click-plugins 1.1.1 py_0 conda-forge/label/cf202003
cliff 2.15.0 py37_0 conda-forge
cligj 0.5.0 py_0 conda-forge/label/cf202003
cloudpickle 1.3.0 py_0
clyent 1.2.2 py37_1
cmd2 0.9.15 py37_0 conda-forge
colorama 0.4.3 py_0
colorcet 2.0.1 py_0 conda-forge
coloredlogs 10.0 py37_0
colorlog 4.1.0 py37_1 conda-forge
comtypes 1.1.7 py37_0
confuse 1.3.0 pyh9f0ad1d_0 conda-forge
console_shortcut 0.1.1 4
contextlib2 0.6.0.post1 py_0
cookiecutter 1.6.0 py37_1000 conda-forge
cryptography 2.7 py37_0 intel
curl 7.68.0 h4496350_0 conda-forge/label/cf202003
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diff-match-patch 20181111 py_0
distributed 2.11.0 py37_0
docutils 0.16 py37_0
entrypoints 0.3 py37_0
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ffmpeg 4.2.3 ha925a31_0 conda-forge
filelock 3.0.12 py_0
fiona 1.8.9.post2 py37h3234bc7_0 conda-forge/label/cf202003
flake8 3.8.3 py_0 anaconda
flask 1.1.1 py_0
flask-compress 1.4.0 pypi_0 pypi
freetype 2.10.1 1 intel
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nose 1.3.7 py37_2
notebook 6.0.3 py37_0
numba 0.48.0 np117py37_0 intel
numexpr 2.7.0 py37_1 intel
numpy 1.17.4 py37ha68da19_4 intel
numpy-base 1.17.4 py37_4 intel
numpydoc 0.9.2 py_0
oauthlib 3.1.0 pypi_0 pypi
olefile 0.46 py37_0
openjpeg 2.3.1 h57dd2e7_3 conda-forge/label/cf202003
openpyxl 3.0.3 py_0
openssl 1.1.1g he774522_1 anaconda
opt-einsum 3.1.0 pypi_0 pypi
optuna 1.0.0 py_0 conda-forge
packaging 20.1 py_0
pandas 1.0.3 py37h3bbf574_1 conda-forge
pandas-profiling 2.8.0 py_0 conda-forge
pandas-summary 0.0.41 py_1 conda-forge
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
panel 0.9.5 py_1 conda-forge
param 1.9.3 py_0 conda-forge
paramiko 2.7.1 py_0
parso 0.7.0 py_0 anaconda
partd 1.1.0 py_0
path 13.1.0 py37_0
path.py 12.4.0 0
pathlib2 2.3.5 py37_0
pathtools 0.1.2 py_1
patsy 0.5.1 py37_0
pbr 5.4.2 py_0 conda-forge
pcre 8.44 h6538335_0 conda-forge
pep8 1.7.1 py37_0
pexpect 4.8.0 py37_0
phik 0.10.0 py_0 conda-forge
pickleshare 0.7.5 py37_0
pillow 7.0.0 py37hcc1f983_0
pip 20.2.2 pypi_0 pypi
pixman 0.38.0 hfa6e2cd_1003 conda-forge
pkginfo 1.5.0.1 py37_0
plotly 4.8.1 py_0
plotly_express 0.4.1 py_0 plotly
pluggy 0.13.1 py37_0
ply 3.11 py37_0
poppler 0.67.0 h1707e21_8 conda-forge/label/cf202003
poppler-data 0.4.9 1 conda-forge/label/cf202003
postgresql 11.5 h06f7779_1 conda-forge/label/cf202003
powershell_shortcut 0.0.1 3
poyo 0.5.0 py_0 conda-forge
prettytable 0.7.2 py_3 conda-forge
proglog 0.1.9 py_0 conda-forge
proj4 6.1.1 hc2d0af5_1 conda-forge/label/cf202003
prometheus_client 0.7.1 py_0
prompt_toolkit 3.0.3 py_0
protobuf 3.11.3 pypi_0 pypi
psutil 5.6.7 py37he774522_0
py 1.8.1 py_0
py-lief 0.9.0 py37ha925a31_3
py-xgboost 0.90 py37_1 anaconda
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycairo 1.19.1 py37h6430cfb_3 conda-forge
pycodestyle 2.6.0 py_0 anaconda
pycosat 0.6.3 py37_3 intel
pycparser 2.18 py37_2 intel
pycrypto 2.6.1 py37hfa6e2cd_9
pyct 0.4.6 py_0 conda-forge
pyct-core 0.4.6 py_0 conda-forge
pycurl 7.43.0.5 py37h7a1dbc1_0
pydocstyle 4.0.1 py_0
pydotplus 2.0.2 py_3 anaconda
pyflakes 2.2.0 py_0 anaconda
pygments 2.5.2 py_0
pygobject 3.36.1 py37hf6b2db1_0 conda-forge
pylint 2.4.4 py37_0
pynacl 1.3.0 py37h62dcd97_0
pynndescent 0.4.8 py_1 anaconda
pyodbc 4.0.30 py37ha925a31_0
pyopenssl 17.5.0 py37_2 intel
pyparsing 2.2.0 py37_2 intel
pyperclip 1.7.0 py_0 conda-forge
pyproj 2.3.1 py37he1416cd_0 conda-forge/label/cf202003
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.15.7 py37he774522_0
pysocks 1.6.7 py37_1 intel
pytables 3.5.2 py37h6a20dd8_0 conda-forge/label/cf202003
pytest 5.3.5 py37_0
pytest-arraydiff 0.3 py37h39e3cac_0
pytest-astropy 0.8.0 py_0
pytest-astropy-header 0.1.2 py_0
pytest-doctestplus 0.5.0 py_0
pytest-openfiles 0.4.0 py_0
pytest-remotedata 0.3.2 py37_0
python 3.7.6 h60c2a47_2
python-dateutil 2.8.0 py37_0 intel
python-editor 1.0.4 py_0
python-jsonrpc-server 0.3.4 py_0
python-language-server 0.34.1 py37_0 anaconda
python-libarchive-c 2.8 py37_13 intel
python_abi 3.7 1_cp37m conda-forge
pytz 2019.1 py37_0 intel
pyviz_comms 0.7.5 pyh9f0ad1d_0 conda-forge
pywavelets 1.1.1 py37he774522_0
pywin32 224 py37hfa6e2cd_1002 intel
pywin32-ctypes 0.2.0 py37_1000
pywinpty 0.5.7 py37_0
pyyaml 5.1.1 py37_0 intel
pyzmq 18.1.1 py37ha925a31_0
qdarkstyle 2.8 py_0
qt 5.9.7 vc14h73c81de_0 [vc14]
qtawesome 0.6.1 py_0
qtconsole 4.6.0 py37_1
qtpy 1.9.0 py_0
requests 2.23.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
retrying 1.3.3 py37_2
rope 0.16.0 py_0
rsa 4.0 pypi_0 pypi
rtree 0.9.3 py37h21ff451_0
ruamel_yaml 0.15.64 py37_1 intel
s3transfer 0.1.13 py37_0 anaconda
scikit-image 0.16.2 py37h47e9c7a_0
scikit-learn 0.23.1 py37h25d0782_0
scikit-surprise 1.1.0 py37hbc2f12b_1002 conda-forge
scipy 1.4.1 pypi_0 pypi
seaborn 0.10.0 py_0
send2trash 1.5.0 py37_0
setuptools 41.0.1 py37_0 intel
shapely 1.6.4 py37ha35856d_1006 conda-forge/label/cf202003
simplegeneric 0.8.1 py37_2
singledispatch 3.4.0.3 py37_0
sip 4.19.8 py37h6538335_0
six 1.15.0 py_0 anaconda
snappy 1.1.7 h777316e_3
snowballstemmer 2.0.0 py_0
sortedcollections 1.1.2 py37_0
sortedcontainers 2.1.0 py37_0
soupsieve 1.9.5 py37_0
sphinx 2.3.1 py_0
sphinxcontrib 1.0 py37_1
sphinxcontrib-applehelp 1.0.1 py_0
sphinxcontrib-devhelp 1.0.1 py_0
sphinxcontrib-htmlhelp 1.0.2 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.2 py_0
sphinxcontrib-serializinghtml 1.1.3 py_0
sphinxcontrib-websupport 1.2.0 py_0
spyder 4.1.4 py37_0 anaconda
spyder-kernels 1.9.2 py37_0 anaconda
spyder-terminal 0.3.1 py37hc8dfbb8_1 spyder-ide
sqlalchemy 1.3.13 py37he774522_0
sqlite 3.31.1 he774522_0
statsmodels 0.11.0 py37he774522_0
stevedore 1.30.1 py_0 conda-forge
stumpy 1.3.0 py_0 conda-forge
sympy 1.5.1 py37_0
tangled-up-in-unicode 0.0.6 pyh9f0ad1d_0 conda-forge
tbb 2020.0 vc14_intel_166 [vc14] intel
tbb4py 2020.0 py37_intel_0 [vc14] intel
tblib 1.6.0 py_0
tensorboard 2.1.0 pypi_0 pypi
tensorflow 2.1.0 pypi_0 pypi
tensorflow-estimator 2.1.0 pypi_0 pypi
tensorflow-gpu 2.1.0 pypi_0 pypi
tensorflow-gpu-estimator 2.1.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.8.3 py37_0
testpath 0.4.4 py_0
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.8 hfa6e2cd_0
toml 0.10.1 py_0
toolz 0.10.0 py_0
tornado 6.0.3 py37he774522_3
tqdm 4.47.0 pyh9f0ad1d_0 conda-forge
traitlets 4.3.3 py37_0
tslearn 0.3.1 py37hbc2f12b_0 conda-forge
typing 3.6.4 py37_0
typing_extensions 3.7.4.2 py_0 conda-forge
ujson 1.35 py37hfa6e2cd_0
umap-learn 0.4.4 py37hc8dfbb8_0 conda-forge
unicodecsv 0.14.1 py37_0
urllib3 1.24.1 py37_2 intel
vc 14.1 h0510ff6_4
visions 0.4.4 pyh9f0ad1d_0 conda-forge
vs2015_runtime 14.16.27012 hf0eaf9b_1
watchdog 0.10.2 py37_0
wcwidth 0.1.8 py_0
webencodings 0.5.1 py37_1
werkzeug 1.0.0 py_0
wheel 0.31.0 py37_3 intel
whichcraft 0.6.1 py_0 conda-forge
widgetsnbextension 3.5.1 py37_0
win_inet_pton 1.0.1 py37_4 intel
win_unicode_console 0.5 py37_0
wincertstore 0.2 py37_3 intel
winpty 0.4.3 4
wrapt 1.11.2 py37he774522_0
xarray 0.15.1 py_0 conda-forge
xerces-c 3.2.2 h6538335_1004 conda-forge/label/cf202003
xlrd 1.2.0 py37_0
xlsxwriter 1.2.7 py_0
xlwings 0.17.1 py37_0
xlwt 1.3.0 py37_0
xz 5.2.4 h2fa13f4_7 intel
yaml 0.1.7 2 intel
yapf 0.28.0 py_0
zeromq 4.3.1 h33f27b4_3
zict 1.0.0 py_0
zipp 2.2.0 py_0
zlib 1.2.11 vc14hfa6e2cd_7 [vc14] intel
zstd 1.3.7 h508b16e_0
```
Here is what happens:
```
conda install -c anaconda pandas=1.1.1
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
```
The list of conflicts is hundreds of lines long; here are the last few hundred...
```
Package snappy conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> blosc -> snappy[version='>=1.1.7,<2.0a0|>=1.1.8,<2.0a0']
defaults/win-64::blosc==1.16.3=h7bd577a_0 -> snappy[version='>=1.1.7,<2.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> snappy
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> snappy
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> blosc[version='>=1.16.3,<2.0a0'] -> snappy[version='>=1.1.7,<2.0a0|>=1.1.8,<2.0a0']
Package ipaddress conflicts for:
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> notebook[version='>=4.0'] -> ipaddress
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> notebook[version='>=4.0'] -> ipaddress
intel/win-64::pyopenssl==17.5.0=py37_2 -> cryptography[version='>=2.1.4'] -> ipaddress
intel/win-64::urllib3==1.24.1=py37_2 -> cryptography[version='>=1.3.4'] -> ipaddress
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> notebook[version='>=4.2.0'] -> ipaddress
defaults/noarch::paramiko==2.7.1=py_0 -> cryptography[version='>=2.5'] -> ipaddress
defaults/win-64::jupyter==1.0.0=py37_7 -> notebook -> ipaddress
defaults/noarch::botocore==1.12.189=py_0 -> urllib3[version='>=1.20,<1.26'] -> ipaddress
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> notebook[version='>=4.0'] -> ipaddress
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> notebook[version='>=4.0'] -> ipaddress
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cryptography -> ipaddress
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> notebook[version='>=4.0'] -> ipaddress
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ipaddress
defaults/win-64::widgetsnbextension==3.5.1=py37_0 -> notebook[version='>=4.4.1'] -> ipaddress
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> notebook -> ipaddress
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> notebook[version='>=4.3.1'] -> ipaddress
conda-forge/noarch::requests==2.24.0=pyh9f0ad1d_0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> ipaddress
Package funcsigs conflicts for:
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> funcsigs[version='>=1.0']
conda-forge/noarch::phik==0.10.0=py_0 -> numba[version='>=0.38.1'] -> funcsigs
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> numba[version='>=0.46,!=0.47'] -> funcsigs
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> funcsigs
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> funcsigs[version='>=1.0']
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> funcsigs[version='>=1.0']
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> mock -> funcsigs
anaconda/noarch::pynndescent==0.4.8=py_1 -> numba[version='>=0.46'] -> funcsigs
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> numba -> funcsigs[version='>=1.0']
conda-forge/noarch::stumpy==1.3.0=py_0 -> numba[version='>=0.42.0'] -> funcsigs
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> funcsigs[version='>=1.0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> numba[version='>=0.37.0,<0.49'] -> funcsigs
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> funcsigs[version='>=1.0']
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> numba -> funcsigs
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> funcsigs[version='>=1.0']
Package python-dateutil conflicts for:
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> bokeh -> python-dateutil[version='>=2.1|>=2.7.3|>=2.6.1|>=2.5.*']
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> pandas[version='>=0.25.3'] -> python-dateutil[version='>=2.6.1|>=2.7.3']
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> python-dateutil[version='>=2.1']
conda-forge/win-64::matplotlib-base==3.2.1=py37h911224e_0 -> python-dateutil
conda-forge/noarch::datashape==0.5.4=py_1 -> python-dateutil
conda-forge/noarch::xarray==0.15.1=py_0 -> pandas[version='>=0.25'] -> python-dateutil[version='>=2.6.1|>=2.7.3']
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
defaults/noarch::botocore==1.12.189=py_0 -> python-dateutil[version='>=2.1,<3.0.0']
conda-forge/win-64::arrow==0.15.6=py37hc8dfbb8_1 -> python-dateutil
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> bokeh[version='>=1.1.0'] -> python-dateutil[version='>=2.1|>=2.7.3|>=2.6.1|>=2.5.*']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> pandas[version='>=0.23'] -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
conda-forge/noarch::phik==0.10.0=py_0 -> matplotlib-base[version='>=2.2.3'] -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
conda-forge/noarch::jinja2-time==0.2.0=py_2 -> arrow -> python-dateutil
conda-forge/noarch::optuna==1.0.0=py_0 -> alembic -> python-dateutil
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> jupyter_client[version='>=5.3.4'] -> python-dateutil[version='>=2.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> anaconda-client -> python-dateutil[version='>=2.1|>=2.6.1|>=2.7.3|>=2.5.*']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> python-dateutil
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> python-dateutil
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> matplotlib-base[version='>=2.2.0'] -> python-dateutil
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> jupyter_client -> python-dateutil[version='>=2.1']
defaults/win-64::statsmodels==0.11.0=py37he774522_0 -> pandas[version='>=0.21'] -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> python-dateutil
conda-forge/noarch::alembic==1.4.0=py_0 -> python-dateutil
defaults/win-64::qtconsole==4.6.0=py37_1 -> jupyter_client[version='>=4.1'] -> python-dateutil[version='>=2.1']
modin==0.7.3 -> pandas==1.0.3 -> python-dateutil[version='>=2.6.1']
defaults/win-64::anaconda-client==1.7.2=py37_0 -> python-dateutil
defaults/win-64::bkcharts==0.2=py37_0 -> pandas -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
anaconda/win-64::s3transfer==0.1.13=py37_0 -> botocore[version='>=1.3.0,<2.0.0'] -> python-dateutil[version='>=2.1,<2.7.0|>=2.1,<2.8.1|>=2.1,<3.0.0']
plotly/noarch::plotly_express==0.4.1=py_0 -> pandas[version='>=0.20.0'] -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
defaults/win-64::notebook==6.0.3=py37_0 -> jupyter_client[version='>=5.3.4'] -> python-dateutil[version='>=2.1']
defaults/noarch::anaconda-project==0.8.4=py_0 -> anaconda-client -> python-dateutil[version='>=2.6.1']
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
conda-forge/noarch::pandas-summary==0.0.41=py_1 -> pandas -> python-dateutil[version='>=2.5.*|>=2.6.1|>=2.7.3']
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> python-dateutil
defaults/noarch::dask==2.11.0=py_0 -> bokeh[version='>=1.0.0'] -> python-dateutil[version='>=2.1|>=2.7.3|>=2.6.1|>=2.5.*']
defaults/win-64::jupyter_client==5.3.4=py37_0 -> python-dateutil[version='>=2.1']
boto3 -> botocore[version='>=1.17.48,<1.18.0'] -> python-dateutil[version='>=2.1,<2.7.0|>=2.1,<2.8.1|>=2.1,<3.0.0']
conda-forge/noarch::descartes==1.1.0=py_4 -> matplotlib-base -> python-dateutil
defaults/noarch::jupyter_console==6.1.0=py_0 -> jupyter_client -> python-dateutil[version='>=2.1']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> matplotlib-base[version='>=3.2.0'] -> python-dateutil[version='>=2.6.1|>=2.7.3']
conda-forge/noarch::panel==0.9.5=py_1 -> bokeh[version='>=2.0'] -> python-dateutil[version='>=2.1']
Package bkcharts conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bkcharts
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> bkcharts
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bokeh -> bkcharts[version='>=0.2']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> bokeh -> bkcharts[version='>=0.2']
Package geos conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> geos[version='>=3.7.2,<3.7.3.0a0']
conda-forge/label/cf202003/win-64::shapely==1.6.4=py37ha35856d_1006 -> geos[version='>=3.7.2,<3.7.3.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> geos[version='>=3.7.2,<3.7.3.0a0']
conda-forge/label/cf202003/win-64::libspatialite==4.3.0a=h01b1fc4_1030 -> geos[version='>=3.7.2,<3.7.3.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> geos[version='>=3.6.2,<3.6.3.0a0|>=3.7.1,<3.7.2.0a0|>=3.7.2,<3.7.3.0a0|>=3.8.0,<3.8.1.0a0']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> shapely -> geos[version='>=3.6.2,<3.6.3.0a0|>=3.7.1,<3.7.2.0a0|>=3.8.0,<3.8.1.0a0|>=3.7.2,<3.7.3.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libspatialite[version='>=4.3.0a,<4.4.0a0'] -> geos[version='>=3.6.2,<3.6.3.0a0|>=3.7.1,<3.7.2.0a0|>=3.8.0,<3.8.1.0a0']
Package pytest conflicts for:
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1']
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1']
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest-arraydiff[version='>=0.1'] -> pytest[version='>=2.8.0|>=2.8|>=3.0|>=4.0|>=4.6']
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pytest
defaults/win-64::astropy==4.0=py37he774522_0 -> pytest-astropy -> pytest[version='>=3.1|>=3.1.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> astropy -> pytest[version='<3.7|<4|>=3.1|>=3.1.0|>=4.0|>=3.0|>=2.8|>=2.8.0|>=4.6']
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1']
Package pyqt conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> qtconsole[version='>=4.6.0'] -> pyqt
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyqt
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> pyqt[version='5.*|5.6.*|5.9.*|>=5.6,<6.0a0|>=5.9.2,<5.10.0a0']
defaults/win-64::qtconsole==4.6.0=py37_1 -> pyqt
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> pyqt[version='5.*|5.6.*|5.9.*|>=5.6,<6.0a0|>=5.9.2,<5.10.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> matplotlib -> pyqt[version='5.*|5.6.*|5.9.*|>=5.6,<6.0a0|>=5.9.2,<5.10.0a0|>=5.6,<5.13']
anaconda/win-64::spyder==4.1.4=py37_0 -> pyqt[version='>=5.6,<5.13']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> pyqt[version='>=5.6,<5.13']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyqt
defaults/win-64::jupyter==1.0.0=py37_7 -> qtconsole -> pyqt[version='>=5.9.2,<5.10.0a0']
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> pyqt=5.9
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> pyqt[version='5.*|5.6.*|5.9.*|>=5.6,<6.0a0|>=5.9.2,<5.10.0a0']
Package docutils conflicts for:
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> docutils[version='>=0.11|>=0.12']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> docutils
defaults/noarch::botocore==1.12.189=py_0 -> docutils[version='>=0.10']
anaconda/win-64::s3transfer==0.1.13=py37_0 -> botocore[version='>=1.3.0,<2.0.0'] -> docutils[version='>=0.10|>=0.10,<0.15|>=0.10,<0.16']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> docutils
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> docutils[version='>=0.11|>=0.12']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> docutils[version='>=0.11|>=0.12']
boto3 -> botocore[version='>=1.17.48,<1.18.0'] -> docutils[version='>=0.10|>=0.10,<0.15|>=0.10,<0.16']
Package lz4-c conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> lz4-c
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> lz4-c
defaults/win-64::blosc==1.16.3=h7bd577a_0 -> lz4-c[version='>=1.8.1.2,<1.9.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> blosc -> lz4-c[version='>=1.8.0,<1.9.0a0|>=1.8.1.2,<1.9.0a0|>=1.9.2,<1.10.0a0']
intel/win-64::python-libarchive-c==2.8=py37_13 -> libarchive -> lz4-c[version='>=1.8.0,<1.9.0a0|>=1.8.1.2,<1.9.0a0|>=1.9.2,<1.10.0a0']
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> blosc[version='>=1.16.3,<2.0a0'] -> lz4-c[version='>=1.8.1.2,<1.9.0a0|>=1.9.2,<1.10.0a0']
defaults/win-64::libarchive==3.3.3=h0643e63_5 -> lz4-c[version='>=1.8.1.2,<1.9.0a0']
Package sip conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> pyqt[version='>=5.6,<5.13'] -> sip[version='4.18.*|>=4.19.4|>=4.19.4,<=4.19.8|>=4.19.13,<=4.19.14']
defaults/win-64::pyqt==5.9.2=py37h6538335_2 -> sip[version='>=4.19.4,<=4.19.8']
defaults/win-64::qtconsole==4.6.0=py37_1 -> pyqt -> sip[version='4.18.*|>=4.19.4|>=4.19.4,<=4.19.8|>=4.19.13,<=4.19.14']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyqt -> sip[version='4.18.*|>=4.19.4|>=4.19.4,<=4.19.8|>=4.19.13,<=4.19.14']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sip
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sip
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> pyqt=5.9 -> sip[version='>=4.19.13,<=4.19.14|>=4.19.4|>=4.19.4,<=4.19.8']
Package rtree conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> rtree[version='>=0.8.3']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> rtree
anaconda/win-64::spyder==4.1.4=py37_0 -> rtree[version='>=0.8.3']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> rtree
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> rtree[version='>=0.8.3']
Package pyodbc conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyodbc
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyodbc
Package tbb4py conflicts for:
defaults/win-64::patsy==0.5.1=py37_0 -> numpy[version='>=1.4.0'] -> tbb4py
conda-forge/noarch::stumpy==1.3.0=py_0 -> numba[version='>=0.42.0'] -> tbb4py
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> numpy -> tbb4py
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> numpy[version='>=1.10'] -> tbb4py
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> numpy -> tbb4py
intel/win-64::numpy-base==1.17.4=py37_4 -> tbb4py
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> numba -> tbb4py
conda-forge/noarch::datashape==0.5.4=py_1 -> numpy[version='>=1.7'] -> tbb4py
conda-forge/noarch::phik==0.10.0=py_0 -> numba[version='>=0.38.1'] -> tbb4py
intel/win-64::numba==0.48.0=np117py37_0 -> tbb4py
defaults/win-64::bkcharts==0.2=py37_0 -> numpy[version='>=1.7.1'] -> tbb4py
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> numba[version='>=0.46,!=0.47'] -> tbb4py
intel/win-64::numpy==1.17.4=py37ha68da19_4 -> numpy-base==1.17.4=py37_4 -> tbb4py
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> numpy -> tbb4py
anaconda/win-64::py-xgboost==0.90=py37_1 -> numpy -> tbb4py
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> numpy[version='>=1.0'] -> tbb4py
conda-forge/noarch::moviepy==1.0.1=py_0 -> numpy -> tbb4py
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> numpy[version='>=1.11.3'] -> tbb4py
defaults/noarch::dask==2.11.0=py_0 -> numpy[version='>=1.13.0'] -> tbb4py
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> numba[version='>=0.37.0,<0.49'] -> tbb4py
defaults/noarch::seaborn==0.10.0=py_0 -> numpy[version='>=1.13.3'] -> tbb4py
conda-forge/noarch::imagehash==4.1.0=pyh9f0ad1d_0 -> numpy -> tbb4py
plotly/noarch::plotly_express==0.4.1=py_0 -> numpy[version='>=1.11'] -> tbb4py
conda-forge/noarch::pandas-summary==0.0.41=py_1 -> numpy -> tbb4py
defaults/win-64::imageio==2.6.1=py37_0 -> numpy -> tbb4py
anaconda/noarch::pynndescent==0.4.8=py_1 -> numba[version='>=0.46'] -> tbb4py
intel/win-64::mkl_random==1.1.0=py37ha68da19_0 -> numpy-base[version='>=1.1.0,<2.0a0'] -> tbb4py
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> numpy[version='>=1.11'] -> tbb4py
intel/win-64::mkl_fft==1.0.15=py37ha68da19_3 -> numpy-base[version='>=1.0.15,<2.0a0'] -> tbb4py
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> numba -> tbb4py
conda-forge/noarch::missingno==0.4.2=py_0 -> numpy -> tbb4py
conda-forge/noarch::optuna==1.0.0=py_0 -> numpy -> tbb4py
Package importlib-metadata conflicts for:
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> importlib-metadata[version='>=0.12']
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> importlib-metadata[version='>=0.12']
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> importlib-metadata[version='>=0.12']
defaults/win-64::inflect==4.1.0=py37_0 -> importlib_metadata -> importlib-metadata[version='>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
defaults/win-64::pytest==5.3.5=py37_0 -> importlib_metadata[version='>=0.12'] -> importlib-metadata[version='>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> importlib-metadata
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> importlib_metadata -> importlib-metadata[version='>=0.12|>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> flake8[version='>=3.8.0'] -> importlib-metadata
anaconda/noarch::flake8==3.8.3=py_0 -> importlib-metadata
defaults/win-64::jsonschema==3.2.0=py37_0 -> importlib_metadata -> importlib-metadata[version='>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> importlib-metadata[version='>=0.12']
anaconda/win-64::spyder==4.1.4=py37_0 -> keyring -> importlib-metadata
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> importlib-metadata[version='>=0.12']
conda-forge/noarch::markdown==3.2.2=py_0 -> importlib-metadata
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> importlib-metadata[version='>=0.12']
conda-forge/noarch::panel==0.9.5=py_1 -> markdown -> importlib-metadata
defaults/win-64::keyring==21.1.0=py37_0 -> importlib_metadata -> importlib-metadata[version='>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
defaults/win-64::path==13.1.0=py37_0 -> importlib_metadata[version='>=0.5'] -> importlib-metadata[version='>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
defaults/win-64::pluggy==0.13.1=py37_0 -> importlib_metadata[version='>=0.12'] -> importlib-metadata[version='>=1.1.3,<1.1.4.0a0|>=1.6.0,<1.6.1.0a0|>=1.6.1,<1.6.2.0a0|>=1.7.0,<1.7.1.0a0']
Package chardet conflicts for:
conda-forge/noarch::pyct==0.4.6=py_0 -> requests -> chardet[version='>=3.0.2,<3.1.0|>=3.0.2,<4']
defaults/win-64::anaconda-client==1.7.2=py37_0 -> requests[version='>=2.9.1'] -> chardet[version='>=3.0.2,<3.1.0|>=3.0.2,<4']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> requests -> chardet[version='>=2.0.0|>=3.0.2,<3.1.0|>=3.0.2,<4']
anaconda/win-64::spyder==4.1.4=py37_0 -> chardet[version='>=2.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> chardet
defaults/noarch::anaconda-project==0.8.4=py_0 -> requests -> chardet[version='>=3.0.2,<3.1.0|>=3.0.2,<4']
conda-forge/noarch::binaryornot==0.4.4=py_1 -> chardet
conda-forge/noarch::requests==2.24.0=pyh9f0ad1d_0 -> chardet[version='>=3.0.2,<4']
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> binaryornot[version='>=0.2.0'] -> chardet[version='>=3.0.2,<3.1.0|>=3.0.2,<4']
conda-forge/noarch::moviepy==1.0.1=py_0 -> requests[version='>=2.8.1,<3.0'] -> chardet[version='>=3.0.2,<3.1.0|>=3.0.2,<4']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> requests -> chardet[version='>=2.0|>=2.0.0|>=3.0.2,<3.1.0|>=3.0.2,<4']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> requests[version='>=2.23.0'] -> chardet[version='>=3.0.2,<3.1.0|>=3.0.2,<4']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> chardet
Package wheel conflicts for:
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> wheel
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> wheel
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> wheel
intel/win-64::pip==19.3.1=py37_2 -> wheel
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> wheel
Package cloudpickle conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> cloudpickle
modin==0.7.3 -> dask[version='>=2.1.0'] -> cloudpickle[version='>=0.2.1|>=0.2.2|>=1.5.0|>=1.3.0']
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> cloudpickle
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0'] -> cloudpickle[version='>=0.2.1|>=0.2.2']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask -> cloudpickle[version='>=0.2.1|>=0.2.2|>=1.5.0|>=1.3.0|>=0.5.0']
defaults/noarch::dask==2.11.0=py_0 -> cloudpickle[version='>=0.2.1']
anaconda/win-64::spyder==4.1.4=py37_0 -> cloudpickle[version='>=0.5.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> spyder-kernels[version='>=1.9.2,<1.10.0'] -> cloudpickle
defaults/win-64::distributed==2.11.0=py37_0 -> cloudpickle[version='>=0.2.2']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> cloudpickle[version='>=0.2.2|>=1.3.0|>=1.5.0']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> cloudpickle[version='>=0.2.1']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> cloudpickle[version='>=0.5.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cloudpickle
Package send2trash conflicts for:
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> notebook[version='>=4.0'] -> send2trash
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> send2trash
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> notebook[version='>=4.3.1'] -> send2trash
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> notebook[version='>=4.0'] -> send2trash
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> notebook[version='>=4.0'] -> send2trash
defaults/win-64::notebook==6.0.3=py37_0 -> send2trash
defaults/win-64::widgetsnbextension==3.5.1=py37_0 -> notebook[version='>=4.4.1'] -> send2trash
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> notebook[version='>=4.2.0'] -> send2trash
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> notebook -> send2trash
defaults/win-64::jupyter==1.0.0=py37_7 -> notebook -> send2trash
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> send2trash
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> notebook[version='>=4.0'] -> send2trash
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> notebook[version='>=4.0'] -> send2trash
Package pathlib2 conflicts for:
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> pathlib2
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> pathlib2[version='>=2.2.0']
defaults/win-64::inflect==4.1.0=py37_0 -> importlib_metadata -> pathlib2
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> pathlib2[version='>=2.2.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pathlib2
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> pathlib2[version='>=2.2.0']
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> pickleshare -> pathlib2
defaults/win-64::keyring==21.1.0=py37_0 -> importlib_metadata -> pathlib2
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> pathlib2[version='>=2.2.0']
defaults/win-64::path==13.1.0=py37_0 -> importlib_metadata[version='>=0.5'] -> pathlib2
defaults/win-64::pytest==5.3.5=py37_0 -> importlib_metadata[version='>=0.12'] -> pathlib2
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> pathlib2[version='>=2.2.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest -> pathlib2[version='>=2.2.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> pathlib2
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pathlib2
defaults/win-64::pluggy==0.13.1=py37_0 -> importlib_metadata[version='>=0.12'] -> pathlib2
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> pathlib2[version='>=2.2.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> pickleshare[version='>=0.4'] -> pathlib2
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> pathlib2
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> pathlib2
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> pathlib2
defaults/win-64::jsonschema==3.2.0=py37_0 -> importlib_metadata -> pathlib2
defaults/win-64::nbconvert==5.6.1=py37_0 -> testpath -> pathlib2
Package statsmodels conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> statsmodels
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> seaborn -> statsmodels[version='>=0.5.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> statsmodels
plotly/noarch::plotly_express==0.4.1=py_0 -> statsmodels[version='>=0.9.0']
conda-forge/noarch::missingno==0.4.2=py_0 -> seaborn -> statsmodels[version='>=0.5.0']
Package tqdm conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> tqdm
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> tqdm
conda-forge/noarch::panel==0.9.5=py_1 -> tqdm
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> panel[version='>=0.7.0'] -> tqdm
conda-forge/noarch::moviepy==1.0.1=py_0 -> proglog[version='<=1.0.0'] -> tqdm
conda-forge/noarch::moviepy==1.0.1=py_0 -> tqdm[version='>=4.11.2,<5.0']
conda-forge/noarch::proglog==0.1.9=py_0 -> tqdm
conda-forge/noarch::optuna==1.0.0=py_0 -> tqdm
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> tqdm[version='>=4.43.0']
Package qt conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> qt
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> qt
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyqt -> qt[version='5.6.*|5.9.*|>=5.9.7,<5.10.0a0|>=5.9.6,<5.10.0a0|>=5.9.4,<5.10.0a0']
defaults/win-64::pyqt==5.9.2=py37h6538335_2 -> qt[version='5.9.*|>=5.9.6,<5.10.0a0']
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> pyqt=5.9 -> qt[version='5.9.*|>=5.9.7,<5.10.0a0|>=5.9.6,<5.10.0a0|>=5.9.4,<5.10.0a0']
anaconda/win-64::spyder==4.1.4=py37_0 -> pyqt[version='>=5.6,<5.13'] -> qt[version='5.6.*|5.9.*|>=5.9.7,<5.10.0a0|>=5.9.6,<5.10.0a0|>=5.9.4,<5.10.0a0']
defaults/win-64::qtconsole==4.6.0=py37_1 -> pyqt -> qt[version='5.6.*|5.9.*|>=5.9.7,<5.10.0a0|>=5.9.6,<5.10.0a0|>=5.9.4,<5.10.0a0']
Package snowballstemmer conflicts for:
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> snowballstemmer[version='>=1.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> snowballstemmer[version='>=1.1']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pydocstyle[version='>=2.0.0'] -> snowballstemmer
defaults/noarch::pydocstyle==4.0.1=py_0 -> snowballstemmer
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> snowballstemmer[version='>=1.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> snowballstemmer
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> snowballstemmer
Package setuptools conflicts for:
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> setuptools
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> setuptools[version='>=18.5']
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> setuptools
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> setuptools
defaults/noarch::anaconda-project==0.8.4=py_0 -> anaconda-client -> setuptools
conda-forge/noarch::phik==0.10.0=py_0 -> joblib[version='>=0.14.1'] -> setuptools
conda-forge/noarch::stumpy==1.3.0=py_0 -> numba[version='>=0.42.0'] -> setuptools
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipython -> setuptools[version='>=18.5|>=40.0']
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> setuptools[version='>=40.0']
conda-forge/noarch::xarray==0.15.1=py_0 -> setuptools
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> setuptools
defaults/noarch::plotly==4.8.1=py_0 -> setuptools
defaults/win-64::bleach==3.1.0=py37_0 -> setuptools
intel/win-64::wheel==0.31.0=py37_3 -> setuptools
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> joblib[version='>=0.11'] -> setuptools
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> imagehash -> setuptools
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> setuptools
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> setuptools[version='>=18.5']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> setuptools
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> jupyter_contrib_core[version='>=0.3.3'] -> setuptools
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> setuptools
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> pygments -> setuptools
defaults/win-64::terminado==0.8.3=py37_0 -> pywinpty -> setuptools
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> setuptools[version='>=40.0']
defaults/win-64::pylint==2.4.4=py37_0 -> astroid[version='>=2.3.0,<2.4'] -> setuptools
defaults/noarch::pygments==2.5.2=py_0 -> setuptools
defaults/win-64::anaconda-client==1.7.2=py37_0 -> setuptools
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> jinja2[version='>=2.7'] -> setuptools
anaconda/win-64::spyder==4.1.4=py37_0 -> pygments[version='>=2.0'] -> setuptools
defaults/noarch::jinja2==2.11.1=py_0 -> setuptools
defaults/win-64::jsonschema==3.2.0=py37_0 -> setuptools
modin==0.7.3 -> distributed[version='>=2.3.2'] -> setuptools
defaults/win-64::scikit-learn==0.23.1=py37h25d0782_0 -> joblib[version='>=0.11'] -> setuptools
defaults/noarch::prompt_toolkit==3.0.3=py_0 -> pygments -> setuptools
conda-forge/noarch::descartes==1.1.0=py_4 -> matplotlib-base -> setuptools
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> setuptools
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> jinja2[version='>=2.10'] -> setuptools
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> setuptools
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> setuptools[version='>=18.5']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> jupyter_contrib_core[version='>=0.3.2'] -> setuptools
conda-forge/noarch::joblib==0.16.0=py_0 -> setuptools
defaults/win-64::pytest==5.3.5=py37_0 -> setuptools[version='>=40.0']
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1'] -> setuptools[version='>=18.5']
conda-forge/noarch::imageio-ffmpeg==0.4.2=py_0 -> setuptools
conda-forge/win-64::cmd2==0.9.15=py37_0 -> setuptools
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> setuptools
conda-forge/noarch::jinja2-time==0.2.0=py_2 -> jinja2 -> setuptools
defaults/win-64::sympy==1.5.1=py37_0 -> setuptools
defaults/win-64::distributed==2.11.0=py37_0 -> setuptools
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> setuptools
defaults/win-64::nbconvert==5.6.1=py37_0 -> bleach -> setuptools
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> jinja2[version='>2.10*'] -> setuptools
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> setuptools
defaults/win-64::nose==1.3.7=py37_2 -> setuptools
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> setuptools[version='>=40.0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> numba[version='>=0.37.0,<0.49'] -> setuptools[version='>=41.2']
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> networkx[version='>=2.4'] -> setuptools
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> setuptools
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> setuptools[version='>=18.5']
intel/win-64::pip==19.3.1=py37_2 -> setuptools
conda-forge/win-64::matplotlib-base==3.2.1=py37h911224e_0 -> setuptools
conda-forge/noarch::imagehash==4.1.0=pyh9f0ad1d_0 -> setuptools
defaults/noarch::flask==1.1.1=py_0 -> jinja2[version='>=2.10'] -> setuptools
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> setuptools
anaconda/win-64::python-language-server==0.34.1=py37_0 -> flake8[version='>=3.8.0'] -> setuptools[version='>=30.0.0']
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> joblib -> setuptools
defaults/win-64::isort==4.3.21=py37_0 -> setuptools
conda-forge/noarch::optuna==1.0.0=py_0 -> joblib -> setuptools
conda-forge/label/cf202003/noarch::munch==2.5.0=py_0 -> setuptools[version='>=17.1']
defaults/win-64::notebook==6.0.3=py37_0 -> jinja2 -> setuptools
conda-forge/noarch::moviepy==1.0.1=py_0 -> imageio-ffmpeg[version='>=0.2.0'] -> setuptools
anaconda/win-64::python-language-server==0.34.1=py37_0 -> setuptools
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> setuptools[version='>=18.5']
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> setuptools[version='>=18.5']
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> setuptools[version='>=40.0']
defaults/noarch::networkx==2.4=py_0 -> setuptools
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> setuptools[version='>=40.0']
defaults/noarch::nbformat==5.0.4=py_0 -> jsonschema[version='>=2.4,!=2.5.0'] -> setuptools
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> setuptools
plotly/noarch::plotly_express==0.4.1=py_0 -> plotly[version='>=4.1.0'] -> setuptools
defaults/win-64::qtconsole==4.6.0=py37_1 -> pygments -> setuptools
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> setuptools[version='>=40.0']
defaults/win-64::clyent==1.2.2=py37_1 -> setuptools
conda-forge/noarch::panel==0.9.5=py_1 -> markdown -> setuptools
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> setuptools
conda-forge/win-64::scikit-surprise==1.1.0=py37hbc2f12b_1002 -> setuptools
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> jinja2[version='>=2.7'] -> setuptools
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> matplotlib-base[version='>=2.2.0'] -> setuptools
anaconda/noarch::flake8==3.8.3=py_0 -> setuptools[version='>=30.0.0']
defaults/win-64::astroid==2.3.3=py37_0 -> setuptools
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> munch -> setuptools[version='>=17.1']
anaconda/noarch::pynndescent==0.4.8=py_1 -> setuptools
conda-forge/win-64::cliff==2.15.0=py37_0 -> cmd2!=0.8.3 -> setuptools
Package expat conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> expat[version='>=2.2.5,<2.3.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> expat[version='>=2.2.5,<2.3.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libkml[version='>=1.3.0,<1.4.0a0'] -> expat[version='>=2.2.5,<3.0a0|>=2.2.9,<2.3.0a0']
conda-forge/label/cf202003/win-64::libkml==1.3.0=h7e985d0_1011 -> expat[version='>=2.2.9,<2.3.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> expat[version='>=2.2.5,<2.3.0a0']
Package iniconfig conflicts for:
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> iniconfig
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest -> iniconfig
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> iniconfig
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> iniconfig
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> iniconfig
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> iniconfig
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> iniconfig
Package future conflicts for:
defaults/noarch::python-jsonrpc-server==0.3.4=py_0 -> future
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> backports.os -> future
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> future[version='>=0.15.2']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> python-jsonrpc-server[version='>=0.3.2'] -> future
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> future
Package toolz conflicts for:
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> cytoolz[version='>=0.7.3'] -> toolz[version='>=0.10.0|>=0.8.0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> toolz[version='>=0.7.4']
defaults/noarch::dask==2.11.0=py_0 -> toolz[version='>=0.7.3']
defaults/win-64::distributed==2.11.0=py37_0 -> toolz[version='>=0.7.4']
defaults/win-64::distributed==2.11.0=py37_0 -> cytoolz[version='>=0.7.4'] -> toolz[version='>=0.10.0|>=0.8.0']
defaults/noarch::dask==2.11.0=py_0 -> cytoolz[version='>=0.7.3'] -> toolz[version='>=0.10.0|>=0.8.0|>=0.8.2|>=0.7.4']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cytoolz -> toolz[version='>=0.10.0|>=0.8.0|>=0.8.2|>=0.7.3|>=0.7.4']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0'] -> toolz[version='>=0.7.3|>=0.8.2']
defaults/noarch::partd==1.1.0=py_0 -> toolz
defaults/win-64::cytoolz==0.10.1=py37he774522_0 -> toolz[version='>=0.10.0']
modin==0.7.3 -> dask[version='>=2.1.0'] -> toolz[version='>=0.7.3|>=0.8.2|>=0.7.4']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> toolz[version='>=0.7.3']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> toolz
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> toolz
Package jupyterlab conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> jupyterlab
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyterlab
Package cycler conflicts for:
conda-forge/noarch::phik==0.10.0=py_0 -> matplotlib-base[version='>=2.2.3'] -> cycler[version='>=0.10']
conda-forge/win-64::matplotlib-base==3.2.1=py37h911224e_0 -> cycler[version='>=0.10']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> matplotlib-base[version='>=2.2'] -> cycler[version='>=0.10']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cycler
conda-forge/noarch::descartes==1.1.0=py_4 -> matplotlib-base -> cycler[version='>=0.10']
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> cycler[version='>=0.10']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> matplotlib-base[version='>=3.2.0'] -> cycler[version='>=0.10']
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> cycler[version='>=0.10']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> matplotlib -> cycler[version='>=0.10']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> cycler
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> cycler[version='>=0.10']
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> matplotlib-base[version='>=2.2.0'] -> cycler[version='>=0.10']
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> cycler[version='>=0.10']
Package defusedxml conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> defusedxml
defaults/win-64::jupyter==1.0.0=py37_7 -> nbconvert -> defusedxml
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> nbconvert[version='>=4.2'] -> defusedxml
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> nbconvert -> defusedxml
anaconda/win-64::spyder==4.1.4=py37_0 -> nbconvert[version='>=4.0'] -> defusedxml
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> nbconvert -> defusedxml
defaults/win-64::nbconvert==5.6.1=py37_0 -> defusedxml
defaults/win-64::notebook==6.0.3=py37_0 -> nbconvert -> defusedxml
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> defusedxml
Package intel-openmp conflicts for:
intel/win-64::mkl_random==1.1.0=py37ha68da19_0 -> mkl -> intel-openmp[version='2019.*|2020.*']
intel/win-64::numexpr==2.7.0=py37_1 -> mkl[version='>=2018.0.0'] -> intel-openmp[version='2019.*|2020.*']
defaults/win-64::scikit-learn==0.23.1=py37h25d0782_0 -> mkl[version='>=2019.4,<2021.0a0'] -> intel-openmp[version='2019.*|2020.*']
intel/win-64::mkl_fft==1.0.15=py37ha68da19_3 -> mkl -> intel-openmp[version='2019.*|2020.*']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> intel-openmp
intel/win-64::mkl==2020.0=intel_166 -> intel-openmp=2020
intel/win-64::mkl-service==2.3.0=py37_0 -> mkl -> intel-openmp[version='2019.*|2020.*']
intel/win-64::numpy-base==1.17.4=py37_4 -> mkl -> intel-openmp[version='2019.*|2020.*']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> intel-openmp
defaults/win-64::scipy==1.5.0=py37h9439919_0 -> mkl[version='>=2019.4,<2021.0a0'] -> intel-openmp[version='2019.*|2020.*']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> mkl -> intel-openmp[version='2019.*|2020.*']
Package mkl-service conflicts for:
anaconda/win-64::py-xgboost==0.90=py37_1 -> numpy -> mkl-service[version='>=2,<3.0a0']
defaults/noarch::seaborn==0.10.0=py_0 -> numpy[version='>=1.13.3'] -> mkl-service[version='>=2,<3.0a0']
intel/win-64::mkl_random==1.1.0=py37ha68da19_0 -> numpy-base[version='>=1.1.0,<2.0a0'] -> mkl-service[version='>=2,<3.0a0|>=2.3.0|>=2.1.0']
conda-forge/noarch::xarray==0.15.1=py_0 -> numpy[version='>=1.17'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::bottleneck==1.3.2=py37h2a96729_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/label/cf202003/win-64::h5py==2.9.0=nompi_py37h9dfa0df_1103 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::scikit-learn==0.23.1=py37h25d0782_0 -> mkl-service[version='>=2,<3.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
intel/win-64::daal4py==2020.0=py37ha68da19_8 -> numpy[version='>=1.15'] -> mkl-service[version='>=2,<3.0a0']
plotly/noarch::plotly_express==0.4.1=py_0 -> numpy[version='>=1.11'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::bkcharts==0.2=py37_0 -> numpy[version='>=1.7.1'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::pywavelets==1.1.1=py37he774522_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
intel/win-64::mkl_fft==1.0.15=py37ha68da19_3 -> numpy-base[version='>=1.0.15,<2.0a0'] -> mkl-service[version='>=2,<3.0a0|>=2.3.0|>=2.1.0']
conda-forge/win-64::scikit-surprise==1.1.0=py37hbc2f12b_1002 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::datashape==0.5.4=py_1 -> numpy[version='>=1.7'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> mkl-service
defaults/win-64::patsy==0.5.1=py37_0 -> numpy[version='>=1.4.0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::moviepy==1.0.1=py_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::astropy==4.0=py37he774522_0 -> numpy[version='>=1.16.5,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> numpy[version='>=1.16.0'] -> mkl-service[version='>=2,<3.0a0']
intel/win-64::numpy==1.17.4=py37ha68da19_4 -> mkl_fft[version='>=1.0.15,<2.0a0'] -> mkl-service[version='>=2,<3.0a0|>=2.1.0']
conda-forge/noarch::imagehash==4.1.0=pyh9f0ad1d_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
intel/win-64::numba==0.48.0=np117py37_0 -> numpy[version='>=1.17,<1.18.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::stumpy==1.3.0=py_0 -> numpy[version='>=1.13'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::optuna==1.0.0=py_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> numpy[version='>=1.10'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> mkl-service
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
defaults/noarch::dask==2.11.0=py_0 -> numpy[version='>=1.13.0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> numexpr -> mkl-service[version='>=2,<3.0a0']
anaconda/noarch::pynndescent==0.4.8=py_1 -> numpy[version='>=1.13'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::phik==0.10.0=py_0 -> numpy[version='>=1.15.4'] -> mkl-service[version='>=2,<3.0a0']
intel/win-64::numpy-base==1.17.4=py37_4 -> mkl-service[version='>=2.1.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> numpy[version='>=1.0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> numpy[version='>=1.17'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::statsmodels==0.11.0=py37he774522_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::pandas-summary==0.0.41=py_1 -> numpy -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> numpy[version='>=1.11'] -> mkl-service[version='>=2,<3.0a0']
intel/win-64::numexpr==2.7.0=py37_1 -> numpy[version='>=1.17,<1.18.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::missingno==0.4.2=py_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> mkl_fft -> mkl-service[version='>=2,<3.0a0|>=2.3.0|>=2.1.0']
defaults/win-64::imageio==2.6.1=py37_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
conda-forge/win-64::matplotlib-base==3.2.1=py37h911224e_0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> numpy[version='>=1.11.3'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> numpy[version='>=1.7'] -> mkl-service[version='>=2,<3.0a0']
conda-forge/label/cf202003/win-64::shapely==1.6.4=py37ha35856d_1006 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
defaults/win-64::scipy==1.5.0=py37h9439919_0 -> mkl-service[version='>=2,<3.0a0']
Package libnetcdf conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libnetcdf[version='>=4.6.2,<4.6.3.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> libnetcdf[version='>=4.6.2,<4.6.3.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> libnetcdf[version='>=4.6.2,<4.6.3.0a0']
Package libsodium conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> pyzmq[version='>=17'] -> libsodium[version='>=1.0.16,<1.0.17.0a0']
defaults/win-64::pyzmq==18.1.1=py37ha925a31_0 -> zeromq[version='>=4.3.1,<4.3.2.0a0'] -> libsodium[version='>=1.0.16,<1.0.17.0a0']
defaults/win-64::notebook==6.0.3=py37_0 -> pyzmq[version='>=17'] -> libsodium[version='>=1.0.16,<1.0.17.0a0']
defaults/win-64::zeromq==4.3.1=h33f27b4_3 -> libsodium[version='>=1.0.16,<1.0.17.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libsodium
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> pyzmq[version='>=17'] -> libsodium[version='>=1.0.16,<1.0.17.0a0']
defaults/win-64::jupyter_client==5.3.4=py37_0 -> pyzmq[version='>=13'] -> libsodium[version='>=1.0.16,<1.0.17.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyzmq -> libsodium[version='>=1.0.16,<1.0.17.0a0|>=1.0.18,<1.0.19.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libsodium
Package krb5 conflicts for:
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> curl[version='>=7.59.0,<8.0a0'] -> krb5[version='>=1.16.1,<1.17.0a0|>=1.17.1,<1.18.0a0|>=1.18.2,<1.19.0a0|>=1.16.4,<1.17.0a0']
defaults/win-64::pycurl==7.43.0.5=py37h7a1dbc1_0 -> libcurl[version='>=7.67.0,<8.0a0'] -> krb5[version='>=1.16.1,<1.17.0a0|>=1.17.1,<1.18.0a0|>=1.18.2,<1.19.0a0|>=1.16.4,<1.17.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> curl -> krb5[version='>=1.16.1,<1.17.0a0|>=1.17.1,<1.18.0a0|>=1.18.2,<1.19.0a0|>=1.16.4,<1.17.0a0']
conda-forge/label/cf202003/win-64::libpq==11.5=hb0bdaea_1 -> krb5[version='>=1.16.3,<1.17.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libpq[version='>=11.5,<12.0a0'] -> krb5[version='>=1.14.2,<1.15.0a0|>=1.16,<1.17.0a0|>=1.16.1,<1.17.0a0|>=1.16.3,<1.17.0a0|>=1.17.1,<1.18.0a0']
conda-forge/label/cf202003/win-64::postgresql==11.5=h06f7779_1 -> krb5[version='>=1.16.3,<1.17.0a0']
conda-forge/label/cf202003/win-64::libcurl==7.68.0=h4496350_0 -> krb5[version='>=1.16.4,<1.17.0a0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> curl[version='>=7.64.1,<8.0a0'] -> krb5[version='>=1.16.1,<1.17.0a0|>=1.17.1,<1.18.0a0|>=1.18.2,<1.19.0a0|>=1.16.4,<1.17.0a0']
conda-forge/label/cf202003/win-64::curl==7.68.0=h4496350_0 -> krb5[version='>=1.16.4,<1.17.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> krb5
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> krb5
Package libtiff conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pillow -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<5.0a0']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> pillow[version='>=4.3.0'] -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libtiff
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> pillow[version='>=3.1.1'] -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<5.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libtiff[version='>=4.0.10,<5.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libtiff
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> openjpeg[version='>=2.3.1,<2.4.0a0'] -> libtiff[version='>=4.1.0,<5.0a0']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> pillow -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<5.0a0']
conda-forge/noarch::imagehash==4.1.0=pyh9f0ad1d_0 -> pillow -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<5.0a0']
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> pillow[version='>=4.0'] -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<5.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> geotiff[version='>=1.5.1,<1.5.2.0a0'] -> libtiff[version='>=4.1.0,<5.0a0']
conda-forge/label/cf202003/win-64::geotiff==1.5.1=h4b1d854_3 -> libtiff[version='>=4.0.10,<5.0a0']
defaults/win-64::imageio==2.6.1=py37_0 -> pillow -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<5.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> libtiff[version='>=4.0.10,<5.0a0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> libtiff[version='>=4.0.10,<5.0a0']
defaults/win-64::pillow==7.0.0=py37hcc1f983_0 -> libtiff[version='>=4.1.0,<5.0a0']
conda-forge/label/cf202003/win-64::openjpeg==2.3.1=h57dd2e7_3 -> libtiff[version='>=4.1.0,<5.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> libtiff[version='>=4.0.10,<5.0a0']
Package paramiko conflicts for:
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> paramiko[version='>=2.4.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> paramiko
anaconda/win-64::spyder==4.1.4=py37_0 -> paramiko[version='>=2.4.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> paramiko[version='>=2.4.0']
Package botocore conflicts for:
boto3 -> botocore[version='>=1.10.24,<1.11.0|>=1.10.32,<1.11.0|>=1.10.45,<1.11.0|>=1.10.62,<1.11.0|>=1.11.2,<1.12.0|>=1.12.111,<1.13.0|>=1.12.134,<1.13.0|>=1.12.162,<1.13.0|>=1.12.199,<1.13.0|>=1.12.234,<1.13.0|>=1.13.13,<1.14.0|>=1.13.19,<1.14.0|>=1.13.39,<1.14.0|>=1.14.0,<1.15.0|>=1.14.14,<1.15.0|>=1.15.0,<1.16.0|>=1.15.12,<1.16.0|>=1.15.39,<1.16.0|>=1.16.11,<1.17.0|>=1.17.12,<1.18.0|>=1.17.31,<1.18.0|>=1.17.37,<1.18.0|>=1.17.39,<1.18.0|>=1.17.43,<1.18.0|>=1.17.45,<1.18.0|>=1.17.48,<1.18.0|>=1.12.82,<1.13.0|>=1.12.66,<1.13.0|>=1.12.35,<1.13.0|>=1.12.21,<1.13.0|>=1.12.13,<1.13.0|>=1.12.7,<1.13.0|>=1.10.4,<1.11.0|>=1.9.18,<1.10.0|>=1.8.46,<1.9.0|>=1.8.0,<1.9.0|>=1.7.0,<1.8.0']
boto3 -> s3transfer[version='>=0.3.0,<0.4.0'] -> botocore[version='>=1.12.36,<2.0.0|>=1.3.0,<2.0.0']
anaconda/win-64::s3transfer==0.1.13=py37_0 -> botocore[version='>=1.3.0,<2.0.0']
Package backports conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backports
defaults/win-64::backports.os==0.1.1=py37_0 -> backports
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> backports
defaults/win-64::backports.shutil_get_terminal_size==1.0.0=py37_2 -> backports
defaults/win-64::get_terminal_size==1.0.0=h38e98db_0 -> backports.shutil_get_terminal_size -> backports
Package widgetsnbextension conflicts for:
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> ipywidgets[version='>=7.5.0,<8.0'] -> widgetsnbextension[version='>=3.5.0,<3.6.0']
defaults/noarch::ipywidgets==7.5.1=py_0 -> widgetsnbextension[version='>=3.5.0,<3.6.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> widgetsnbextension
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> ipywidgets[version='>=7.5.1'] -> widgetsnbextension[version='>=3.5.0,<3.6.0']
defaults/win-64::jupyter==1.0.0=py37_7 -> ipywidgets -> widgetsnbextension[version='>=1.2.6|>=3.0.0|>=3.1.0,<4.0|>=3.2.0,<4.0.0|>=3.3.0,<3.4.0|>=3.4.0,<3.5.0|>=3.5.0,<3.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipywidgets -> widgetsnbextension[version='>=1.2.6|>=3.0.0|>=3.1.0,<4.0|>=3.2.0,<4.0.0|>=3.3.0,<3.4.0|>=3.4.0,<3.5.0|>=3.5.0,<3.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> widgetsnbextension
Package numpydoc conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> numpydoc[version='>=0.6.0']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> numpydoc[version='>=0.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> numpydoc
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> numpydoc[version='>=0.6.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> numpydoc
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> jedi[version='>=0.10'] -> numpydoc
Package multipledispatch conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> multipledispatch
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> datashape[version='>=0.5.1'] -> multipledispatch[version='>=0.4.7']
conda-forge/noarch::datashape==0.5.4=py_1 -> multipledispatch[version='>=0.4.7']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> multipledispatch
Package sortedcontainers conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> intervaltree -> sortedcontainers
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sortedcontainers
defaults/win-64::sortedcollections==1.1.2=py37_0 -> sortedcontainers[version='>=2.0']
defaults/noarch::hypothesis==5.5.4=py_0 -> sortedcontainers[version='>=2.1.0,<3.0.0']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> sortedcontainers[version='!=2.0.0,!=2.0.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> sortedcontainers[version='!=2.0.0,!=2.0.1|>=2.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sortedcontainers
modin==0.7.3 -> distributed[version='>=2.3.2'] -> sortedcontainers[version='!=2.0.0,!=2.0.1']
defaults/noarch::pytest-astropy==0.8.0=py_0 -> hypothesis -> sortedcontainers[version='>=2.1.0,<3.0.0']
defaults/win-64::distributed==2.11.0=py37_0 -> sortedcontainers[version='!=2.0.0,!=2.0.1']
defaults/noarch::intervaltree==3.0.2=py_0 -> sortedcontainers
Package typing_extensions conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bokeh -> typing_extensions[version='>=3.7.4']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> typing_extensions
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> bokeh[version='>=1.1.0'] -> typing_extensions[version='>=3.7.4']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> bokeh -> typing_extensions[version='>=3.7.4']
defaults/noarch::dask==2.11.0=py_0 -> bokeh[version='>=1.0.0'] -> typing_extensions[version='>=3.7.4']
conda-forge/noarch::panel==0.9.5=py_1 -> bokeh[version='>=2.0'] -> typing_extensions[version='>=3.7.4']
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> typing_extensions[version='>=3.7.4']
Package winpty conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> winpty
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pywinpty -> winpty[version='>=0.4.3,<1.0a0']
defaults/win-64::terminado==0.8.3=py37_0 -> pywinpty -> winpty[version='>=0.4.3,<1.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> winpty
defaults/win-64::pywinpty==0.5.7=py37_0 -> winpty
Package jupyter_core conflicts for:
defaults/win-64::widgetsnbextension==3.5.1=py37_0 -> notebook[version='>=4.4.1'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> jupyter_client -> jupyter_core[version='>=4.6.0']
defaults/noarch::ipywidgets==7.5.1=py_0 -> nbformat[version='>=4.2.0'] -> jupyter_core
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> notebook[version='>=4.0'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
defaults/win-64::qtconsole==4.6.0=py37_1 -> jupyter_client[version='>=4.1'] -> jupyter_core[version='>=4.6.0']
defaults/noarch::nbformat==5.0.4=py_0 -> jupyter_core
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyter_client -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
defaults/win-64::notebook==6.0.3=py37_0 -> jupyter_core[version='>=4.6.1']
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> notebook[version='>=4.3.1'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> notebook[version='>=4.0'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> notebook[version='>=4.0'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
anaconda/win-64::spyder==4.1.4=py37_0 -> nbconvert[version='>=4.0'] -> jupyter_core
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> notebook -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> jupyter_client[version='>=5.3.4'] -> jupyter_core[version='>=4.6.0']
defaults/win-64::anaconda-client==1.7.2=py37_0 -> nbformat -> jupyter_core
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> jupyter_core
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> jupyter_core
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> jupyter_contrib_core[version='>=0.3'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> jupyter_core
defaults/noarch::jupyter_console==6.1.0=py_0 -> jupyter_client -> jupyter_core[version='>=4.6.0']
defaults/win-64::notebook==6.0.3=py37_0 -> jupyter_client[version='>=5.3.4'] -> jupyter_core[version='>=4.6.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> jupyter_core
defaults/win-64::jupyter==1.0.0=py37_7 -> nbconvert -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyter_core
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> jupyter_contrib_core[version='>=0.3'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> notebook[version='>=4.2.0'] -> jupyter_core[version='>=4.4.0|>=4.6.0|>=4.6.1']
defaults/win-64::nbconvert==5.6.1=py37_0 -> jupyter_core
defaults/win-64::jupyter_client==5.3.4=py37_0 -> jupyter_core[version='>=4.6.0']
defaults/win-64::qtconsole==4.6.0=py37_1 -> jupyter_core
Package scipy conflicts for:
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> scipy[version='>=1.4.1']
conda-forge/noarch::imagehash==4.1.0=pyh9f0ad1d_0 -> scipy
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> scikit-learn[version='>=0.20'] -> scipy
conda-forge/noarch::missingno==0.4.2=py_0 -> seaborn -> scipy[version='>=0.15.2|>=1.0.1']
defaults/win-64::statsmodels==0.11.0=py37he774522_0 -> scipy[version='>=1.0']
defaults/noarch::seaborn==0.10.0=py_0 -> scipy[version='>=1.0.1']
defaults/win-64::scikit-learn==0.23.1=py37h25d0782_0 -> scipy
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scipy
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> scipy
plotly/noarch::plotly_express==0.4.1=py_0 -> patsy[version='>=0.5'] -> scipy[version='>=0.14|>=1.0']
plotly/noarch::plotly_express==0.4.1=py_0 -> scipy[version='>=0.18']
anaconda/noarch::pynndescent==0.4.8=py_1 -> scipy[version='>=1.0']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> scipy[version='>=0.19']
defaults/win-64::patsy==0.5.1=py37_0 -> scipy
conda-forge/noarch::missingno==0.4.2=py_0 -> scipy
anaconda/win-64::py-xgboost==0.90=py37_1 -> scipy
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> imagehash -> scipy[version='>=1.1.0']
conda-forge/noarch::phik==0.10.0=py_0 -> scipy[version='>=1.1.0']
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> scipy
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> scipy[version='>=1.3.1']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> scipy
conda-forge/noarch::optuna==1.0.0=py_0 -> scipy
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-image -> scipy[version='>=0.14|>=0.15.2|>=0.17|>=0.19|>=1.0.1|>=1.0']
conda-forge/noarch::stumpy==1.3.0=py_0 -> scipy[version='>=1.2.1']
anaconda/noarch::pynndescent==0.4.8=py_1 -> scikit-learn[version='>=0.19'] -> scipy
defaults/win-64::statsmodels==0.11.0=py37he774522_0 -> patsy[version='>=0.5.1'] -> scipy
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> scipy
Package msys2-conda-epoch conflicts for:
defaults/win-64::m2w64-expat==2.1.1=2 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> msys2-conda-epoch
conda-forge/win-64::libffi==3.2.1=h6538335_1007 -> m2w64-gcc-libs -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-gcc-libs==5.3.0=7 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-libiconv==1.14=6 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::pywinpty==0.5.7=py37_0 -> m2w64-gcc-libs -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-gettext==0.19.7=2 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-xz==5.2.2=2 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> msys2-conda-epoch
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> m2w64-xz -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-libwinpthread-git==5.0.0.4634.697f757=2 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-gcc-libgfortran==5.3.0=6 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-gcc-libs-core==5.3.0=7 -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> m2w64-gcc-libgfortran -> msys2-conda-epoch[version='>=20160418']
anaconda/win-64::libxgboost==0.90=1 -> m2w64-gcc-libs -> msys2-conda-epoch[version='>=20160418']
defaults/win-64::m2w64-gmp==6.1.0=2 -> msys2-conda-epoch[version='>=20160418']
Package ipykernel conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> qtconsole[version='>=4.6.0'] -> ipykernel[version='>=4.1|>=5.1.3']
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> ipykernel[version='>=5.1.3']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> notebook[version='>=4.0'] -> ipykernel
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> notebook[version='>=4.2.0'] -> ipykernel
defaults/win-64::qtconsole==4.6.0=py37_1 -> ipykernel[version='>=4.1']
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipykernel[version='>=4.5.1']
defaults/win-64::jupyter==1.0.0=py37_7 -> ipywidgets -> ipykernel[version='>=4.1|>=4.2.2|>=4.5.1']
defaults/win-64::jupyter==1.0.0=py37_7 -> ipykernel
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> notebook[version='>=4.0'] -> ipykernel
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ipykernel
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> notebook[version='>=4.0'] -> ipykernel
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipykernel
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipywidgets -> ipykernel[version='>4.9.0|>=4.1|>=4.2.2|>=4.5.1|>=5.1.3|>=4.8.2']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> notebook -> ipykernel
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> notebook[version='>=4.0'] -> ipykernel
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> notebook[version='>=4.3.1'] -> ipykernel
defaults/win-64::notebook==6.0.3=py37_0 -> ipykernel
defaults/win-64::widgetsnbextension==3.5.1=py37_0 -> notebook[version='>=4.4.1'] -> ipykernel
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> notebook[version='>=4.0'] -> ipykernel
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> ipywidgets[version='>=7.5.1'] -> ipykernel[version='>=4.5.1']
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> ipykernel[version='>=4.7']
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> ipywidgets[version='>=7.5.0,<8.0'] -> ipykernel[version='>=4.5.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipykernel
Package click conflicts for:
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> click[version='>=4.0,<8']
defaults/win-64::distributed==2.11.0=py37_0 -> click[version='>=6.6']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> click
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> click[version='>=2.0|>=5.1|>=6.6']
conda-forge/noarch::hiplot==0.1.17=py_0 -> flask -> click[version='>=2.0|>=5.1']
conda-forge/label/cf202003/noarch::cligj==0.5.0=py_0 -> click[version='>=4.0']
modin==0.7.3 -> distributed[version='>=2.3.2'] -> click[version='>=6.6']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> click-plugins[version='>=1.0'] -> click[version='>=3.0|>=4.0']
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> click[version='>=5.0']
conda-forge/label/cf202003/noarch::click-plugins==1.1.1=py_0 -> click[version='>=3.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> click
defaults/noarch::flask==1.1.1=py_0 -> click[version='>=5.1']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> click[version='>=4.0,<8']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> click[version='>=6.6']
conda-forge/noarch::flask-compress==1.5.0=pyh9f0ad1d_0 -> flask -> click[version='>=2.0|>=5.1']
Package boost-cpp conflicts for:
conda-forge/label/cf202003/win-64::libkml==1.3.0=h7e985d0_1011 -> boost-cpp[version='>=1.72.0,<1.72.1.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libkml[version='>=1.3.0,<1.4.0a0'] -> boost-cpp[version='>=1.72.0,<1.72.1.0a0']
Package psutil conflicts for:
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> psutil[version='>=5.2|>=5.3']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> psutil
modin==0.7.3 -> distributed[version='>=2.3.2'] -> psutil[version='>=5.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> psutil[version='>=5.0|>=5.3|>=5.2']
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> psutil
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest-openfiles[version='>=0.3.1'] -> psutil
defaults/win-64::distributed==2.11.0=py37_0 -> psutil[version='>=5.0']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> psutil[version='>=5.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> psutil
anaconda/win-64::spyder==4.1.4=py37_0 -> psutil[version='>=5.3']
Package werkzeug conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> werkzeug
defaults/noarch::flask==1.1.1=py_0 -> werkzeug[version='>=0.14']
conda-forge/noarch::hiplot==0.1.17=py_0 -> flask -> werkzeug[version='>=0.14|>=0.15|>=0.7|>=0.7,<1.0.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> werkzeug
conda-forge/noarch::flask-compress==1.5.0=pyh9f0ad1d_0 -> flask -> werkzeug[version='>=0.14|>=0.15|>=0.7|>=0.7,<1.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> flask -> werkzeug[version='>=0.14|>=0.15|>=0.7|>=0.7,<1.0.0']
Package colorama conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> colorama[version='>=0.3.5']
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> colorama
conda-forge/noarch::optuna==1.0.0=py_0 -> colorlog -> colorama
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> colorama
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> colorama
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> colorama
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> colorama
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> colorama
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> colorama
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> colorama
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> colorama
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> colorama
defaults/win-64::coloredlogs==10.0=py37_0 -> colorama
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> colorama
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pylint -> colorama
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> colorama[version='>=0.3.5']
conda-forge/win-64::cliff==2.15.0=py37_0 -> cmd2!=0.8.3 -> colorama
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> colorama
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1'] -> colorama
defaults/win-64::pytest==5.3.5=py37_0 -> colorama
conda-forge/win-64::cmd2==0.9.15=py37_0 -> colorama
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> colorama
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> colorama
conda-forge/win-64::colorlog==4.1.0=py37_1 -> colorama
anaconda/win-64::spyder==4.1.4=py37_0 -> pylint[version='>=1.0'] -> colorama[version='>=0.3.5']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> colorama
defaults/win-64::pylint==2.4.4=py37_0 -> colorama
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> coloredlogs -> colorama
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> colorama
Package decorator conflicts for:
defaults/win-64::traitlets==4.3.3=py37_0 -> decorator
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> decorator
conda-forge/noarch::moviepy==1.0.1=py_0 -> decorator[version='>=4.0.2,<5.0']
defaults/win-64::nbconvert==5.6.1=py37_0 -> traitlets[version='>=4.2'] -> decorator
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> traitlets -> decorator
defaults/noarch::nbformat==5.0.4=py_0 -> traitlets[version='>=4.1'] -> decorator
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> decorator
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> traitlets[version='>=4.1'] -> decorator
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1'] -> decorator
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> decorator
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> decorator
defaults/noarch::networkx==2.4=py_0 -> decorator[version='>=4.3.0']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> networkx[version='>=2.0'] -> decorator[version='>=3.4.0|>=4.1.0|>=4.3.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> networkx -> decorator[version='>=3.4.0|>=4.1.0|>=4.3.0']
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> decorator
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> traitlets -> decorator
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> decorator
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> decorator
defaults/win-64::qtconsole==4.6.0=py37_1 -> traitlets -> decorator
defaults/win-64::notebook==6.0.3=py37_0 -> traitlets[version='>=4.2.1'] -> decorator
defaults/win-64::jupyter_core==4.6.1=py37_0 -> traitlets -> decorator
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> decorator
defaults/win-64::jupyter_client==5.3.4=py37_0 -> traitlets -> decorator
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> networkx[version='>=2.4'] -> decorator[version='>=4.3.0']
Package packaging conflicts for:
defaults/win-64::pytest==5.3.5=py37_0 -> packaging
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> packaging
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> packaging
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> bokeh -> packaging[version='>=16.8']
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> packaging
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> packaging
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> packaging
conda-forge/noarch::panel==0.9.5=py_1 -> bokeh[version='>=2.0'] -> packaging[version='>=16.8']
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> packaging
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> packaging
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> packaging
defaults/noarch::dask==2.11.0=py_0 -> bokeh[version='>=1.0.0'] -> packaging[version='>=16.8']
defaults/win-64::nbconvert==5.6.1=py37_0 -> bleach -> packaging
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> packaging
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bokeh -> packaging[version='>=16.8']
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> packaging
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> packaging
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> bokeh[version='>=1.1.0'] -> packaging[version='>=16.8']
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> packaging
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> packaging[version='>=16.8']
Package pyzmq conflicts for:
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> jupyter_client[version='>=5.3.4'] -> pyzmq[version='>=13']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyzmq
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> jupyter_client -> pyzmq[version='>=13|>=13.0']
defaults/win-64::notebook==6.0.3=py37_0 -> pyzmq[version='>=17']
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> pyzmq[version='>=17']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> pyzmq[version='>=17']
anaconda/win-64::spyder==4.1.4=py37_0 -> pyzmq[version='>=17']
defaults/noarch::jupyter_console==6.1.0=py_0 -> jupyter_client -> pyzmq[version='>=13|>=13.0']
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> notebook[version='>=4.0'] -> pyzmq[version='>=17']
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> notebook[version='>=4.2.0'] -> pyzmq[version='>=17']
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> notebook[version='>=4.0'] -> pyzmq[version='>=17']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> notebook[version='>=4.0'] -> pyzmq[version='>=17']
defaults/win-64::jupyter_client==5.3.4=py37_0 -> pyzmq[version='>=13']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> notebook[version='>=4.0'] -> pyzmq[version='>=17']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyzmq
defaults/win-64::jupyter==1.0.0=py37_7 -> notebook -> pyzmq[version='>=17']
defaults/win-64::widgetsnbextension==3.5.1=py37_0 -> notebook[version='>=4.4.1'] -> pyzmq[version='>=17']
defaults/win-64::qtconsole==4.6.0=py37_1 -> jupyter_client[version='>=4.1'] -> pyzmq[version='>=13|>=13.0']
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> notebook[version='>=4.3.1'] -> pyzmq[version='>=17']
defaults/win-64::notebook==6.0.3=py37_0 -> jupyter_client[version='>=5.3.4'] -> pyzmq[version='>=13']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> notebook[version='>=4.0'] -> pyzmq[version='>=17']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> notebook -> pyzmq[version='>=17']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyter_client -> pyzmq[version='>=13|>=13.0|>=17']
Package jsonschema conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyterlab_server -> jsonschema[version='>=2.4,!=2.5.0|>=3.0.1']
defaults/win-64::nbconvert==5.6.1=py37_0 -> nbformat[version='>=4.4'] -> jsonschema[version='>=2.4,!=2.5.0']
defaults/noarch::ipywidgets==7.5.1=py_0 -> nbformat[version='>=4.2.0'] -> jsonschema[version='>=2.4,!=2.5.0']
defaults/win-64::anaconda-client==1.7.2=py37_0 -> nbformat -> jsonschema[version='>=2.4,!=2.5.0']
defaults/win-64::notebook==6.0.3=py37_0 -> nbformat -> jsonschema[version='>=2.4,!=2.5.0']
defaults/noarch::nbformat==5.0.4=py_0 -> jsonschema[version='>=2.4,!=2.5.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> jsonschema
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> jupyterlab_server[version='>=1.0.0,<2.0.0'] -> jsonschema[version='>=3.0.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jsonschema
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> jsonschema[version='>=3.0.1']
Package wcwidth conflicts for:
conda-forge/win-64::cliff==2.15.0=py37_0 -> cmd2!=0.8.3 -> wcwidth
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> wcwidth
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> wcwidth
conda-forge/win-64::cmd2==0.9.15=py37_0 -> wcwidth
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> wcwidth
defaults/noarch::jupyter_console==6.1.0=py_0 -> prompt_toolkit[version='>=2.0.0,<3.1.0,!=3.0.0,!=3.0.1'] -> wcwidth
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> wcwidth
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> wcwidth
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> wcwidth
defaults/win-64::pytest==5.3.5=py37_0 -> wcwidth
defaults/noarch::prompt_toolkit==3.0.3=py_0 -> wcwidth
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> wcwidth
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> prompt_toolkit[version='>=2.0.0,<4,!=3.0.0,!=3.0.1'] -> wcwidth
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> wcwidth
Package pyopenssl conflicts for:
defaults/noarch::botocore==1.12.189=py_0 -> urllib3[version='>=1.20,<1.26'] -> pyopenssl[version='>=0.14']
conda-forge/noarch::requests==2.24.0=pyh9f0ad1d_0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> pyopenssl[version='>=0.14']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> urllib3 -> pyopenssl[version='>=0.14']
intel/win-64::urllib3==1.24.1=py37_2 -> pyopenssl[version='>=0.14']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyopenssl
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyopenssl
Package libxslt conflicts for:
defaults/win-64::lxml==4.5.0=py37h1350720_0 -> libxslt[version='>=1.1.33,<2.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libxslt
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> lxml -> libxslt[version='>=1.1.32,<2.0a0|>=1.1.33,<2.0a0|>=1.1.34,<2.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libxslt
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> lxml -> libxslt[version='>=1.1.32,<2.0a0|>=1.1.33,<2.0a0|>=1.1.34,<2.0a0']
Package qtawesome conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> qtawesome
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> qtawesome[version='>=0.5.7']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> qtawesome
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> qtawesome[version='>=0.4.1|>=0.5.7']
anaconda/win-64::spyder==4.1.4=py37_0 -> qtawesome[version='>=0.5.7']
Package astropy conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> astropy
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> astropy
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> astropy[version='>=4.0']
Package intervaltree conflicts for:
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> intervaltree
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> intervaltree
anaconda/win-64::spyder==4.1.4=py37_0 -> intervaltree
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> intervaltree
Package libxml2 conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libspatialite[version='>=4.3.0a,<4.4.0a0'] -> libxml2[version='>=2.9.4,<2.10.0a0|>=2.9.8,<2.10.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> libxml2[version='>=2.9.9,<2.10.0a0']
defaults/win-64::lxml==4.5.0=py37h1350720_0 -> libxslt[version='>=1.1.33,<2.0a0'] -> libxml2[version='>=2.9.10,<2.10.0a0|>=2.9.8,<2.10.0a0']
conda-forge/label/cf202003/win-64::libspatialite==4.3.0a=h01b1fc4_1030 -> libxml2[version='>=2.9.9,<2.10.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libxml2
intel/win-64::python-libarchive-c==2.8=py37_13 -> libarchive -> libxml2[version='>=2.9.10,<2.10.0a0|>=2.9.4,<2.10.0a0|>=2.9.7,<2.10.0a0|>=2.9.8,<2.10.0a0|>=2.9.9,<2.10.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libxml2[version='>=2.9.9,<2.10.0a0']
defaults/win-64::libarchive==3.3.3=h0643e63_5 -> libxml2[version='>=2.9.8,<2.10.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libarchive -> libxml2[version='>=2.9.10,<2.10.0a0|>=2.9.4,<2.10.0a0|>=2.9.7,<2.10.0a0|>=2.9.8,<2.10.0a0|>=2.9.9,<2.10.0a0']
conda-forge/label/cf202003/win-64::postgresql==11.5=h06f7779_1 -> libxml2[version='>=2.9.9,<2.10.0a0']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> lxml -> libxml2[version='>=2.9.10,<2.10.0a0|>=2.9.9,<2.10.0a0|>=2.9.8,<2.10.0a0|>=2.9.7,<2.10.0a0|>=2.9.4,<2.10.0a0']
defaults/win-64::libxslt==1.1.33=h579f668_0 -> libxml2[version='>=2.9.8,<2.10.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> libxml2[version='>=2.9.9,<2.10.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libxml2
defaults/win-64::lxml==4.5.0=py37h1350720_0 -> libxml2[version='>=2.9.9,<2.10.0a0']
Package more-itertools conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
conda-forge/win-64::importlib-metadata==1.6.1=py37hc8dfbb8_0 -> zipp[version='>=0.5'] -> more-itertools
defaults/win-64::pytest==5.3.5=py37_0 -> more-itertools[version='>=4.0']
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> more-itertools
defaults/noarch::jaraco.itertools==5.0.0=py_0 -> more-itertools[version='>=4.0.0']
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> more-itertools
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
defaults/win-64::importlib_metadata==1.5.0=py37_0 -> zipp[version='>=0.5'] -> more-itertools
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> more-itertools[version='>=4.0,<6.0|>=4.0|>=4.0.0']
Package urllib3 conflicts for:
boto3 -> botocore[version='>=1.17.48,<1.18.0'] -> urllib3[version='>=1.20,<1.24|>=1.20,<1.25|>=1.20,<1.26']
defaults/win-64::anaconda-client==1.7.2=py37_0 -> requests[version='>=2.9.1'] -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> requests -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> urllib3
conda-forge/noarch::moviepy==1.0.1=py_0 -> requests[version='>=2.8.1,<3.0'] -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
anaconda/win-64::s3transfer==0.1.13=py37_0 -> botocore[version='>=1.3.0,<2.0.0'] -> urllib3[version='>=1.20,<1.24|>=1.20,<1.25|>=1.20,<1.26']
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> requests[version='>=2.18.0'] -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
conda-forge/noarch::requests==2.24.0=pyh9f0ad1d_0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> requests[version='>=2.23.0'] -> urllib3[version='>=1.21.1|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> requests -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
conda-forge/noarch::pyct==0.4.6=py_0 -> requests -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> urllib3
defaults/noarch::botocore==1.12.189=py_0 -> urllib3[version='>=1.20,<1.26']
defaults/noarch::anaconda-project==0.8.4=py_0 -> requests -> urllib3[version='>=1.21.1|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
Package m2w64-gmp conflicts for:
defaults/win-64::m2w64-gettext==0.19.7=2 -> m2w64-gcc-libs -> m2w64-gmp
anaconda/win-64::libxgboost==0.90=1 -> m2w64-gcc-libs -> m2w64-gmp
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> m2w64-gmp
conda-forge/win-64::libffi==3.2.1=h6538335_1007 -> m2w64-gcc-libs -> m2w64-gmp
defaults/win-64::m2w64-gcc-libgfortran==5.3.0=6 -> m2w64-gcc-libs-core -> m2w64-gmp
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> m2w64-gmp
defaults/win-64::pywinpty==0.5.7=py37_0 -> m2w64-gcc-libs -> m2w64-gmp
defaults/win-64::m2w64-gcc-libs-core==5.3.0=7 -> m2w64-gmp
defaults/win-64::m2w64-xz==5.2.2=2 -> m2w64-gcc-libs -> m2w64-gmp
defaults/win-64::m2w64-gcc-libs==5.3.0=7 -> m2w64-gmp
Package anaconda-project conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> anaconda-project
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> anaconda-project
Package sphinxcontrib-htmlhelp conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> sphinxcontrib-htmlhelp
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> sphinxcontrib-htmlhelp
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> sphinxcontrib-htmlhelp
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sphinxcontrib-htmlhelp
Package cytoolz conflicts for:
defaults/win-64::distributed==2.11.0=py37_0 -> cytoolz[version='>=0.7.4']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask -> cytoolz[version='>=0.7.3|>=0.8.2|>=0.7.4']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0'] -> cytoolz[version='>=0.7.3|>=0.8.2']
defaults/noarch::dask==2.11.0=py_0 -> cytoolz[version='>=0.7.3']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> cytoolz[version='>=0.7.3']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> cytoolz[version='>=0.7.4|>=0.8.2']
modin==0.7.3 -> dask[version='>=2.1.0'] -> cytoolz[version='>=0.7.3|>=0.8.2|>=0.7.4']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> cytoolz
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cytoolz
Package atomicwrites conflicts for:
defaults/noarch::pytest-doctestplus==0.5.0=py_0 -> pytest[version='>=3.0'] -> atomicwrites[version='>=1.0']
defaults/win-64::pytest-arraydiff==0.3=py37h39e3cac_0 -> pytest -> atomicwrites[version='>=1.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> atomicwrites[version='>=1.2.0']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> atomicwrites[version='>=1.2.0']
defaults/win-64::pytest==5.3.5=py37_0 -> atomicwrites[version='>=1.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> atomicwrites
defaults/noarch::pytest-openfiles==0.4.0=py_0 -> pytest[version='>=3.1'] -> atomicwrites[version='>=1.0']
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest[version='>=3.1'] -> atomicwrites[version='>=1.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> atomicwrites
defaults/win-64::pytest-remotedata==0.3.2=py37_0 -> pytest[version='>=3.1'] -> atomicwrites[version='>=1.0']
defaults/noarch::pytest-astropy-header==0.1.2=py_0 -> pytest[version='>=3.0'] -> atomicwrites[version='>=1.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest -> atomicwrites[version='>=1.0|>=1.2.0']
Package requests conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> anaconda-client -> requests[version='>2.0.0|>=1.2.3|>=2.9.1|>=2.5.0|>=2.0.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> requests[version='>2.0.0|>=2.0.0|>=2.5.0']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> requests
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> jupyterlab_server[version='>=1.0.0,<2.0.0'] -> requests
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> requests
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> requests[version='>=2.18.0']
conda-forge/noarch::colorcet==2.0.1=py_0 -> pyct[version='>=0.4.4'] -> requests
defaults/win-64::anaconda-client==1.7.2=py37_0 -> requests[version='>=2.9.1']
conda-forge/noarch::panel==0.9.5=py_1 -> pyct[version='>=0.4.4'] -> requests
defaults/noarch::anaconda-project==0.8.4=py_0 -> anaconda-client -> requests[version='>=2.9.1']
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> requests
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> requests[version='>2.0.0|>=2.0.0|>=2.5.0']
conda-forge/noarch::moviepy==1.0.1=py_0 -> requests[version='>=2.8.1,<3.0']
conda-forge/noarch::pyct==0.4.6=py_0 -> requests
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> requests
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> requests
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> bokeh -> requests[version='>=1.2.3']
defaults/noarch::anaconda-project==0.8.4=py_0 -> requests
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> requests[version='>=2.23.0']
Package zeromq conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> zeromq
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> zeromq
defaults/win-64::notebook==6.0.3=py37_0 -> pyzmq[version='>=17'] -> zeromq[version='>=4.2.5,<4.2.6.0a0|>=4.3.1,<4.4.0a0|>=4.3.2,<4.3.3.0a0|>=4.3.1,<4.3.2.0a0']
anaconda/win-64::spyder==4.1.4=py37_0 -> pyzmq[version='>=17'] -> zeromq[version='>=4.2.5,<4.2.6.0a0|>=4.3.1,<4.4.0a0|>=4.3.2,<4.3.3.0a0|>=4.3.1,<4.3.2.0a0']
defaults/win-64::pyzmq==18.1.1=py37ha925a31_0 -> zeromq[version='>=4.3.1,<4.3.2.0a0']
defaults/win-64::jupyter_client==5.3.4=py37_0 -> pyzmq[version='>=13'] -> zeromq[version='>=4.2.5,<4.2.6.0a0|>=4.3.1,<4.4.0a0|>=4.3.2,<4.3.3.0a0|>=4.3.1,<4.3.2.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyzmq -> zeromq[version='>=4.2.5,<4.2.6.0a0|>=4.3.1,<4.4.0a0|>=4.3.2,<4.3.3.0a0|>=4.3.1,<4.3.2.0a0']
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> pyzmq[version='>=17'] -> zeromq[version='>=4.2.5,<4.2.6.0a0|>=4.3.1,<4.4.0a0|>=4.3.2,<4.3.3.0a0|>=4.3.1,<4.3.2.0a0']
Package pandas conflicts for:
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> pandas[version='>=0.25.3,!=1.0.1,!=1.0.0,!=1.0.2']
defaults/win-64::bkcharts==0.2=py37_0 -> pandas
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pandas
modin==0.7.3 -> dask[version='>=2.1.0'] -> pandas[version='>=0.21.0|>=0.23.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> pandas[version='>=0.20.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pandas
plotly/noarch::plotly_express==0.4.1=py_0 -> statsmodels[version='>=0.9.0'] -> pandas[version='>=0.14|>=0.21']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask -> pandas[version='>=0.14|>=0.14.0|>=0.19.0|>=0.21.0|>=0.23.0|>=0.22.0|>=0.21']
conda-forge/noarch::phik==0.10.0=py_0 -> pandas[version='>=0.23.4']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> missingno[version='>=0.4.2'] -> pandas[version='>=0.23.4|>=0.25.3']
conda-forge/noarch::pandas-summary==0.0.41=py_1 -> pandas
defaults/noarch::seaborn==0.10.0=py_0 -> pandas[version='>=0.22.0']
plotly/noarch::plotly_express==0.4.1=py_0 -> pandas[version='>=0.20.0']
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> pandas[version='>=0.25.3']
conda-forge/noarch::missingno==0.4.2=py_0 -> pandas
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> pandas[version='>=0.20.3']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> bokeh -> pandas[version='>=0.18.0|>=0.19.0|>=0.21.0|>=0.23.0|>=0.25|>=0.24|>=0.19.2']
defaults/win-64::statsmodels==0.11.0=py37he774522_0 -> pandas[version='>=0.21']
conda-forge/noarch::missingno==0.4.2=py_0 -> seaborn -> pandas[version='>=0.14.0|>=0.22.0']
modin==0.7.3 -> pandas==1.0.3
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> pandas[version='>=0.23']
conda-forge/noarch::xarray==0.15.1=py_0 -> pandas[version='>=0.25']
defaults/noarch::dask==2.11.0=py_0 -> pandas[version='>=0.23.0']
Package hypothesis conflicts for:
conda-forge/win-64::cmd2==0.9.15=py37_0 -> attrs -> hypothesis
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> hypothesis
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> attrs -> hypothesis
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> attrs[version='>=17'] -> hypothesis
defaults/noarch::pytest-astropy==0.8.0=py_0 -> hypothesis
defaults/win-64::astropy==4.0=py37he774522_0 -> pytest-astropy -> hypothesis
Package pyasn1 conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> paramiko[version='>=2.4.0'] -> pyasn1[version='>=0.1.7']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyasn1
Package m2w64-gcc-libs-core conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> m2w64-gcc-libs-core
defaults/win-64::m2w64-gcc-libgfortran==5.3.0=6 -> m2w64-gcc-libs-core
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> m2w64-gcc-libs-core
defaults/win-64::m2w64-xz==5.2.2=2 -> m2w64-gcc-libs -> m2w64-gcc-libs-core
defaults/win-64::pywinpty==0.5.7=py37_0 -> m2w64-gcc-libs -> m2w64-gcc-libs-core
defaults/win-64::m2w64-gcc-libs==5.3.0=7 -> m2w64-gcc-libs-core
anaconda/win-64::libxgboost==0.90=1 -> m2w64-gcc-libs -> m2w64-gcc-libs-core
defaults/win-64::m2w64-gettext==0.19.7=2 -> m2w64-gcc-libs -> m2w64-gcc-libs-core
conda-forge/win-64::libffi==3.2.1=h6538335_1007 -> m2w64-gcc-libs -> m2w64-gcc-libs-core
Package pytest-openfiles conflicts for:
defaults/win-64::astropy==4.0=py37he774522_0 -> pytest-astropy -> pytest-openfiles[version='>=0.2|>=0.3.0|>=0.3|>=0.3.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest-openfiles
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest-openfiles[version='>=0.3.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest-astropy -> pytest-openfiles[version='>=0.2|>=0.3.0|>=0.3|>=0.3.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pytest-openfiles
Package blosc conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytables -> blosc[version='>=1.14.3,<2.0a0|>=1.14.4,<2.0a0|>=1.15.0,<2.0a0|>=1.16.3,<2.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> blosc
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> blosc[version='>=1.16.3,<2.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> blosc
Package brotlipy conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> urllib3 -> brotlipy[version='>=0.6.0']
defaults/noarch::botocore==1.12.189=py_0 -> urllib3[version='>=1.20,<1.26'] -> brotlipy[version='>=0.6.0']
conda-forge/noarch::requests==2.24.0=pyh9f0ad1d_0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> brotlipy[version='>=0.6.0']
conda-forge/noarch::flask-compress==1.5.0=pyh9f0ad1d_0 -> brotlipy
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> brotlipy
conda-forge/noarch::hiplot==0.1.17=py_0 -> flask-compress -> brotlipy
Package dask conflicts for:
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> dask
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-image -> dask[version='>=0.5']
modin==0.7.3 -> dask[version='>=2.1.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask
Package proj conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> geotiff[version='>=1.5.1,<1.5.2.0a0'] -> proj[version='>=6.2.1,<6.2.2.0a0|>=7.0.1,<7.0.2.0a0']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> pyproj[version='>=2.2.0'] -> proj[version='>=6.2.1,<6.2.2.0a0|>=7.0.1,<7.0.2.0a0']
Package geotiff conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> geotiff[version='>=1.5.1,<1.5.2.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> geotiff[version='>=1.5.1,<1.5.2.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> geotiff[version='>=1.5.1,<1.5.2.0a0']
Package contextvars conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> contextvars
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> contextvars
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> contextvars
modin==0.7.3 -> distributed[version='>=2.3.2'] -> contextvars
Package hdf5 conflicts for:
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> hdf5[version='>=1.10.4,<1.10.5.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> hdf5
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> hdf5[version='>=1.10.4,<1.10.5.0a0']
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> hdf5[version='>=1.10.4,<1.10.5.0a0']
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> hdf5[version='>=1.10.4,<1.10.5.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> hdf5
conda-forge/label/cf202003/win-64::kealib==1.4.10=heacb130_1003 -> hdf5[version='>=1.10.4,<1.10.5.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> hdf5[version='>=1.10.4,<1.10.5.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> h5py -> hdf5[version='1.10.1|1.10.2.*|1.10.3.*|>=1.10.1,<1.10.2.0a0|>=1.10.2,<1.10.3.0a0|>=1.10.4,<1.10.5.0a0|>=1.8.20,<1.9.0a0|>=1.8.18,<1.8.19.0a0|>=1.8.18,<1.9.0a0|1.8.17|1.8.16']
conda-forge/label/cf202003/win-64::h5py==2.9.0=nompi_py37h9dfa0df_1103 -> hdf5[version='>=1.10.4,<1.10.5.0a0']
Package tblib conflicts for:
defaults/win-64::distributed==2.11.0=py37_0 -> tblib[version='>=1.6.0']
modin==0.7.3 -> distributed[version='>=2.3.2'] -> tblib[version='>=1.6.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> tblib
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> tblib[version='>=1.6.0']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> tblib[version='>=1.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> tblib
Package cmd2 conflicts for:
conda-forge/win-64::cliff==2.15.0=py37_0 -> cmd2!=0.8.3
conda-forge/noarch::optuna==1.0.0=py_0 -> cliff -> cmd2!=0.8.3
Package python-editor conflicts for:
conda-forge/noarch::optuna==1.0.0=py_0 -> alembic -> python-editor[version='>=0.3']
conda-forge/noarch::alembic==1.4.0=py_0 -> python-editor[version='>=0.3']
Package scikit-image conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> scikit-image
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-image
Package gettext conflicts for:
conda-forge/win-64::pygobject==3.36.1=py37hf6b2db1_0 -> glib[version='>=2.58.3,<3.0a0'] -> gettext[version='>=0.19.8.1,<1.0a0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> glib[version='>=2.58.3,<3.0a0'] -> gettext[version='>=0.19.8.1,<1.0a0']
conda-forge/win-64::gobject-introspection==1.64.1=py37hf0dd101_1 -> glib[version='>=2.58.3,<3.0a0'] -> gettext[version='>=0.19.8.1,<1.0a0']
conda-forge/win-64::glib==2.64.3=he4de6d7_0 -> gettext[version='>=0.19.8.1,<1.0a0']
Package xlwings conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> xlwings
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> xlwings
Package pexpect conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pexpect
anaconda/win-64::spyder==4.1.4=py37_0 -> pexpect[version='>=4.4.0']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> pexpect[version='>=4.4.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> pexpect[version='>=4.4.0']
Package postgresql conflicts for:
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> postgresql
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> postgresql
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> postgresql
Package networkx conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-image -> networkx[version='>=1.8,<2.0|>=1.8|>=2.0']
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> networkx[version='>=2.4']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> networkx[version='>=2.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> networkx
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> networkx
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> visions[version='>=0.4.4'] -> networkx[version='>=2.4']
Package pandoc conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pandoc
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> nbconvert -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> nbconvert[version='>=4.2'] -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> nbconvert -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
defaults/win-64::jupyter==1.0.0=py37_7 -> nbconvert -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pandoc
defaults/win-64::nbconvert==5.6.1=py37_0 -> pandoc[version='>=1.12.1']
anaconda/win-64::spyder==4.1.4=py37_0 -> nbconvert[version='>=4.0'] -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> nbconvert -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
defaults/win-64::notebook==6.0.3=py37_0 -> nbconvert -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
Package libpq conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> postgresql -> libpq[version='10.3|10.3|10.4|10.4|10.5|10.5|11.1|11.1|11.2|11.2|12.2|11.5',build='hb0bdaea_1|h0990ea7_0|h5fe2233_0|h1ac0bd9_0|h1ac0bd9_0|h5fe2233_0|h3235a2c_0|h3235a2c_0|h3235a2c_0|h4410098_0|h4410098_0|hc4dcbb0_0']
conda-forge/label/cf202003/win-64::postgresql==11.5=h06f7779_1 -> libpq==11.5=hb0bdaea_1
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> libpq[version='>=11.5,<12.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> libpq[version='>=11.5,<12.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libpq[version='>=11.5,<12.0a0']
Package joblib conflicts for:
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> joblib
conda-forge/noarch::optuna==1.0.0=py_0 -> joblib
defaults/win-64::scikit-learn==0.23.1=py37h25d0782_0 -> joblib[version='>=0.11']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> nltk -> joblib[version='>=0.11']
conda-forge/win-64::scikit-surprise==1.1.0=py37hbc2f12b_1002 -> joblib
conda-forge/noarch::phik==0.10.0=py_0 -> joblib[version='>=0.14.1']
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> joblib[version='>=0.11']
anaconda/win-64::py-xgboost==0.90=py37_1 -> scikit-learn -> joblib[version='>=0.11']
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> scikit-learn -> joblib[version='>=0.11']
anaconda/noarch::pynndescent==0.4.8=py_1 -> scikit-learn[version='>=0.19'] -> joblib[version='>=0.11']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> joblib
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> phik[version='>=0.9.10'] -> joblib[version='>=0.14.1']
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> scikit-learn[version='>=0.20'] -> joblib[version='>=0.11']
Package terminado conflicts for:
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> notebook[version='>=4.0'] -> terminado[version='>=0.8.1']
defaults/win-64::widgetsnbextension==3.5.1=py37_0 -> notebook[version='>=4.4.1'] -> terminado[version='>=0.8.1']
defaults/win-64::jupyter==1.0.0=py37_7 -> notebook -> terminado[version='>=0.8.1']
defaults/win-64::notebook==6.0.3=py37_0 -> terminado[version='>=0.8.1']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> terminado
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> notebook[version='>=4.3.1'] -> terminado[version='>=0.8.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> terminado
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> terminado
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> notebook[version='>=4.0'] -> terminado[version='>=0.8.1']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> notebook -> terminado[version='>=0.8.1']
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> notebook[version='>=4.2.0'] -> terminado[version='>=0.8.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> notebook -> terminado[version='>=0.8.1']
conda-forge/win-64::jupyter_highlight_selected_word==0.2.0=py37_1000 -> notebook[version='>=4.0'] -> terminado[version='>=0.8.1']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> notebook[version='>=4.0'] -> terminado[version='>=0.8.1']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> notebook[version='>=4.0'] -> terminado[version='>=0.8.1']
Package prompt-toolkit conflicts for:
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0']
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0|>=3.0.6,<3.0.7.0a0|>=3.0.5,<3.0.6.0a0|>=3.0.4,<3.0.5.0a0|>=3.0.7,<3.0.8.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipython -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0|>=3.0.6,<3.0.7.0a0|>=3.0.5,<3.0.6.0a0|>=3.0.4,<3.0.5.0a0|>=3.0.7,<3.0.8.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> prompt-toolkit
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0']
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> prompt_toolkit[version='>=2.0.0,<4,!=3.0.0,!=3.0.1'] -> prompt-toolkit[version='>=3.0.4,<3.0.5.0a0|>=3.0.5,<3.0.6.0a0|>=3.0.6,<3.0.7.0a0|>=3.0.7,<3.0.8.0a0']
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1'] -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0']
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> prompt-toolkit[version='!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0']
Package openmp conflicts for:
intel/win-64::mkl_random==1.1.0=py37ha68da19_0 -> icc_rt[version='>=16.0.3'] -> openmp=2018
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> icc_rt -> openmp=2018
intel/win-64::mkl_fft==1.0.15=py37ha68da19_3 -> icc_rt[version='>=16.0.3'] -> openmp=2018
intel/win-64::numba==0.48.0=np117py37_0 -> icc_rt -> openmp
intel/win-64::numexpr==2.7.0=py37_1 -> mkl[version='>=2018.0.0'] -> openmp=2018
intel/win-64::mkl-service==2.3.0=py37_0 -> mkl -> openmp=2018
intel/win-64::numpy-base==1.17.4=py37_4 -> icc_rt[version='>=16.0.3'] -> openmp=2018
Package dask-core conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask -> dask-core[version='0.15.2.*|0.15.3.*|0.15.4.*|0.16.0.*|0.16.1.*|0.17.0.*|0.17.1.*|0.17.2.*|0.17.3.*|0.17.4.*|0.17.5.*|0.18.0.*|0.18.1.*|0.18.2.*|0.19.0.*|0.19.1.*|0.19.2.*|0.19.3.*|0.19.4.*|0.20.0.*|0.20.1.*|0.20.2.*|1.0.0.*|1.1.1.*|1.1.2.*|1.1.3.*|1.1.4.*|1.1.5.*|1.2.0.*|1.2.2.*|2.0.0.*|2.1.0.*|2.10.0.*|2.10.1.*|2.11.0.*|2.12.0.*|2.13.0.*|2.14.0.*|2.15.0.*|2.16.0.*|2.17.0.*|2.17.2.*|2.18.1.*|2.19.0.*|2.20.0.*|2.22.0.*|2.23.0.*|2.24.0.*|2.9.2.*|2.9.1.*|2.9.0.*|2.8.1.*|2.8.0.*|2.7.0.*|2.6.0.*|2.5.2.*|2.5.0.*|2.4.0.*|2.3.0.*|2.2.0.*|2.25.0.*|>=2.9.0|>=2.7.0|>=2.5.2|>=2|>=0.18.0|>=0.17.0|>=0.16.0|>=0.15.2|>=0.15.0|>=0.9.0|>=0.15']
defaults/noarch::dask==2.11.0=py_0 -> dask-core=2.11.0
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> dask-core
defaults/win-64::distributed==2.11.0=py37_0 -> dask-core[version='>=2.9.0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0'] -> dask-core[version='0.18.0.*|0.18.1.*|0.18.2.*|0.19.0.*|0.19.1.*|0.19.2.*|0.19.3.*|0.19.4.*|0.20.0.*|0.20.1.*|0.20.2.*|1.0.0.*|1.1.1.*|1.1.2.*|1.1.3.*|1.1.4.*|1.1.5.*|1.2.0.*|1.2.2.*|2.0.0.*|2.1.0.*|2.10.0.*|2.10.1.*|2.11.0.*|2.12.0.*|2.13.0.*|2.14.0.*|2.15.0.*|2.16.0.*|2.17.0.*|2.17.2.*|2.18.1.*|2.19.0.*|2.20.0.*|2.22.0.*|2.23.0.*|2.24.0.*|2.9.2.*|2.9.1.*|2.9.0.*|2.8.1.*|2.8.0.*|2.7.0.*|2.6.0.*|2.5.2.*|2.5.0.*|2.4.0.*|2.3.0.*|2.2.0.*|2.25.0.*']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask-core
modin==0.7.3 -> dask[version='>=2.1.0'] -> dask-core[version='2.1.0.*|2.10.0.*|2.10.1.*|2.11.0.*|2.12.0.*|2.13.0.*|2.14.0.*|2.15.0.*|2.16.0.*|2.17.0.*|2.17.2.*|2.18.1.*|2.19.0.*|2.20.0.*|2.22.0.*|2.23.0.*|2.24.0.*|2.9.2.*|2.9.1.*|2.9.0.*|2.8.1.*|2.8.0.*|2.7.0.*|2.6.0.*|2.5.2.*|2.5.0.*|2.4.0.*|2.3.0.*|2.2.0.*|2.25.0.*|>=2.9.0|>=2.7.0|>=2.5.2|>=2']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> dask-core[version='>=2.9.0']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> dask-core[version='>=0.15.0']
Package param conflicts for:
conda-forge/noarch::colorcet==2.0.1=py_0 -> param[version='>=1.7.0']
conda-forge/noarch::panel==0.9.5=py_1 -> pyct[version='>=0.4.4'] -> param[version='>=1.7.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> param[version='>=1.9.3,<2.0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> param[version='>=1.6.1']
conda-forge/noarch::pyct-core==0.4.6=py_0 -> param[version='>=1.7.0']
conda-forge/noarch::panel==0.9.5=py_1 -> param[version='>=1.9.3']
conda-forge/noarch::pyct==0.4.6=py_0 -> pyct-core=0.4.6 -> param[version='>=1.7.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> panel[version='>=0.7.0'] -> param[version='>=1.9.2|>=1.9.3']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> colorcet[version='>=0.9.0'] -> param[version='>=1.7.0']
conda-forge/noarch::pyviz_comms==0.7.5=pyh9f0ad1d_0 -> param
Package pandocfilters conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pandocfilters
defaults/win-64::jupyter==1.0.0=py37_7 -> nbconvert -> pandocfilters[version='>=1.4.1']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> nbconvert -> pandocfilters[version='>=1.4.1']
defaults/win-64::notebook==6.0.3=py37_0 -> nbconvert -> pandocfilters[version='>=1.4.1']
defaults/win-64::nbconvert==5.6.1=py37_0 -> pandocfilters[version='>=1.4.1']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> nbconvert -> pandocfilters[version='>=1.4.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pandocfilters
anaconda/win-64::spyder==4.1.4=py37_0 -> nbconvert[version='>=4.0'] -> pandocfilters[version='>=1.4.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> nbconvert -> pandocfilters[version='>=1.4.1']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> nbconvert[version='>=4.2'] -> pandocfilters[version='>=1.4.1']
Package pytest-astropy conflicts for:
defaults/win-64::astropy==4.0=py37he774522_0 -> pytest-astropy
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest-astropy
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pytest-astropy
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> astropy[version='>=4.0'] -> pytest-astropy
Package sphinxcontrib conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sphinxcontrib
defaults/noarch::sphinxcontrib-websupport==1.2.0=py_0 -> sphinxcontrib
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinxcontrib
Package backports.shutil_which conflicts for:
defaults/win-64::terminado==0.8.3=py37_0 -> pywinpty -> backports.shutil_which
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pywinpty -> backports.shutil_which
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backports.shutil_which
Package backcall conflicts for:
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> backcall
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> backcall
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> backcall
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> backcall
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> backcall
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> backcall
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backcall
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1'] -> backcall
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> backcall
Package msgpack-python conflicts for:
modin==0.7.3 -> distributed[version='>=2.3.2'] -> msgpack-python[version='>=0.6.0']
defaults/win-64::distributed==2.11.0=py37_0 -> msgpack-python[version='>=0.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> msgpack-python[version='>=0.6.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> msgpack-python
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> msgpack-python[version='>=0.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> msgpack-python
Package pynacl conflicts for:
defaults/noarch::paramiko==2.7.1=py_0 -> pynacl[version='>=1.0.1']
anaconda/win-64::spyder==4.1.4=py37_0 -> paramiko[version='>=2.4.0'] -> pynacl[version='>=1.0.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pynacl
Package alabaster conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> alabaster
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> alabaster
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> alabaster[version='>=0.7,<0.8']
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> alabaster[version='>=0.7,<0.8']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> alabaster[version='>=0.7,<0.8']
Package libspatialindex conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> rtree[version='>=0.8.3'] -> libspatialindex[version='>=1.9.3,<1.9.4.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libspatialindex
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> rtree -> libspatialindex[version='>=1.9.3,<1.9.4.0a0']
defaults/win-64::rtree==0.9.3=py37h21ff451_0 -> libspatialindex[version='>=1.9.3,<1.9.4.0a0']
Package m2w64-gcc-libgfortran conflicts for:
defaults/win-64::m2w64-gcc-libs==5.3.0=7 -> m2w64-gcc-libgfortran
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> m2w64-gcc-libgfortran
defaults/win-64::m2w64-xz==5.2.2=2 -> m2w64-gcc-libs -> m2w64-gcc-libgfortran
conda-forge/win-64::libffi==3.2.1=h6538335_1007 -> m2w64-gcc-libs -> m2w64-gcc-libgfortran
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> m2w64-gcc-libgfortran
defaults/win-64::pywinpty==0.5.7=py37_0 -> m2w64-gcc-libs -> m2w64-gcc-libgfortran
anaconda/win-64::libxgboost==0.90=1 -> m2w64-gcc-libs -> m2w64-gcc-libgfortran
defaults/win-64::m2w64-gettext==0.19.7=2 -> m2w64-gcc-libs -> m2w64-gcc-libgfortran
Package imagesize conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> imagesize
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> imagesize
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> imagesize
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> imagesize
Package pysocks conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pysocks
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pysocks
intel/win-64::urllib3==1.24.1=py37_2 -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']
conda-forge/noarch::requests==2.24.0=pyh9f0ad1d_0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> urllib3 -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']
defaults/noarch::botocore==1.12.189=py_0 -> urllib3[version='>=1.20,<1.26'] -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']
Package html5lib conflicts for:
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> html5lib
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> html5lib
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> html5lib
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> html5lib
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bleach -> html5lib[version='>=0.999,!=0.9999,!=0.99999,<0.99999999|>=0.99999999|>=0.99999999pre,!=1.0b1,!=1.0b2,!=1.0b3,!=1.0b4,!=1.0b5,!=1.0b6,!=1.0b7,!=1.0b8']
defaults/win-64::nbconvert==5.6.1=py37_0 -> bleach -> html5lib[version='>=0.999,!=0.9999,!=0.99999,<0.99999999|>=0.99999999|>=0.99999999pre,!=1.0b1,!=1.0b2,!=1.0b3,!=1.0b4,!=1.0b5,!=1.0b6,!=1.0b7,!=1.0b8']
Package backports.functools_lru_cache conflicts for:
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> backports.functools_lru_cache
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> astroid -> backports.functools_lru_cache
conda-forge/noarch::jinja2-time==0.2.0=py_2 -> arrow -> backports.functools_lru_cache
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> backports.functools_lru_cache
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> backports.functools_lru_cache
anaconda/win-64::spyder==4.1.4=py37_0 -> pylint[version='>=1.0'] -> backports.functools_lru_cache
defaults/win-64::pylint==2.4.4=py37_0 -> isort[version='>=4.2.5,<5'] -> backports.functools_lru_cache
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pylint -> backports.functools_lru_cache
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backports.functools_lru_cache
defaults/win-64::beautifulsoup4==4.8.2=py37_0 -> soupsieve[version='>=1.2'] -> backports.functools_lru_cache
Package pywin32 conflicts for:
defaults/noarch::nbformat==5.0.4=py_0 -> jupyter_core -> pywin32[version='>=1.0']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> jupyter_core -> pywin32[version='>=1.0']
defaults/win-64::qtconsole==4.6.0=py37_1 -> jupyter_client[version='>=4.1'] -> pywin32[version='>=1.0']
intel/win-64::menuinst==1.4.16=py37_0 -> pywin32
defaults/win-64::notebook==6.0.3=py37_0 -> jupyter_client[version='>=5.3.4'] -> pywin32[version='>=1.0']
defaults/noarch::jupyter_console==6.1.0=py_0 -> jupyter_client -> pywin32[version='>=1.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pywin32
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> jupyter_client -> pywin32[version='>=1.0']
defaults/win-64::jupyter_client==5.3.4=py37_0 -> pywin32[version='>=1.0']
defaults/win-64::nbconvert==5.6.1=py37_0 -> jupyter_core -> pywin32[version='>=1.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pywin32
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> jupyter_client[version='>=5.3.4'] -> pywin32[version='>=1.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> keyring -> pywin32
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> jupyter_core -> pywin32[version='>=1.0']
defaults/win-64::xlwings==0.17.1=py37_0 -> pywin32
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyter_client -> pywin32[version='>=1.0']
defaults/win-64::jupyter_core==4.6.1=py37_0 -> pywin32[version='>=1.0']
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> jupyter_core -> pywin32[version='>=1.0']
Package shapely conflicts for:
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> shapely
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> shapely
Package tangled-up-in-unicode conflicts for:
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> tangled-up-in-unicode[version='>=0.0.6']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> visions[version='>=0.4.4'] -> tangled-up-in-unicode[version='>=0.0.4']
conda-forge/noarch::visions==0.4.4=pyh9f0ad1d_0 -> tangled-up-in-unicode[version='>=0.0.4']
Package patsy conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> patsy
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> statsmodels -> patsy[version='>=0.4.0|>=0.5.1']
plotly/noarch::plotly_express==0.4.1=py_0 -> statsmodels[version='>=0.9.0'] -> patsy[version='>=0.4.0|>=0.5.1']
defaults/win-64::statsmodels==0.11.0=py37he774522_0 -> patsy[version='>=0.5.1']
plotly/noarch::plotly_express==0.4.1=py_0 -> patsy[version='>=0.5']
conda-forge/noarch::missingno==0.4.2=py_0 -> seaborn -> patsy
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> patsy
Package backports_abc conflicts for:
defaults/win-64::jupyter_client==5.3.4=py37_0 -> tornado[version='>=4.1'] -> backports_abc[version='>=0.4']
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> tornado -> backports_abc[version='>=0.4']
defaults/noarch::anaconda-project==0.8.4=py_0 -> tornado[version='>=4.2'] -> backports_abc[version='>=0.4']
defaults/win-64::distributed==2.11.0=py37_0 -> tornado[version='>=5'] -> backports_abc[version='>=0.4']
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> tornado[version='!=6.0.0,!=6.0.1,!=6.0.2'] -> backports_abc[version='>=0.4']
defaults/win-64::notebook==6.0.3=py37_0 -> tornado[version='>=5.0'] -> backports_abc[version='>=0.4']
defaults/win-64::terminado==0.8.3=py37_0 -> tornado[version='>=4'] -> backports_abc[version='>=0.4']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backports_abc
conda-forge/win-64::matplotlib-base==3.2.1=py37h911224e_0 -> tornado -> backports_abc[version='>=0.4']
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> tornado[version='>=5.1'] -> backports_abc[version='>=0.4']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> tornado -> backports_abc[version='>=0.4']
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> tornado[version='>=4.2'] -> backports_abc[version='>=0.4']
conda-forge/noarch::jupyter_contrib_core==0.3.3=py_2 -> tornado -> backports_abc[version='>=0.4']
defaults/win-64::matplotlib==2.2.3=py37hd159220_0 -> tornado -> backports_abc[version='>=0.4']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> tornado -> backports_abc[version='>=0.4']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> tornado -> backports_abc[version='>=0.4']
Package cryptography-vectors conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cryptography -> cryptography-vectors=2.3
intel/win-64::urllib3==1.24.1=py37_2 -> cryptography[version='>=1.3.4'] -> cryptography-vectors=2.3
intel/win-64::pyopenssl==17.5.0=py37_2 -> cryptography[version='>=2.1.4'] -> cryptography-vectors=2.3
Package ipython conflicts for:
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> ipykernel[version='>=5.1.3'] -> ipython[version='>=5.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ipython
defaults/win-64::jupyter==1.0.0=py37_7 -> ipykernel -> ipython[version='>=4.0.0|>=4.0|>=5.0']
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipykernel -> ipython[version='>=4.0.0|>=4.0|>=5.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipykernel -> ipython[version='>=4.0.0|>=4.0|>=5.0']
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0']
defaults/win-64::qtconsole==4.6.0=py37_1 -> ipykernel[version='>=4.1'] -> ipython[version='>=4.0.0|>=4.0|>=5.0']
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipykernel[version='>=4.5.1'] -> ipython[version='>=4.0|>=5.0']
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> ipykernel[version='>=4.7'] -> ipython[version='>=4.0.0|>=4.0|>=5.0']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> ipywidgets[version='>=7.5.1'] -> ipython[version='>=4.0.0']
defaults/win-64::notebook==6.0.3=py37_0 -> ipykernel -> ipython[version='>=4.0.0|>=4.0|>=5.0']
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1']
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipython
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> jupyter_latex_envs[version='>=1.3.8'] -> ipython
Package wrapt conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> astroid -> wrapt=1.11
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> wrapt
defaults/win-64::astroid==2.3.3=py37_0 -> wrapt
defaults/win-64::pylint==2.4.4=py37_0 -> astroid[version='>=2.3.0,<2.4'] -> wrapt
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> wrapt
Package pytest-astropy-header conflicts for:
defaults/win-64::astropy==4.0=py37he774522_0 -> pytest-astropy -> pytest-astropy-header[version='>=0.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pytest-astropy-header
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytest-astropy -> pytest-astropy-header[version='>=0.1']
defaults/noarch::pytest-astropy==0.8.0=py_0 -> pytest-astropy-header[version='>=0.1']
Package yapf conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> yapf
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> yapf
anaconda/win-64::python-language-server==0.34.1=py37_0 -> yapf
Package spyder-kernels conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> spyder-kernels[version='0.*|>=0.1,<1|>=0.4.2,<1|>=0.4.3,<1|>=0.5.0,<1|>=1.8.1,<2.0.0|>=1.9.0,<1.10.0|>=1.9.1,<1.10.0|>=1.9.2,<1.10.0|>=1.8.1,<1.9.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder-kernels
anaconda/win-64::spyder==4.1.4=py37_0 -> spyder-kernels[version='>=1.9.2,<1.10.0']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> spyder-kernels[version='>=1.8.1,<1.9.0|>=1.8.1,<2.0.0|>=1.9.0,<1.10.0|>=1.9.1,<1.10.0|>=1.9.2,<1.10.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> spyder-kernels
Package mock conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytables -> mock
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> mock
conda-forge/label/cf202003/win-64::pytables==3.5.2=py37h6a20dd8_0 -> mock
Package matplotlib-base conflicts for:
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> matplotlib-base[version='>=2.2']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> matplotlib-base
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> matplotlib -> matplotlib-base[version='3.1.2|3.1.2|3.1.2|3.1.3|3.1.3|3.1.3|>=3.2.1,<3.2.2.0a0|>=3.2.2,<3.2.3.0a0|>=3.3.1,<3.3.2.0a0',build='py38h64f37c6_1|py36h64f37c6_1|py36h64f37c6_0|py37h64f37c6_0|py38h64f37c6_0|py37h64f37c6_1']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> phik[version='>=0.9.10'] -> matplotlib-base[version='>=2.2.3']
conda-forge/noarch::descartes==1.1.0=py_4 -> matplotlib-base
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> matplotlib-base[version='3.1.2|3.1.2|3.1.2|3.1.3|3.1.3|3.1.3|>=3.2.1,<3.2.2.0a0|>=3.2.2,<3.2.3.0a0|>=3.3.1,<3.3.2.0a0',build='py38h64f37c6_1|py36h64f37c6_1|py36h64f37c6_0|py37h64f37c6_0|py38h64f37c6_0|py37h64f37c6_1']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> matplotlib-base[version='>=3.2.0']
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> matplotlib-base[version='>=2.2.0']
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> matplotlib-base[version='3.1.2|3.1.2|3.1.2|3.1.3|3.1.3|3.1.3|>=3.2.1,<3.2.2.0a0|>=3.2.2,<3.2.3.0a0|>=3.3.1,<3.3.2.0a0',build='py38h64f37c6_1|py36h64f37c6_1|py36h64f37c6_0|py37h64f37c6_0|py38h64f37c6_0|py37h64f37c6_1']
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> matplotlib-base[version='3.1.2|3.1.2|3.1.2|3.1.3|3.1.3|3.1.3|>=3.2.1,<3.2.2.0a0|>=3.2.2,<3.2.3.0a0|>=3.3.1,<3.3.2.0a0',build='py38h64f37c6_1|py36h64f37c6_1|py36h64f37c6_0|py37h64f37c6_0|py38h64f37c6_0|py37h64f37c6_1']
conda-forge/noarch::phik==0.10.0=py_0 -> matplotlib-base[version='>=2.2.3']
Package argh conflicts for:
defaults/win-64::watchdog==0.10.2=py37_0 -> argh[version='>=0.24.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> argh
anaconda/win-64::spyder==4.1.4=py37_0 -> watchdog -> argh[version='>=0.24.1']
Package heapdict conflicts for:
defaults/win-64::distributed==2.11.0=py37_0 -> zict[version='>=0.1.3'] -> heapdict
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> heapdict
defaults/noarch::zict==1.0.0=py_0 -> heapdict
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> heapdict
Package entrypoints conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> entrypoints
defaults/win-64::nbconvert==5.6.1=py37_0 -> entrypoints[version='>=0.2.2']
defaults/win-64::keyring==21.1.0=py37_0 -> entrypoints
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> nbconvert -> entrypoints[version='>=0.2.2']
anaconda/win-64::spyder==4.1.4=py37_0 -> keyring -> entrypoints[version='>=0.2.2']
defaults/win-64::qtconsole==4.6.0=py37_1 -> jupyter_client[version='>=4.1'] -> entrypoints
defaults/win-64::notebook==6.0.3=py37_0 -> jupyter_client[version='>=5.3.4'] -> entrypoints[version='>=0.2.2']
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> nbconvert[version='>=4.2'] -> entrypoints[version='>=0.2.2']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> nbconvert -> entrypoints[version='>=0.2.2']
anaconda/win-64::spyder-kernels==1.9.2=py37_0 -> jupyter_client[version='>=5.3.4'] -> entrypoints
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> entrypoints
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> jupyter_client -> entrypoints
defaults/noarch::jupyter_console==6.1.0=py_0 -> jupyter_client -> entrypoints
defaults/win-64::jupyter==1.0.0=py37_7 -> nbconvert -> entrypoints[version='>=0.2.2']
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> nbconvert -> entrypoints[version='>=0.2.2']
Package itsdangerous conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> itsdangerous
conda-forge/noarch::flask-compress==1.5.0=pyh9f0ad1d_0 -> flask -> itsdangerous[version='>=0.21|>=0.24']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> flask -> itsdangerous[version='>=0.21|>=0.24']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> itsdangerous
conda-forge/noarch::hiplot==0.1.17=py_0 -> flask -> itsdangerous[version='>=0.21|>=0.24']
defaults/noarch::flask==1.1.1=py_0 -> itsdangerous[version='>=0.24']
Package ujson conflicts for:
anaconda/win-64::python-language-server==0.34.1=py37_0 -> ujson[version='<=1.35']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> python-jsonrpc-server[version='>=0.3.2'] -> ujson
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ujson
defaults/noarch::python-jsonrpc-server==0.3.4=py_0 -> ujson
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> ujson[version='<=1.35']
Package unicodecsv conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> unicodecsv
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> unicodecsv
Package parso conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> parso
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> jedi[version='>=0.10'] -> parso[version='0.1.0|>=0.1.0,<0.2|>=0.2.0|>=0.3.0|>=0.5.0|>=0.5.2|>=0.7.0|>=0.7.0,<0.8.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> parso=0.7.0
anaconda/win-64::python-language-server==0.34.1=py37_0 -> jedi[version='>=0.17.0,<0.18.0a0'] -> parso[version='>=0.7.0|>=0.7.0,<0.8.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> parso
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jedi -> parso[version='0.1.0|>=0.1.0,<0.2|>=0.2.0|>=0.3.0|>=0.5.0|>=0.5.2|>=0.7.0|>=0.7.0,<0.8.0|0.7.0.*|0.5.2.*']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> parso[version='0.5.2.*|0.7.0.*']
anaconda/win-64::jedi==0.17.1=py37_0 -> parso[version='>=0.7.0,<0.8.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> jedi=0.17.1 -> parso[version='>=0.7.0,<0.8.0']
Package progress conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> progress
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> progress
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> progress
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pip -> progress
Package qtpy conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> qtpy
defaults/noarch::qtawesome==0.6.1=py_0 -> qtpy
anaconda/win-64::spyder==4.1.4=py37_0 -> qtpy[version='>=1.5.0']
defaults/win-64::jupyter==1.0.0=py37_7 -> qtconsole -> qtpy
anaconda/win-64::spyder==4.1.4=py37_0 -> qtawesome[version='>=0.5.7'] -> qtpy
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> qtpy[version='>=1.1|>=1.2.0|>=1.5.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> qtpy
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> qtpy[version='>=1.5.0']
Package rope conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> rope[version='>=0.10.5']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> rope[version='>=0.10.5']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> rope
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> rope[version='>=0.10.5|>=0.9.4']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> rope
Package typing conflicts for:
conda-forge/win-64::bokeh==2.1.0=py37hc8dfbb8_0 -> typing_extensions[version='>=3.7.4'] -> typing[version='>=3.7.4']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> typing
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> typing
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> typing
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> typing
conda-forge/noarch::optuna==1.0.0=py_0 -> typing
Package ply conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ply
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ply
Package asn1crypto conflicts for:
defaults/noarch::paramiko==2.7.1=py_0 -> cryptography[version='>=2.5'] -> asn1crypto[version='>=0.21.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> asn1crypto
intel/win-64::cryptography==2.7=py37_0 -> asn1crypto[version='>=0.21.0']
intel/win-64::urllib3==1.24.1=py37_2 -> cryptography[version='>=1.3.4'] -> asn1crypto[version='>=0.21.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> asn1crypto
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cryptography -> asn1crypto[version='>=0.21.0']
intel/win-64::pyopenssl==17.5.0=py37_2 -> cryptography[version='>=2.1.4'] -> asn1crypto[version='>=0.21.0']
Package bleach conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> nbconvert[version='>=4.0'] -> bleach
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> nbconvert -> bleach
defaults/win-64::notebook==6.0.3=py37_0 -> nbconvert -> bleach
conda-forge/win-64::jupyter_nbextensions_configurator==0.4.1=py37_0 -> nbconvert -> bleach
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> bleach
defaults/win-64::nbconvert==5.6.1=py37_0 -> bleach
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bleach
defaults/win-64::jupyter==1.0.0=py37_7 -> nbconvert -> bleach
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> nbconvert[version='>=4.2'] -> bleach
Package libssh2 conflicts for:
defaults/win-64::pycurl==7.43.0.5=py37h7a1dbc1_0 -> libcurl[version='>=7.67.0,<8.0a0'] -> libssh2[version='>=1.8.2,<1.9.0a0|>=1.8.2,<2.0a0|>=1.9.0,<2.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libssh2
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> curl -> libssh2[version='1.*|>=1.8.0,<2.0a0|>=1.8.2,<2.0a0|>=1.9.0,<2.0a0|>=1.8.2,<1.9.0a0']
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> libssh2
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libnetcdf[version='>=4.6.2,<4.6.3.0a0'] -> libssh2
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> curl[version='>=7.59.0,<8.0a0'] -> libssh2[version='>=1.8.0,<2.0a0|>=1.8.2,<2.0a0|>=1.9.0,<2.0a0|>=1.8.2,<1.9.0a0']
conda-forge/label/cf202003/win-64::curl==7.68.0=h4496350_0 -> libssh2[version='>=1.8.2,<1.9.0a0']
conda-forge/label/cf202003/win-64::libcurl==7.68.0=h4496350_0 -> libssh2[version='>=1.8.2,<1.9.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libssh2
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> curl[version='>=7.64.1,<8.0a0'] -> libssh2[version='>=1.8.2,<1.9.0a0|>=1.8.2,<2.0a0|>=1.9.0,<2.0a0']
Package prompt_toolkit conflicts for:
conda-forge/noarch::hiplot==0.1.17=py_0 -> ipython[version='>=7.0.1'] -> prompt_toolkit[version='>=2.0.0,<3|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1']
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> prompt_toolkit[version='>=1.0.4,<2.0.0|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1|>=2.0.0,<3']
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> prompt_toolkit[version='>=1.0.4,<2.0.0|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1|>=2.0.0,<3']
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> prompt_toolkit[version='>=1.0.4,<2.0.0|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1|>=2.0.0,<3']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> prompt_toolkit[version='>=1.0.4,<2.0.0|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1|>=2.0.0,<3']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> prompt_toolkit
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> prompt_toolkit[version='>=1.0.4,<2.0.0|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1|>=2.0.0,<3']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipython -> prompt_toolkit[version='>=1.0.0,<2|>=1.0.4,<2.0.0|>=2.0.0|>=2.0.0,<4,!=3.0.0,!=3.0.1|>=2.0.0,<3|>=2.0.0,<3.1.0,!=3.0.0,!=3.0.1|>=2.0.0,<2.1.0']
defaults/noarch::jupyter_console==6.1.0=py_0 -> prompt_toolkit[version='>=2.0.0,<3.1.0,!=3.0.0,!=3.0.1']
defaults/win-64::jupyter==1.0.0=py37_7 -> jupyter_console -> prompt_toolkit[version='>=1.0.0,<2|>=2.0.0,<2.1.0|>=2.0.0,<3.1.0,!=3.0.0,!=3.0.1']
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> prompt_toolkit[version='>=2.0.0,<4,!=3.0.0,!=3.0.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> prompt_toolkit
Package boto conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> boto
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> boto
Package pympler conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> attrs -> pympler
conda-forge/win-64::cmd2==0.9.15=py37_0 -> attrs -> pympler
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> attrs[version='>=17'] -> pympler
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> pympler
Package pixman conflicts for:
conda-forge/win-64::pycairo==1.19.1=py37h6430cfb_3 -> cairo[version='>=1.16.0,<1.17.0a0'] -> pixman[version='>=0.38.0,<0.39.0a0']
conda-forge/win-64::gobject-introspection==1.64.1=py37hf0dd101_1 -> cairo[version='>=1.16.0,<1.17.0a0'] -> pixman[version='>=0.38.0,<0.39.0a0']
conda-forge/win-64::cairo==1.16.0=h63a05c6_1001 -> pixman[version='>=0.38.0,<0.39.0a0']
Package hdf4 conflicts for:
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> hdf4[version='>=4.2.13,<4.3.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> hdf4[version='>=4.2.13,<4.3.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> hdf4[version='>=4.2.13,<4.3.0a0']
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> hdf4[version='>=4.2.13,<4.3.0a0']
Package configparser conflicts for:
defaults/win-64::jsonschema==3.2.0=py37_0 -> importlib_metadata -> configparser[version='>=3.5']
defaults/win-64::pluggy==0.13.1=py37_0 -> importlib_metadata[version='>=0.12'] -> configparser[version='>=3.5']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> entrypoints -> configparser[version='>=3.5']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pydocstyle[version='>=2.0.0'] -> configparser
defaults/win-64::path==13.1.0=py37_0 -> importlib_metadata[version='>=0.5'] -> configparser[version='>=3.5']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> configparser
anaconda/win-64::spyder==4.1.4=py37_0 -> pylint[version='>=1.0'] -> configparser
defaults/win-64::inflect==4.1.0=py37_0 -> importlib_metadata -> configparser[version='>=3.5']
defaults/win-64::pytest==5.3.5=py37_0 -> importlib_metadata[version='>=0.12'] -> configparser[version='>=3.5']
defaults/win-64::nbconvert==5.6.1=py37_0 -> entrypoints[version='>=0.2.2'] -> configparser
defaults/win-64::keyring==21.1.0=py37_0 -> entrypoints -> configparser[version='>=3.5']
Package cfitsio conflicts for:
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> cfitsio[version='>=3.470,<3.471.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> cfitsio[version='>=3.470,<3.471.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> cfitsio[version='>=3.470,<3.471.0a0']
Package get_terminal_size conflicts for:
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> get_terminal_size
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> get_terminal_size
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> get_terminal_size
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> get_terminal_size
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> get_terminal_size
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> get_terminal_size
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> get_terminal_size
Package bottleneck conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bottleneck
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> bottleneck
Package flask conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> flask
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> flask
conda-forge/noarch::hiplot==0.1.17=py_0 -> flask
conda-forge/noarch::flask-compress==1.5.0=pyh9f0ad1d_0 -> flask
Package proj4 conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libspatialite[version='>=4.3.0a,<4.4.0a0'] -> proj4[version='>=4.9.3,<4.9.4.0a0|>=5.1.0,<5.1.1.0a0|>=5.2.0,<5.2.1.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> proj4[version='>=6.1.1,<6.1.2.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> proj4[version='>=6.1.1,<6.1.2.0a0']
conda-forge/label/cf202003/win-64::geotiff==1.5.1=h4b1d854_3 -> proj4[version='>=6.1.1,<6.1.2.0a0']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> pyproj[version='>=2.2.0'] -> proj4[version='>=6.1.1,<6.1.2.0a0']
conda-forge/label/cf202003/win-64::pyproj==2.3.1=py37he1416cd_0 -> proj4[version='>=6.1.1,<6.1.2.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> proj4[version='>=6.1.1,<6.1.2.0a0']
conda-forge/label/cf202003/win-64::libspatialite==4.3.0a=h01b1fc4_1030 -> proj4[version='>=6.1.1,<6.1.2.0a0']
Package pyreadline conflicts for:
conda-forge/label/cf202003/win-64::h5py==2.9.0=nompi_py37h9dfa0df_1103 -> pyreadline
defaults/win-64::humanfriendly==8.2=py37_0 -> pyreadline
conda-forge/win-64::cmd2==0.9.15=py37_0 -> pyreadline
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyreadline
defaults/win-64::coloredlogs==10.0=py37_0 -> humanfriendly[version='>=4.7'] -> pyreadline
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyreadline
conda-forge/win-64::cliff==2.15.0=py37_0 -> cmd2!=0.8.3 -> pyreadline
Package _low_priority conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libarchive -> _low_priority
intel/win-64::python-libarchive-c==2.8=py37_13 -> libarchive -> _low_priority
Package soupsieve conflicts for:
conda-forge/noarch::hiplot==0.1.17=py_0 -> beautifulsoup4 -> soupsieve[version='>=1.2']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> soupsieve
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> soupsieve
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> beautifulsoup4 -> soupsieve[version='>=1.2']
defaults/win-64::beautifulsoup4==4.8.2=py37_0 -> soupsieve[version='>=1.2']
Package isort conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pylint -> isort[version='>=4.2.5|>=4.2.5,<5|>=4.2.5,<6']
anaconda/win-64::spyder==4.1.4=py37_0 -> pylint[version='>=1.0'] -> isort[version='>=4.2.5|>=4.2.5,<5|>=4.2.5,<6']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pylint -> isort[version='>=4.2.5|>=4.2.5,<5|>=4.2.5,<6']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> isort
defaults/win-64::pylint==2.4.4=py37_0 -> isort[version='>=4.2.5,<5']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> isort
Package keyring conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> keyring
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> keyring
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> keyring
anaconda/win-64::spyder==4.1.4=py37_0 -> keyring
Package mako conflicts for:
conda-forge/noarch::optuna==1.0.0=py_0 -> alembic -> mako
conda-forge/noarch::alembic==1.4.0=py_0 -> mako
Package m2w64-gettext conflicts for:
defaults/win-64::m2w64-xz==5.2.2=2 -> m2w64-gettext
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> m2w64-xz -> m2w64-gettext
Package libarchive conflicts for:
intel/win-64::python-libarchive-c==2.8=py37_13 -> libarchive
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libarchive
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libarchive
Package m2w64-xz conflicts for:
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> m2w64-xz
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> m2w64-xz
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> m2w64-xz
Package zict conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> distributed -> zict[version='>=0.1.2|>=0.1.3']
defaults/noarch::dask==2.11.0=py_0 -> distributed[version='>=2.11.0'] -> zict[version='>=0.1.3']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> zict
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> zict
modin==0.7.3 -> distributed[version='>=2.3.2'] -> zict[version='>=0.1.3']
defaults/win-64::distributed==2.11.0=py37_0 -> zict[version='>=0.1.3']
Package win_inet_pton conflicts for:
intel/win-64::urllib3==1.24.1=py37_2 -> pysocks[version='>=1.5.6,<2.0,!=1.5.7'] -> win_inet_pton
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> win_inet_pton
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> win_inet_pton
intel/win-64::pysocks==1.6.7=py37_1 -> win_inet_pton
Package humanfriendly conflicts for:
defaults/win-64::coloredlogs==10.0=py37_0 -> humanfriendly[version='>=4.7']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> coloredlogs -> humanfriendly[version='>=3.2|>=4.7']
Package nose conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> nose
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> nose
Package nltk conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> nltk
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> nltk
Package pyct conflicts for:
conda-forge/noarch::colorcet==2.0.1=py_0 -> pyct[version='>=0.4.4']
conda-forge/noarch::panel==0.9.5=py_1 -> pyct[version='>=0.4.4']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> panel[version='>=0.7.0'] -> pyct[version='>=0.4.4']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> colorcet[version='>=0.9.0'] -> pyct[version='>=0.4.4']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> pyct[version='>=0.4.5']
Package freexl conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> freexl[version='>=1.0.5,<2.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> freexl[version='>=1.0.5,<2.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> freexl[version='>=1.0.5,<2.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libspatialite[version='>=4.3.0a,<4.4.0a0'] -> freexl[version='>=1.0.4,<2.0a0']
conda-forge/label/cf202003/win-64::libspatialite==4.3.0a=h01b1fc4_1030 -> freexl[version='>=1.0.5,<2.0a0']
Package beautifulsoup4 conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> beautifulsoup4
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> beautifulsoup4
conda-forge/noarch::hiplot==0.1.17=py_0 -> beautifulsoup4
Package pcre conflicts for:
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> pcre[version='>=8.43,<9.0a0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> glib[version='>=2.58.3,<3.0a0'] -> pcre[version='>=8.44,<9.0a0']
conda-forge/win-64::gobject-introspection==1.64.1=py37hf0dd101_1 -> glib[version='>=2.58.3,<3.0a0'] -> pcre[version='>=8.44,<9.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> pcre[version='>=8.43,<9.0a0']
conda-forge/win-64::pygobject==3.36.1=py37hf6b2db1_0 -> glib[version='>=2.58.3,<3.0a0'] -> pcre[version='>=8.44,<9.0a0']
conda-forge/win-64::glib==2.64.3=he4de6d7_0 -> pcre[version='>=8.44,<9.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> pcre[version='>=8.43,<9.0a0']
Package click-plugins conflicts for:
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> click-plugins[version='>=1.0']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> click-plugins[version='>=1.0']
Package path conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> path.py -> path[version='<13.2']
defaults/noarch::path.py==12.4.0=0 -> path[version='<13.2']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> path
Package clyent conflicts for:
defaults/win-64::anaconda-client==1.7.2=py37_0 -> clyent[version='>=1.2.2']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> anaconda-client -> clyent[version='>=1.2.0|>=1.2.2']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> clyent
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> clyent
defaults/noarch::anaconda-project==0.8.4=py_0 -> anaconda-client -> clyent[version='>=1.2.0|>=1.2.2']
Package munch conflicts for:
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> munch
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> munch
Package menuinst conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> menuinst
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> menuinst
Package fastcache conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> fastcache
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> fastcache
defaults/win-64::sympy==1.5.1=py37_0 -> fastcache
Package flake8 conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> flake8
anaconda/win-64::python-language-server==0.34.1=py37_0 -> flake8[version='>=3.8.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> flake8[version='>=3.8.0']
Package pywavelets conflicts for:
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> imagehash -> pywavelets
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pywavelets
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-image -> pywavelets[version='>=0.4.0']
conda-forge/noarch::imagehash==4.1.0=pyh9f0ad1d_0 -> pywavelets
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pywavelets
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> pywavelets[version='>=0.4.0']
Package sphinxcontrib-qthelp conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sphinxcontrib-qthelp
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> sphinxcontrib-qthelp
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> sphinxcontrib-qthelp
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> sphinxcontrib-qthelp
Package backports.shutil_get_terminal_size conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backports.shutil_get_terminal_size
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> backports.shutil_get_terminal_size
defaults/noarch::ipywidgets==7.5.1=py_0 -> ipython[version='>=4.0.0'] -> backports.shutil_get_terminal_size
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> ipython[version='>=5.4.0'] -> backports.shutil_get_terminal_size
defaults/win-64::ipykernel==5.1.4=py37h39e3cac_0 -> ipython[version='>=5.0'] -> backports.shutil_get_terminal_size
defaults/win-64::get_terminal_size==1.0.0=h38e98db_0 -> backports.shutil_get_terminal_size
conda-forge/win-64::jupyter_latex_envs==1.4.4=py37_1000 -> ipython -> backports.shutil_get_terminal_size
defaults/noarch::jupyter_console==6.1.0=py_0 -> ipython -> backports.shutil_get_terminal_size
Package libcurl conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libcurl
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> curl[version='>=7.59.0,<8.0a0'] -> libcurl[version='7.59.0|7.59.0|7.60.0|7.60.0|7.61.0|7.61.0|7.61.1|7.61.1|7.61.1|7.62.0|7.62.0|7.63.0|7.63.0|7.63.0|7.63.0|7.64.0|7.64.0|7.64.1|7.64.1|7.65.2|7.65.2|7.65.3|7.65.3|7.67.0|7.68.0|7.69.1|7.71.0|7.71.1|7.68.0',build='h0990ea7_0|hc4dcbb0_0|hc4dcbb0_0|h0990ea7_0|h7a46e7a_0|h7602738_0|h7602738_0|h7a46e7a_0|h2a8f88b_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h7a46e7a_2|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_1|h2a8f88b_2|h7a46e7a_1000|h2a8f88b_1000|h4496350_0']
defaults/win-64::pycurl==7.43.0.5=py37h7a1dbc1_0 -> libcurl[version='>=7.67.0,<8.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> libcurl
conda-forge/label/cf202003/win-64::curl==7.68.0=h4496350_0 -> libcurl==7.68.0=h4496350_0
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> curl -> libcurl[version='7.57.0|7.58.0|7.58.0|7.59.0|7.59.0|7.60.0|7.60.0|7.61.0|7.61.0|7.61.1|7.61.1|7.61.1|7.62.0|7.62.0|7.63.0|7.63.0|7.63.0|7.63.0|7.64.0|7.64.0|7.64.1|7.64.1|7.65.2|7.65.2|7.65.3|7.65.3|7.67.0|7.68.0|7.69.1|7.71.0|7.71.1|7.68.0|>=7.67.0,<8.0a0|>=7.65.3,<8.0a0|>=7.64.1,<8.0a0|>=7.63.0,<8.0a0|>=7.61.0,<8.0a0|>=7.60.0,<8.0a0',build='h7a46e7a_0|h7a46e7a_0|h7602738_0|h0990ea7_0|hc4dcbb0_0|hc4dcbb0_0|h0990ea7_0|h7a46e7a_0|h7602738_0|h7602738_0|h7a46e7a_0|h2a8f88b_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h7a46e7a_2|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_1|h2a8f88b_2|h7a46e7a_1000|h2a8f88b_1000|h4496350_0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> curl[version='>=7.64.1,<8.0a0'] -> libcurl[version='7.64.1|7.64.1|7.65.2|7.65.2|7.65.3|7.65.3|7.67.0|7.68.0|7.69.1|7.71.0|7.71.1|7.68.0',build='h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h7a46e7a_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_0|h2a8f88b_1|h4496350_0']
Package jdcal conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jdcal
defaults/noarch::openpyxl==3.0.3=py_0 -> jdcal
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> jdcal
Package threadpoolctl conflicts for:
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> scikit-learn -> threadpoolctl
anaconda/noarch::pynndescent==0.4.8=py_1 -> scikit-learn[version='>=0.19'] -> threadpoolctl
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> threadpoolctl
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> scikit-learn[version='>=0.23'] -> threadpoolctl
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> scikit-learn[version='>=0.20'] -> threadpoolctl
defaults/win-64::scikit-learn==0.23.1=py37h25d0782_0 -> threadpoolctl
anaconda/win-64::py-xgboost==0.90=py37_1 -> scikit-learn -> threadpoolctl
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-learn -> threadpoolctl
Package openjpeg conflicts for:
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> openjpeg[version='>=2.3.1,<2.4.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> openjpeg[version='>=2.3.1,<2.4.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> openjpeg[version='>=2.3.1,<2.4.0a0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> openjpeg[version='>=2.3.1,<2.4.0a0']
Package pkginfo conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pkginfo
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pkginfo
Package functools32 conflicts for:
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> jsonschema[version='>=3.0.1'] -> functools32
defaults/noarch::seaborn==0.10.0=py_0 -> matplotlib[version='>=2.1.2'] -> functools32
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jsonschema -> functools32
defaults/noarch::nbformat==5.0.4=py_0 -> jsonschema[version='>=2.4,!=2.5.0'] -> functools32
conda-forge/noarch::missingno==0.4.2=py_0 -> matplotlib -> functools32
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> functools32
defaults/win-64::scikit-image==0.16.2=py37h47e9c7a_0 -> matplotlib[version='>=2.0.0'] -> functools32
Package path.py conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> path.py
anaconda/win-64::spyder==4.1.4=py37_0 -> pickleshare[version='>=0.4'] -> path.py
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> path.py
defaults/win-64::ipython==7.12.0=py37h5ca1d4c_0 -> pickleshare -> path.py
Package pycrypto conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pycrypto
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pycrypto
Package glib conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> poppler[version='>=0.67.0,<0.68.0a0'] -> glib[version='>=2.58.3,<3.0a0']
conda-forge/win-64::pygobject==3.36.1=py37hf6b2db1_0 -> glib[version='>=2.58.3,<3.0a0']
conda-forge/win-64::gobject-introspection==1.64.1=py37hf0dd101_1 -> glib[version='>=2.58.3,<3.0a0']
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> glib[version='>=2.58.3,<3.0a0']
Package jupyter conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> jupyter
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyter
Package sphinxcontrib-applehelp conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> sphinxcontrib-applehelp
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> sphinxcontrib-applehelp
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sphinxcontrib-applehelp
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> sphinxcontrib-applehelp
Package curl conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> curl
conda-forge/label/cf202003/win-64::poppler==0.67.0=h1707e21_8 -> curl[version='>=7.64.1,<8.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libnetcdf[version='>=4.6.2,<4.6.3.0a0'] -> curl[version='>=7.59.0,<8.0a0|>=7.64.1,<8.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pycurl -> curl[version='7.55.*|>=7.55.1,<8.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> curl
conda-forge/label/cf202003/win-64::libnetcdf==4.6.2=h396784b_1001 -> curl[version='>=7.59.0,<8.0a0']
Package pyflakes conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyflakes
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pyflakes[version='>=2.2.0,<2.3.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyflakes
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> pyflakes[version='>=2.2.0,<2.3.0']
anaconda/noarch::flake8==3.8.3=py_0 -> pyflakes[version='>=2.2.0,<2.3.0']
Package markdown conflicts for:
conda-forge/noarch::panel==0.9.5=py_1 -> markdown
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> panel[version='>=0.7.0'] -> markdown
Package json5 conflicts for:
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> json5
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> jupyterlab_server[version='>=1.0.0,<2.0.0'] -> json5
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> json5
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyterlab_server -> json5
Package gevent conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> gevent
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> gevent
Package greenlet conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> greenlet
defaults/win-64::gevent==1.4.0=py37he774522_0 -> greenlet[version='>=0.4.14']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> greenlet
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> gevent -> greenlet[version='>=0.4.10|>=0.4.13|>=0.4.14']
Package libgdal conflicts for:
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> gdal -> libgdal[version='2.3.2|2.3.2|2.3.3|3.0.2|>=2.2.2,<2.3.0a0|2.4.2',build='h1155b67_0|h10f50ba_0|heaf30cb_0|hcd84ac5_0|h4f71e3f_8']
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> libgdal[version='>=2.2.2,<2.3.0a0|>=2.3.3,<2.4.0a0|>=3.0.2,<3.1.0a0|>=2.4.2,<2.5.0a0']
Package backports.os conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> backports.os
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> backports.os
Package sortedcollections conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sortedcollections
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sortedcollections
Package partd conflicts for:
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0'] -> partd[version='>=0.3.10|>=0.3.8']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> partd
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask -> partd[version='>=0.3.10|>=0.3.8']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> partd
defaults/noarch::dask==2.11.0=py_0 -> partd[version='>=0.3.10']
modin==0.7.3 -> dask[version='>=2.1.0'] -> partd[version='>=0.3.10']
Package pydocstyle conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> pydocstyle[version='>=2.0.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pydocstyle
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pydocstyle[version='>=2.0.0']
Package pycurl conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pycurl
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pycurl
Package qtconsole conflicts for:
defaults/win-64::jupyter==1.0.0=py37_7 -> qtconsole
anaconda/win-64::spyder==4.1.4=py37_0 -> qtconsole[version='>=4.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> qtconsole[version='>=4.2|>=4.6.0']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> qtconsole[version='>=4.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> qtconsole
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> qtconsole
Package lxml conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> lxml
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> lxml
conda-forge/win-64::jupyter_contrib_nbextensions==0.5.1=py37_0 -> lxml
Package icu conflicts for:
conda-forge/win-64::pycairo==1.19.1=py37h6430cfb_3 -> cairo[version='>=1.16.0,<1.17.0a0'] -> icu[version='>=58.2,<59.0a0']
defaults/win-64::qt==5.9.7=vc14h73c81de_0 -> icu[version='>=58.2,<59.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> icu[version='58.2.*|>=58.2,<59.0a0']
conda-forge/win-64::cairo==1.16.0=h63a05c6_1001 -> icu[version='>=58.2,<59.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> icu[version='58.2.*|>=58.2,<59.0a0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> icu
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> qt -> icu[version='>=58.2,<59.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> icu[version='58.2.*|>=58.2,<59.0a0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> icu
conda-forge/win-64::gobject-introspection==1.64.1=py37hf0dd101_1 -> cairo[version='>=1.16.0,<1.17.0a0'] -> icu[version='>=58.2,<59.0a0']
defaults/win-64::pyqt==5.9.2=py37h6538335_2 -> qt=5.9 -> icu[version='>=58.2,<59.0a0']
Package cairo conflicts for:
conda-forge/win-64::pycairo==1.19.1=py37h6430cfb_3 -> cairo[version='>=1.16.0,<1.17.0a0']
conda-forge/win-64::gobject-introspection==1.64.1=py37hf0dd101_1 -> cairo[version='>=1.16.0,<1.17.0a0']
conda-forge/win-64::pygobject==3.36.1=py37hf6b2db1_0 -> gobject-introspection -> cairo[version='1.14.*|>=1.14.10,<2.0a0|>=1.14.12,<2.0a0|>=1.16.0,<1.17.0a0']
Package pathtools conflicts for:
defaults/win-64::watchdog==0.10.2=py37_0 -> pathtools[version='>=0.1.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pathtools
anaconda/win-64::spyder==4.1.4=py37_0 -> watchdog -> pathtools[version='>=0.1.1']
Package openpyxl conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> openpyxl
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> openpyxl
Package datashape conflicts for:
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> datashape[version='>=0.5.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> datashape
Package python-language-server conflicts for:
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> python-language-server[version='>=0.31.2,<0.32.0|>=0.31.9,<0.32.0|>=0.34.0,<1.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> python-language-server[version='>=0.31.2,<0.32.0|>=0.31.9,<0.32.0|>=0.34.0,<1.0.0']
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> python-language-server
Package pycodestyle conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pycodestyle
anaconda/noarch::flake8==3.8.3=py_0 -> pycodestyle[version='>=2.6.0,<2.7.0']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> autopep8 -> pycodestyle[version='>=2.3|>=2.6']
defaults/noarch::autopep8==1.4.4=py_0 -> pycodestyle[version='>=2.3']
anaconda/win-64::spyder==4.1.4=py37_0 -> python-language-server[version='>=0.34.0,<1.0.0'] -> pycodestyle[version='>=2.6.0,<2.7.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pycodestyle
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pycodestyle[version='>=2.6.0,<2.7.0']
Package qdarkstyle conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> qdarkstyle
anaconda/win-64::spyder==4.1.4=py37_0 -> qdarkstyle[version='>=2.8']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder -> qdarkstyle[version='>=2.7|>=2.8']
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0'] -> qdarkstyle[version='>=2.7|>=2.8']
Package pyct-core conflicts for:
conda-forge/noarch::panel==0.9.5=py_1 -> pyct[version='>=0.4.4'] -> pyct-core=0.4.6
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> pyct[version='>=0.4.5'] -> pyct-core=0.4.6
conda-forge/noarch::pyct==0.4.6=py_0 -> pyct-core=0.4.6
conda-forge/noarch::colorcet==2.0.1=py_0 -> pyct[version='>=0.4.4'] -> pyct-core=0.4.6
Package ipywidgets conflicts for:
conda-forge/noarch::ipympl==0.5.6=pyh9f0ad1d_1 -> ipywidgets[version='>=7.5.0,<8.0']
conda-forge/noarch::pandas-profiling==2.8.0=py_0 -> ipywidgets[version='>=7.5.1']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ipywidgets
defaults/win-64::jupyter==1.0.0=py37_7 -> ipywidgets
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ipywidgets
Package pyperclip conflicts for:
conda-forge/win-64::cmd2==0.9.15=py37_0 -> pyperclip[version='>=1.5.27']
conda-forge/win-64::cliff==2.15.0=py37_0 -> cmd2!=0.8.3 -> pyperclip[version='>=1.5.27']
Package fsspec conflicts for:
modin==0.7.3 -> dask[version='>=2.1.0'] -> fsspec[version='>=0.4.0|>=0.5.1|>=0.6.0']
conda-forge/noarch::datashader==0.11.0=pyh9f0ad1d_0 -> dask[version='>=0.18.0'] -> fsspec[version='>=0.4.0|>=0.5.1|>=0.6.0']
defaults/noarch::dask==2.11.0=py_0 -> fsspec[version='>=0.6.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> dask -> fsspec[version='>=0.4.0|>=0.5.1|>=0.6.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> fsspec
Package mpmath conflicts for:
defaults/win-64::sympy==1.5.1=py37_0 -> mpmath[version='>=0.19']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> mpmath
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> mpmath
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sympy -> mpmath[version='>=0.19']
Package liblief conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> liblief
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> liblief
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> py-lief -> liblief[version='0.10.1|0.9.0|0.9.0|0.9.0',build='ha925a31_2|ha925a31_0|ha925a31_3|ha925a31_0']
defaults/win-64::py-lief==0.9.0=py37ha925a31_3 -> liblief==0.9.0=ha925a31_3
Package pyrsistent conflicts for:
defaults/noarch::nbformat==5.0.4=py_0 -> jsonschema[version='>=2.4,!=2.5.0'] -> pyrsistent[version='>=0.14.0']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pyrsistent
defaults/noarch::jupyterlab_server==1.0.6=py_0 -> jsonschema[version='>=3.0.1'] -> pyrsistent[version='>=0.14.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jsonschema -> pyrsistent[version='>=0.14.0']
defaults/win-64::jsonschema==3.2.0=py37_0 -> pyrsistent[version='>=0.14.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pyrsistent
Package contextlib2 conflicts for:
defaults/win-64::path==13.1.0=py37_0 -> importlib_metadata[version='>=0.5'] -> contextlib2
defaults/win-64::pytest==5.3.5=py37_0 -> importlib_metadata[version='>=0.12'] -> contextlib2
defaults/win-64::inflect==4.1.0=py37_0 -> importlib_metadata -> contextlib2
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> contextlib2
defaults/win-64::pluggy==0.13.1=py37_0 -> importlib_metadata[version='>=0.12'] -> contextlib2
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> contextlib2
defaults/win-64::keyring==21.1.0=py37_0 -> importlib_metadata -> contextlib2
defaults/win-64::jsonschema==3.2.0=py37_0 -> importlib_metadata -> contextlib2
Package cligj conflicts for:
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> cligj[version='>=0.5']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> cligj[version='>=0.5']
Package pytables conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pytables
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pytables
Package mccabe conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> mccabe
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pylint -> mccabe[version='>=0.6,<0.7']
anaconda/win-64::spyder==4.1.4=py37_0 -> pylint[version='>=1.0'] -> mccabe[version='>=0.6,<0.7|>=0.6.0,<0.7.0']
anaconda/win-64::python-language-server==0.34.1=py37_0 -> mccabe[version='>=0.6.0,<0.7.0']
defaults/win-64::pylint==2.4.4=py37_0 -> mccabe[version='>=0.6,<0.7']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pylint -> mccabe[version='>=0.6,<0.7']
anaconda/noarch::flake8==3.8.3=py_0 -> mccabe[version='>=0.6.0,<0.7.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> mccabe
Package pep8 conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pep8
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pep8
Package jmespath conflicts for:
boto3 -> jmespath[version='>=0.7.1,<1.0.0']
anaconda/win-64::s3transfer==0.1.13=py37_0 -> botocore[version='>=1.3.0,<2.0.0'] -> jmespath[version='>=0.7.1,<1.0.0']
defaults/noarch::botocore==1.12.189=py_0 -> jmespath[version='>=0.7.1,<1.0.0']
Package gdal conflicts for:
conda-forge/label/cf202003/noarch::geopandas==0.7.0=py_1 -> fiona -> gdal=2.2
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> gdal
Package powershell_shortcut conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> powershell_shortcut
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> powershell_shortcut
Package libspatialite conflicts for:
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> libspatialite[version='>=4.3.0a,<4.4.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> libspatialite[version='>=4.3.0a,<4.4.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> libspatialite[version='>=4.3.0a,<4.4.0a0']
Package pywin32-ctypes conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> keyring -> pywin32-ctypes[version='!=0.1.0,!=0.1.1']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> keyring -> pywin32-ctypes[version='!=0.1.0,!=0.1.1']
defaults/win-64::keyring==21.1.0=py37_0 -> pywin32-ctypes
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> pywin32-ctypes
Package webencodings conflicts for:
conda-forge/noarch::pbr==5.4.2=py_0 -> pip -> webencodings
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> webencodings
defaults/win-64::nbconvert==5.6.1=py37_0 -> bleach -> webencodings
defaults/win-64::python==3.7.6=h60c2a47_2 -> pip -> webencodings
defaults/win-64::html5lib==1.0.1=py37_0 -> webencodings
defaults/win-64::bleach==3.1.0=py37_0 -> webencodings
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> webencodings
Package sphinxcontrib-serializinghtml conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sphinxcontrib-serializinghtml
defaults/noarch::numpydoc==0.9.2=py_0 -> sphinx -> sphinxcontrib-serializinghtml
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sphinx -> sphinxcontrib-serializinghtml
anaconda/win-64::spyder==4.1.4=py37_0 -> sphinx[version='>=0.6.6'] -> sphinxcontrib-serializinghtml
Package xlwt conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> xlwt
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> xlwt
Package anaconda-client conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> anaconda-client
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> anaconda-client
defaults/noarch::anaconda-project==0.8.4=py_0 -> anaconda-client
Package comtypes conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> comtypes
defaults/win-64::xlwings==0.17.1=py37_0 -> comtypes
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> comtypes
Package m2w64-expat conflicts for:
defaults/win-64::m2w64-xz==5.2.2=2 -> m2w64-gettext -> m2w64-expat
defaults/win-64::m2w64-gettext==0.19.7=2 -> m2w64-expat
Package bitarray conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> bitarray
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> bitarray
Package jaraco.itertools conflicts for:
conda-forge/win-64::importlib-metadata==1.6.1=py37hc8dfbb8_0 -> zipp[version='>=0.5'] -> jaraco.itertools
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> zipp -> jaraco.itertools
defaults/win-64::importlib_metadata==1.5.0=py37_0 -> zipp[version='>=0.5'] -> jaraco.itertools
Package pyviz_comms conflicts for:
conda-forge/noarch::panel==0.9.5=py_1 -> pyviz_comms[version='>=0.7.4']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> pyviz_comms[version='>=0.7.4']
conda-forge/noarch::holoviews==1.13.2=pyh9f0ad1d_0 -> panel[version='>=0.7.0'] -> pyviz_comms[version='>=0.7.2|>=0.7.3']
Package poppler conflicts for:
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> poppler[version='>=0.67.0,<0.68.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> poppler[version='>=0.67.0,<0.68.0a0']
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> poppler[version='>=0.67.0,<0.68.0a0']
Package astroid conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> astroid
anaconda/win-64::python-language-server==0.34.1=py37_0 -> pylint -> astroid[version='>=1.5.1|>=1.6,<2.0|>=2.0.0|>=2.2.0|>=2.3.0,<2.4|>=2.4.0,<2.5|>=2.4.0,<=2.5']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> astroid
defaults/win-64::pylint==2.4.4=py37_0 -> astroid[version='>=2.3.0,<2.4']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> pylint -> astroid[version='>=1.5.1|>=1.6,<2.0|>=2.0.0|>=2.2.0|>=2.3.0,<2.4|>=2.4.0,<2.5|>=2.4.0,<=2.5']
anaconda/win-64::spyder==4.1.4=py37_0 -> pylint[version='>=1.0'] -> astroid[version='>=1.5.1|>=1.6,<2.0|>=2.0.0|>=2.2.0|>=2.3.0,<2.4|>=2.4.0,<2.5|>=2.4.0,<=2.5']
Package h5py conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> h5py
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> h5py
Package daal4py conflicts for:
conda-forge/win-64::tslearn==0.3.1=py37hbc2f12b_0 -> scikit-learn -> daal4py
conda-forge/win-64::umap-learn==0.4.4=py37hc8dfbb8_0 -> scikit-learn[version='>=0.20'] -> daal4py
anaconda/noarch::pynndescent==0.4.8=py_1 -> scikit-learn[version='>=0.19'] -> daal4py
conda-forge/noarch::imbalanced-learn==0.7.0=py_1 -> scikit-learn[version='>=0.23'] -> daal4py
anaconda/win-64::py-xgboost==0.90=py37_1 -> scikit-learn -> daal4py
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> scikit-learn -> daal4py
Package sympy conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> sympy
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> sympy
Package xlrd conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> xlrd
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> xlrd
Package typed-ast conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> typed-ast
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> astroid -> typed-ast[version='>=1.3.0|>=1.4.0,<1.5']
defaults/win-64::pylint==2.4.4=py37_0 -> astroid[version='>=2.3.0,<2.4'] -> typed-ast
Package locket conflicts for:
defaults/noarch::dask==2.11.0=py_0 -> partd[version='>=0.3.10'] -> locket
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defaults/win-64::_anaconda_depends==2019.03=py37_0 -> locket
defaults/noarch::partd==1.1.0=py_0 -> locket
Package py-lief conflicts for:
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defaults/win-64::_anaconda_depends==2019.03=py37_0 -> py-lief
Package xerces-c conflicts for:
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conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> xerces-c[version='>=3.2.2,<3.2.3.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> xerces-c[version='>=3.2.2,<3.2.3.0a0']
Package filelock conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> filelock
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Package bcrypt conflicts for:
anaconda/win-64::spyder==4.1.4=py37_0 -> paramiko[version='>=2.4.0'] -> bcrypt[version='>=3.1.3']
defaults/noarch::paramiko==2.7.1=py_0 -> bcrypt[version='>=3.1.3']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> bcrypt
Package console_shortcut conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> console_shortcut
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> console_shortcut
Package ruamel_yaml conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> anaconda-client -> ruamel_yaml[version='<0.15|>=0.11.14']
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> ruamel_yaml
defaults/noarch::anaconda-project==0.8.4=py_0 -> anaconda-client -> ruamel_yaml[version='<0.15|>=0.11.14']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> ruamel_yaml
defaults/noarch::anaconda-project==0.8.4=py_0 -> ruamel_yaml
Package jupyterlab_server conflicts for:
defaults/noarch::jupyterlab==1.2.6=pyhf63ae98_0 -> jupyterlab_server[version='>=1.0.0,<2.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyterlab -> jupyterlab_server[version='>=0.2.0,<0.3.0|>=1.0.0,<2.0.0|>=1.1.0,<2.0.0']
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> jupyterlab_server
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> jupyterlab_server
Package ffmpeg conflicts for:
conda-forge/noarch::imageio-ffmpeg==0.4.2=py_0 -> ffmpeg
conda-forge/noarch::moviepy==1.0.1=py_0 -> ffmpeg
Package stevedore conflicts for:
conda-forge/win-64::cliff==2.15.0=py37_0 -> stevedore[version='>=1.20.0']
conda-forge/noarch::optuna==1.0.0=py_0 -> cliff -> stevedore[version='>=1.20.0']
Package libllvm9 conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> llvmlite -> libllvm9
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> libllvm9
anaconda/noarch::pynndescent==0.4.8=py_1 -> llvmlite[version='>=0.30'] -> libllvm9
Package m2w64-libiconv conflicts for:
defaults/win-64::m2w64-xz==5.2.2=2 -> m2w64-gettext -> m2w64-libiconv
defaults/win-64::m2w64-gettext==0.19.7=2 -> m2w64-libiconv
Package retrying conflicts for:
plotly/noarch::plotly_express==0.4.1=py_0 -> plotly[version='>=4.1.0'] -> retrying[version='>=1.3.3']
defaults/noarch::plotly==4.8.1=py_0 -> retrying[version='>=1.3.3']
Package cython conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> cython
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> cython
Package spyder conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> spyder
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> spyder
spyder-ide/win-64::spyder-terminal==0.3.1=py37hc8dfbb8_1 -> spyder[version='>=4.0.0,<5.0.0']
Package arrow conflicts for:
conda-forge/noarch::jinja2-time==0.2.0=py_2 -> arrow
conda-forge/win-64::cookiecutter==1.6.0=py37_1000 -> jinja2-time[version='>=0.1.0'] -> arrow
Package kealib conflicts for:
conda-forge/label/cf202003/win-64::fiona==1.8.9.post2=py37h3234bc7_0 -> libgdal[version='>=2.4.2,<2.5.0a0'] -> kealib[version='>=1.4.10,<1.5.0a0']
conda-forge/label/cf202003/win-64::gdal==2.4.2=py37he6b6c38_8 -> libgdal==2.4.2=h4f71e3f_8 -> kealib[version='>=1.4.10,<1.5.0a0']
conda-forge/label/cf202003/win-64::libgdal==2.4.2=h4f71e3f_8 -> kealib[version='>=1.4.10,<1.5.0a0']
Package glob2 conflicts for:
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> glob2
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> glob2
Package xlsxwriter conflicts for:
defaults/win-64::_anaconda_depends==2019.03=py37_0 -> xlsxwriter
defaults/win-64::anaconda==custom=py37_1 -> _anaconda_depends -> xlsxwriterThe following specifications were found to be incompatible with your CUDA driver:
- feature:/win-64::__cuda==10.1=0
- feature:|@/win-64::__cuda==10.1=0
Your installed CUDA driver is: 10.1
```
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MDExOlB1bGxSZXF1ZXN0NDc3Mzg3NzA5
| 36,057
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CLN remove unnecessary trailing commas
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|
CONTRIBUTOR
| null |
#35925
- pandas/tests/arithmetic/test_interval.py
- pandas/tests/arithmetic/test_numeric.py
- pandas/tests/arrays/boolean/test_logical.py
I am not including "pandas/io/sas/sas_xport.py" and "pandas/io/stata.py" as there is a PR already open for those.
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MDExOlB1bGxSZXF1ZXN0NDc3NTA2Njg1
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Comma cleanup for #35925
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| 2020-09-02T01:29:17Z
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|
CONTRIBUTOR
| null |
- [x] pandas/tests/generic/test_finalize.py
- [x] pandas/tests/generic/test_to_xarray.py
- [x] pandas/tests/groupby/aggregate/test_numba.py
- [x] pandas/tests/groupby/test_apply.py
- [x] pandas/tests/groupby/test_categorical.py
- [x] pandas/tests/groupby/test_groupby.py
- [x] pandas/tests/groupby/test_groupby_dropna.py
- [x] pandas/tests/groupby/test_groupby_subclass.py
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MDExOlB1bGxSZXF1ZXN0NDc3NTA5NTA2
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CLN remove unnecessary trailing commas in groupby tests
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| 2
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| 2020-09-02T16:20:00Z
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CONTRIBUTOR
| null |
xref #35925
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MDU6SXNzdWU2OTA2NzY4MjY=
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BUG: MultiIndex with nan values obtained by `groupby` behaves different to MultiIndex.from_tuples()
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| null |
CONTRIBUTOR
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
I checked in 1.1.1
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
In [11]: import pandas as pd
...: import numpy as np
...:
...: df = pd.DataFrame({
...: 'animal': ['Falcon', 'Falcon', 'Parrot', 'Parrot'],
...: 'type': [np.nan, np.nan, np.nan, np.nan],
...: 'speed': [380., 370., 24., 26.]
...: })
...: speed = df.groupby(['animal', 'type'], dropna=False)['speed'].first()
In [12]: speed
Out[12]:
animal type
Falcon NaN 380.0
Parrot NaN 24.0
Name: speed, dtype: float64
In [13]: speed.index.levels
Out[13]: FrozenList([['Falcon', 'Parrot'], [nan]])
In [14]: speed.index.codes
Out[14]: FrozenList([[0, 1], [0, 0]])
In [15]: # Reconstruct same index to allow for multiplication.
...: ix_wing = pd.MultiIndex.from_tuples(
...: [('Falcon', np.nan), ('Parrot', np.nan)], names=['animal', 'type']
...: )
...: wing = pd.Series([42, 44], index=ix_wing)
In [16]: wing
Out[16]:
animal type
Falcon NaN 42
Parrot NaN 44
dtype: int64
In [17]: wing.index.levels
Out[17]: FrozenList([['Falcon', 'Parrot'], []])
In [18]: wing.index.codes
Out[18]: FrozenList([[0, 1], [-1, -1]])
In [19]:
In [19]:
In [19]: speed * wing
Out[19]:
animal type
Falcon NaN NaN
NaN NaN
Parrot NaN NaN
NaN NaN
dtype: float64
```
#### Problem description
I'm trying to perform combine two series (say multiplication for now). One of them is obtained by a groupby aggregation (say `first`) and the other series is constructed manually. Both series have a MultiIndex which _should_ be the same and a multiplication should work fine. However, it seems that `groupby(..., dropna=False)` creates a different MI which causes the operation to return an unexpected result.
#### Expected Output
I would expect the result of `speed * wing` to be
```
Falcon NaN 15960.0
Parrot NaN 1056.0
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.7.17-200.fc32.x86_64
Version : #1 SMP Fri Aug 21 15:23:46 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_AU.UTF-8
LOCALE : en_AU.UTF-8
pandas : 1.1.1
numpy : 1.18.4
pytz : 2019.3
dateutil : 2.8.1
pip : 20.2.1
setuptools : 47.3.1
Cython : 0.29.17
pytest : 5.1.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 0.9.6
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.3 (dt dec pq3 ext lo64)
jinja2 : 2.11.2
IPython : 7.17.0
pandas_datareader: None
bs4 : None
bottleneck : 1.3.1
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : 2.7.1
odfpy : None
openpyxl : 1.8.6
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.12
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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MDExOlB1bGxSZXF1ZXN0NDc3NjE3Nzgz
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BUG: groupby and agg on read-only array gives ValueError: buffer source array is read-only
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| 4
| 2020-09-02T07:00:58Z
| 2020-09-05T08:26:11Z
| 2020-09-04T14:28:16Z
|
CONTRIBUTOR
| null |
- [x] closes #36014
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
I found multiple aggregate functions that were failing for a read-only array. I applied the change suggested in #36014 to all of them.
A couple of questions.
1. I had to add the Py_ssize_t cdefs to suppress the error below for `len(values) != len(labels)`. Let me know if there is another preferred way of doing it.
```
error: comparison of integer expressions of different signedness: ‘Py_ssize_t’ {aka ‘long int’} and ‘size_t’ {aka ‘long unsigned int’} [-Werror=sign-compare]
```
2. I see some functions don't have the `len(values) != len(labels)` check. Should it be there in all the functions?
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MDU6SXNzdWU2OTA3ODQyMzg=
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|
QST: CSV: export, import and new lines
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[] | null | 10
| 2020-09-02T07:18:58Z
| 2020-09-02T17:47:23Z
| 2020-09-02T17:47:23Z
|
NONE
| null |
- [x] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
- [ ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
#### Question about pandas
```python
df = pd.DataFrame([ ['a\rb'] ], columns=['A'])
df.to_csv('df.csv', index=False, sep=';', encoding='utf-8')
df_imported = pd.read_csv('df.csv', sep=';', encoding='utf-8')
(len(df), len(df_imported)) # => (1, 2)
```
On Linux, symbol `\r` is not escaped by `pd.to_csv`. But seems like `pd.read_csv` expects something else.
Is it bug or feature? How to avoid this?
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MDU6SXNzdWU2OTA4MzQ2NDg=
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|
BUG: Unary minus raises for series with Int64Dtype
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| 5
| 2020-09-02T08:41:07Z
| 2020-09-14T04:19:37Z
| 2020-09-13T12:44:16Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas (commit 73c1d32)
---
#### Code Sample, a copy-pastable example
```python
>>> import pandas as pd
>>> pd.__version__
'1.1.1'
>>> s = pd.Series([1, 2, 3], dtype="Int64")
>>> -s
Traceback (most recent call last):
File "...", line 1, in <module>
-s
File ".../lib/python3.8/site-packages/pandas/core/generic.py", line 1297, in __neg__
arr = operator.neg(values)
TypeError: bad operand type for unary -: 'IntegerArray'
```
#### Problem description
I cannot negate series with Int64Dtype. This was possible in previous versions (but it returned object dtype).
#### Expected Output
```
>>> import pandas as pd
>>> pd.__version__
'1.0.5'
>>> s = pd.Series([1, 2, 3], dtype="Int64")
>>> -s
0 -1
1 -2
2 -3
dtype: object
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Thu Jun 18 20:49:00 PDT 2020; root:xnu-6153.141.1~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 47.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.15.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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MDU6SXNzdWU2OTA5NDg4OTg=
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|
BUG: Scatterplot x-axis label disappears with colorscale when using matplotlib backend
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| 10
| 2020-09-02T11:38:50Z
| 2021-10-31T13:03:15Z
| null |
NONE
| null |
- This issue was reported and resolved in #10611 but returned with 0.24.0.
- I have confirmed this bug exists on the latest version of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
# Your code here
import matplotlib.cm as cm
import pandas as pd
import numpy as np
X = np.random.rand(10,3)
df = pd.DataFrame(X,columns=['t','hlReference', 'STEP_STRENGTH'])
df.plot.scatter(
x='t',
y='hlReference',
c='STEP_STRENGTH',
cmap=cm.autumn,)
```
#### Problem description
X-axis label disappears when you add a colorscale to a scatterplot when using matplotlib backend.
**UPDATE confirmed this bug occurs in Jupyter and when files are written out**
Example taken from [this SO question](https://stackoverflow.com/a/52632120/4590385) that also shows the two workarounds.
Workaround 1: Get an ax object and pass `ax=ax`.
Workaround 2: Pass `sharex=False`
A previous solution to the problem is discussed in closed issue #10611, but it appears that stopped working in 0.24.0.
#### Expected Output
Show the x-axis label.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : d9fff2792bf16178d4e450fe7384244e50635733
python : 3.7.6.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
Version : Darwin Kernel Version 18.7.0: Thu Jun 18 20:50:10 PDT 2020; root:xnu-4903.278.43~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.0
numpy : 1.18.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0.post20200814
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : 0.7.4
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : 0.8.7
xarray : None
xlrd : None
xlwt : None
numba : 0.50.0
</details>
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BUG: Index.equals returns incorrect result
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[] | null | 9
| 2020-09-02T12:01:45Z
| 2020-09-03T10:47:02Z
| 2020-09-02T16:10:26Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
# Your code here
import pandas
i1 = pandas.date_range("2008-01-01", periods=1000, freq="12H")
i2 = pandas.date_range("2008-01-01", periods=1000, freq="12H")
i2.freq = None
i1.equals(i2)
True
# but freqs are now equal
i1.freq == i2.freq
False
```
#### Problem description
Could anyone please explain? Is it normal behavior for `equals`?
#### Output of ``pd.show_versions()``
<details>
pandas : 1.1.1
numpy : 1.18.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 41.2.0
Cython : None
pytest : 5.4.2
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.7.3
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : 3.6.1
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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MDU6SXNzdWU2OTA5OTk4MTg=
| 36,066
|
BUG: isin has unexpected behaviour when using a dataframe with a large amount of rows (1.000.001)
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[] | null | 7
| 2020-09-02T12:58:34Z
| 2020-09-11T08:26:42Z
| 2020-09-04T11:04:51Z
|
CONTRIBUTOR
| null |
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
import pandas as pd
import numpy as np
nans = np.repeat(np.nan, 1_000_001)
big = pd.DataFrame({"test":nans})
assert all(big["test"].isin([np.nan])) == True
nans = np.repeat(np.nan, 1_000_000)
small = pd.DataFrame({"test":nans})
assert all(small["test"].isin([np.nan])) == True
assert all(small.dtypes == big.dtypes)
```
#### Problem description
The above code fails on the first assert, but not on the second.
#### Expected Output
The excepted behavior would be that both asserts either fail or succeeds
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.7.7.final.0
python-bits : 64
OS : Darwin
OS-release : 19.3.0
Version : Darwin Kernel Version 19.3.0: Thu Jan 9 20:58:23 PST 2020; root:xnu-6153.81.5~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 19.2.3
setuptools : 41.2.0
Cython : 0.29.17
pytest : 5.4.3
hypothesis : 4.57.1
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.15.1
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.48.0
</details>
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MDExOlB1bGxSZXF1ZXN0NDc3ODExMTEw
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|
TYP: update setup.cfg
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| 1
| 2020-09-02T13:12:50Z
| 2020-09-02T15:47:31Z
| 2020-09-02T15:41:40Z
|
MEMBER
| null |
fixes in #36017 merged between generating config in #36012 and merging #36012
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|
TYP: statically define attributes in plotting._matplotlib.core
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| 1
| 2020-09-02T13:15:11Z
| 2020-09-02T15:49:20Z
| 2020-09-02T15:42:30Z
|
MEMBER
| null |
continuation of changes in #36016
pandas\plotting\_matplotlib\core.py:231: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:232: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:233: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:235: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:385: error: "MPLPlot" has no attribute "label"; maybe "ylabel" or "xlabel"? [attr-defined]
pandas\plotting\_matplotlib\core.py:553: error: "MPLPlot" has no attribute "mark_right" [attr-defined]
pandas\plotting\_matplotlib\core.py:732: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:733: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:735: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:738: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:739: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:741: error: "MPLPlot" has no attribute "style" [attr-defined]
pandas\plotting\_matplotlib\core.py:1008: error: "ScatterPlot" has no attribute "label" [attr-defined]
pandas\plotting\_matplotlib\core.py:1075: error: "LinePlot" has no attribute "stacked" [attr-defined]
pandas\plotting\_matplotlib\core.py:1180: error: "LinePlot" has no attribute "stacked" [attr-defined]
pandas\plotting\_matplotlib\core.py:1269: error: "AreaPlot" has no attribute "stacked" [attr-defined]
pandas\plotting\_matplotlib\core.py:1351: error: "BarPlot" has no attribute "stacked" [attr-defined]
pandas\plotting\_matplotlib\core.py:1427: error: "BarPlot" has no attribute "stacked" [attr-defined]
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|
BUG:read_csv misleading handling of csv files containing rows with different number of delimiters
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[] | null | 1
| 2020-09-02T14:10:54Z
| 2021-08-13T02:14:52Z
| null |
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import pandas as pd
pd.read_csv('fake.csv')
```
fake.csv file
```csv
col1,col2,col3,col4,col5
a,a,a,a,a
a,a,a
```
#### Problem description
Pandas read_csv function should throw an error, or at least a warning, when a csv contains a row with a number of delimiters less than the number of delimiters contained in the header row (the first raw?).
For example, if the number of delimiters is greater an exception is thrown.
#### Expected Output
Error or warning.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-42-generic
Version : #46~18.04.1-Ubuntu SMP Fri Jul 10 07:21:24 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.1.1
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0.post20200814
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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MDU6SXNzdWU2OTEwNjg0MDQ=
| 36,070
|
Pandas fails to build in AIX with Python 3.7
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| 3
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| 2020-09-08T07:13:21Z
| 2020-09-08T07:13:20Z
|
CONTRIBUTOR
| null |
Building Pandas master branch in AIX fails with the below error
ERROR: Command errored out with exit status 1:
command: /opt/freeware/bin/python3 /opt/freeware/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py get_requires_for_build_wheel /tmp/tmp3r6qx0fj
cwd: /tmp/pip-req-build-_gzfu3c7
Complete output (30 lines):
Traceback (most recent call last):
File "/opt/freeware/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py", line 207, in <module>
main()
File "/opt/freeware/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py", line 197, in main
json_out['return_val'] = hook(**hook_input['kwargs'])
File "/opt/freeware/lib/python3.7/site-packages/pip/_vendor/pep517/_in_process.py", line 54, in get_requires_for_build_wheel
return hook(config_settings)
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/build_meta.py", line 150, in get_requires_for_build_wheel
config_settings, requirements=['wheel'])
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/build_meta.py", line 130, in _get_build_requires
self.run_setup()
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/build_meta.py", line 254, in run_setup
self).run_setup(setup_script=setup_script)
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/build_meta.py", line 145, in run_setup
exec(compile(code, __file__, 'exec'), locals())
File "setup.py", line 25, in <module>
cmdclass = versioneer.get_cmdclass()
File "/tmp/pip-req-build-_gzfu3c7/versioneer.py", line 1543, in get_cmdclass
from setuptools.command.sdist import sdist as _sdist
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/command/__init__.py", line 8, in <module>
from distutils.command.bdist import bdist
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/_distutils/command/bdist.py", line 24, in <module>
class bdist(Command):
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/_distutils/command/bdist.py", line 32, in bdist
"(default: %s)" % get_platform()),
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/_distutils/util.py", line 107, in get_platform
return get_host_platform()
File "/tmp/pip-build-env-s1psbl1s/overlay/lib/python3.7/site-packages/setuptools/_distutils/util.py", line 82, in get_host_platform
from _aix_support import aix_platform
ModuleNotFoundError: No module named '_aix_support'
Same issue which affects the scipy build as well --> https://github.com/scipy/scipy/issues/12797
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Backport PR #35852 on branch 1.1.x (API: replace dropna=False option with na_sentinel=None in factorize)
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| 2020-09-02T16:37:26Z
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NONE
| null |
Backport PR #35852: API: replace dropna=False option with na_sentinel=None in factorize
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Backport PR #36051 on branch 1.1.x (BUG: frame._item_cache not cleared when Series is altered)
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NONE
| null |
Backport PR #36051: BUG: frame._item_cache not cleared when Series is altered
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| 691,192,494
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MDExOlB1bGxSZXF1ZXN0NDc3OTY0ODYw
| 36,073
|
CLN clearing unnecessary trailing commas
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| 1
| 2020-09-02T16:51:04Z
| 2020-09-02T19:21:45Z
| 2020-09-02T19:21:30Z
|
CONTRIBUTOR
| null |
This PR is related to issue #35925, black 19.10b0 and upgraded version both passes these changes.
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MDU6SXNzdWU2OTEyMDM3MTE=
| 36,074
|
Pandas MultiIndex causes out of memory error
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| 2020-09-02T17:01:40Z
| 2020-10-12T23:28:34Z
| 2020-10-12T23:28:33Z
|
NONE
| null |
I have used multi indexing in my code which is causing out of memory error.
`import pandas as pd
import numpy as np
import io
import requests
url="https://raw.githubusercontent.com/mahsa-ebrahimian/netflix_project/master/netflix_sample_complete.csv"
movie_db=pd.read_csv(url, error_bad_lines=False)
del movie_db['Unnamed: 0']
iix_n = pd.MultiIndex.from_product([np.unique(movie_db.user_id), np.unique(movie_db.date)])
arr = (movie_db.pivot_table('rating', ['user_id', 'date'], 'item_id', aggfunc='sum').reindex(iix_n,copy=False).to_numpy().reshape(movie_db.user_id.nunique(),movie_db.date.nunique(),-1))`
any performance tip or alternative solution to change my data into desired 3D way would be appreciated.
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MDU6SXNzdWU2OTEyNDExNTE=
| 36,075
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DOC: Docstring for comparison operators has "=!" instead of "!="
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| 2020-09-02T17:24:30Z
| 2021-04-13T15:46:43Z
| null |
CONTRIBUTOR
| null |
#### Location of the documentation
Shows up in all the flexible comparison docstrings like "https://pandas.pydata.org/docs/dev/reference/api/pandas.DataFrame.ne.html". The typo is in the `_flex_comp_doc_FRAME` shared docstring found in `core/ops/docstrings.py`.
#### Documentation problem
The docstring says `=!` instead of `!=` for the not-equals comparison.
#### Suggested fix for documentation
Just need to change it to `!=`.
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MDU6SXNzdWU2OTEyNjMxMzg=
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|
BUG: ser.to_frame().all() inconsistent with ser.all() with CategoryDtype
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| 4
| 2020-09-02T17:42:26Z
| 2020-11-14T19:38:31Z
| 2020-11-14T19:38:31Z
|
MEMBER
| null |
Based on tests.frame.test_analytics.test_any_all_np_func
```
ser = pd.Series([0, 1], dtype="category", name="A")
df = ser.to_frame()
>>> ser.all().
TypeError: Categorical cannot perform the operation all
>>> df.all().item()
False
```
Whats happening here is the DataFrame case is calling `self.values` which casts to int64 (avoidable with 2D EAs...).
If instead we refactor (xref #35881) to operate blockwise, this block is ignored, so we end up getting the result we'd get on an empty DataFrame, i.e. True. (xref #28900 ignoring failures is a footgun).
Expected Behavior: as long as have ignore_failures, `df.all()` should be `True`
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DOC: Fix typo of `=!` to `!=` in docstring
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| 2021-04-07T01:26:05Z
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CONTRIBUTOR
| null |
This fixes GH36075.
- [x] closes #36075
I'm marking the following list items as not-applicable because I'm simply swapping two characters in a docstring that had been in the incorrect order.
- [NA] tests added / passed
- [NA] passes `black pandas`
- [NA] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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MDExOlB1bGxSZXF1ZXN0NDc4MjAxNjg2
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BUG: Unary pos/neg ops on IntegerArrays failing with TypeError
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CONTRIBUTOR
| null |
- [ ] closes #36063
- [ ] tests added / passed
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- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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BUG:
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NONE
| null |
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
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MDExOlB1bGxSZXF1ZXN0NDc4MjM4Mzc5
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BUG: add py39 compat check for ast.slice #32766
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MEMBER
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- [x] closes #32766
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BUG: Unary pos/neg ops on IntegerArrays failing with TypeError
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| 2020-09-05T03:10:54Z
| 2020-09-05T03:10:50Z
|
CONTRIBUTOR
| null |
- [x] pandas/tests/indexes/datetimes/test_datetime.py
- [x] pandas/tests/indexes/datetimes/test_timezones.py
- [x] pandas/tests/indexes/multi/test_constructors.py
- [x] pandas/tests/indexes/multi/test_isin.py
- [x] pandas/tests/indexes/test_base.py
- [x] pandas/tests/indexes/timedeltas/test_scalar_compat.py
- [x] pandas/tests/indexes/timedeltas/test_searchsorted.py
- [x] pandas/tests/indexing/common.py
- [x] pandas/tests/indexing/test_callable.py
- [x] pandas/tests/indexing/test_check_indexer.py
- [x] pandas/tests/indexing/test_coercion.py
- [x] pandas/tests/indexing/test_floats.py
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MDU6SXNzdWU2OTE1ODI4Mjc=
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BUG: Plotting charts in different orders creates different plot outputs
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| 2020-09-03T13:31:55Z
| 2020-09-03T13:31:49Z
|
NONE
| null |
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample
```python
import numpy as np
import pandas as pd
df = pd.DataFrame(
{
"date": [
"2000-01-01",
"2000-01-01",
"2000-01-01",
"2000-01-02",
"2000-01-02",
"2000-01-02",
"2000-01-03",
"2000-01-03",
"2000-01-03",
],
"group": ["A", "B", "C", "A", "B", "C", "A", "B", "C"],
}
)
df["count"] = np.random.randint(0, 5, df.shape[0])
df["date"] = pd.to_datetime(df["date"])
separate_plot = df.groupby(["date", "group"])["count"].sum().unstack().plot()
separate_plot.get_figure().savefig("separate_plot.png")
total_plot = df.groupby("date")["count"].sum().plot()
total_plot.get_figure().savefig("total_plot.png")
```
#### Problem description
Plotting the "separate" plot before the "total" plot results in the following graphs:
*separate_plot.png*:
*total_plot.png*:
As you can see, the lines from the "separate" plot also appear on the "total" plot, despite not grouping by "group" in the "total" plot. In my testing, this only occurs when the "separate" plot is made before the "total" plot.
#### Expected Output
The graphs should look something like the following regardless of which is plotted first:
*separate_plot.png*:
*total_plot.png*:
#### Output of ``pd.show_versions()``
<details>
/usr/lib/python3.8/site-packages/_distutils_hack/__init__.py:30: UserWarning: Setuptools is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.8.5_1
Version : #1 SMP Thu Aug 27 08:23:40 UTC 2020
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.19.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 50.0.0
Cython : None
pytest : 5.4.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : 7.18.1
pandas_datareader: None
bs4 : 4.8.2
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : None
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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MDU6SXNzdWU2OTE2NzQyODE=
| 36,084
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BUG: feather NaN data type issue
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| 2
| 2020-09-03T06:13:56Z
| 2020-09-03T14:19:07Z
| 2020-09-03T14:19:07Z
|
NONE
| null |
# Issue
Feather recasting nan to None instead
#### Code Sample, a copy-pastable example
```python
x = {"a": [np.nan , "xyz"]}
df = pd.DataFrame(x)
df
print(type(df['a'].values[0]))
print(df['a'].values[0])
df.to_feather("example.feather")
df_read = pd.read_feather("example.feather")
df_read
```
```python
x = {"a": [np.nan, "xyz"]}
df = pd.DataFrame(x)
df
print(type(df['a'].values[0]))
print(df['a'].values[0])
df.to_pickle("example.feather")
df_read = pd.read_pickle("example.feather")
df_read
```
#### Problem description
[this should explain **why** the current behaviour is a problem and why the expected output is a better solution]
#### Expected Output
expected to have NaN output
#### Output of ``pd.show_versions()``
<details>
```
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 126 Stepping 5, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 0.25.0
numpy : 1.17.4
pytz : 2019.3
dateutil : 2.8.1
pip : 20.2.2
setuptools : 41.4.0
Cython : 0.29.13
pytest : 5.4.1
hypothesis : 5.8.1
sphinx : 2.2.0
blosc : None
feather : None
xlsxwriter : 1.2.1
lxml.etree : None
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : 4.8.0
bottleneck : 1.2.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : None
matplotlib : 3.3.0
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.5
pandas_gbq : 0.13.2
pyarrow : 0.17.1
pytables : None
s3fs : 0.4.0
scipy : 1.5.2
sqlalchemy : 1.3.9
tables : 3.6.1
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.1
```
</details>
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MDExOlB1bGxSZXF1ZXN0NDc4NDYyNDM5
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CI: MyPy fixup
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| 0
| 2020-09-03T08:39:18Z
| 2020-09-03T10:22:21Z
| 2020-09-03T10:20:52Z
|
MEMBER
| null |
https://github.com/pandas-dev/pandas/runs/1064831108
```
mypy --version
mypy 0.782
Performing static analysis using mypy
pandas/io/common.py:168: error: unused 'type: ignore' comment
pandas/io/common.py:170: error: Incompatible default for argument "encoding" (default has type "None", argument has type "str") [assignment]
pandas/io/common.py:172: error: Incompatible default for argument "mode" (default has type "None", argument has type "str") [assignment]
Found 3 errors in 1 file (checked 1037 source files)
```
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MDExOlB1bGxSZXF1ZXN0NDc4NTYwNDU5
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DOC: minor fixes to whatsnew\v1.1.2.rst
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https://pandas.pydata.org/pandas-docs/dev/whatsnew/v1.1.2.html
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MDExOlB1bGxSZXF1ZXN0NDc4NTY4NzU0
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DOC: Add trailing dot
|
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| 1
| 2020-09-03T11:38:59Z
| 2020-09-03T16:14:18Z
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CONTRIBUTOR
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| 691,911,295
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MDExOlB1bGxSZXF1ZXN0NDc4NTgyNjQw
| 36,088
|
TYP: activate Check for missing error codes
|
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| 1
| 2020-09-03T12:05:01Z
| 2020-09-05T10:10:50Z
| 2020-09-04T20:59:52Z
|
MEMBER
| null |
xref #35311
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| 691,918,821
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MDExOlB1bGxSZXF1ZXN0NDc4NTg4ODAy
| 36,089
|
STY: add code check for use of builtin filter function
|
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| 2
| 2020-09-03T12:15:40Z
| 2020-09-05T07:30:48Z
| 2020-09-05T03:19:00Z
|
MEMBER
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xref https://github.com/pandas-dev/pandas/pull/35717#issuecomment-674051885
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MDExOlB1bGxSZXF1ZXN0NDc4NjAwODgz
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DOC: add mypy version to whatsnew\v1.2.0.rst
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xref https://github.com/pandas-dev/pandas/pull/36012#issuecomment-685188102
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PERF: use from __future__ import annotations more
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| 2020-09-03T16:07:34Z
| 2020-09-03T16:07:34Z
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MEMBER
| null |
xref https://github.com/pandas-dev/pandas/pull/36034#issuecomment-684964511
@WillAyd using `python -X importtime -c "import pandas"` I don't see any different in import time after running a few times and things are cached.
so I don't think we gain anything from a performance POV and therefore only need to use it for stylistic reasons in a few modules and not across the codebase.
I've opened this PR, in case someone wants to test performance with these changes.
so feel free to close
|
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MEMBER
| null |
xref #39513
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MEMBER
| null |
- [x] closes #34789
- [x] tests added / passed
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
We also avoid copies by not calling `self.as_array` and instead moving the mask-finding to the block level.
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| 5
| 2020-09-03T16:14:40Z
| 2020-09-06T17:49:33Z
| 2020-09-06T17:49:28Z
|
CONTRIBUTOR
| null |
- [x] closes #24980
- [x] tests added / passed
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This PR is mainly from #29670 contributed by @charlesdong1991, and I made a few changes on his work.
The code have passed all tests modified and added in `test_format.py` and `test_to_latex.py`.
Any comment is welcomed!
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Backport PR #36086 on branch 1.1.x (DOC: minor fixes to whatsnew\v1.1.2.rst)
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Backport PR #36086: DOC: minor fixes to whatsnew\v1.1.2.rst
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ENH: Improve `OverflowError` message when `pandas.read_stata` fails to convert dates
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CONTRIBUTOR
| null |
#### Is your feature request related to a problem?
Calling `pd.read_stata` on a DTA file with a bad date format code leads to a minimally useful error message. The error is [raised from this line](https://github.com/pandas-dev/pandas/blob/309018c7ce7e9e31708f58af971ed92823921493/pandas/io/stata.py#L294).
What I see:
```python
>>> import pandas as pd
>>> pd.read_stata("date_overflow.DTA")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/miker985/lib-code/pandas/pandas/io/stata.py", line 1933, in read_stata
data = reader.read()
File "/home/miker985/lib-code/pandas/pandas/io/stata.py", line 1682, in read
data[col], self.fmtlist[i]
File "/home/miker985/lib-code/pandas/pandas/io/stata.py", line 333, in _stata_elapsed_date_to_datetime_vec
conv_dates = convert_delta_safe(base, days, "d")
File "/home/miker985/lib-code/pandas/pandas/io/stata.py", line 294, in convert_delta_safe
values = [base + relativedelta(days=int(d)) for d in deltas]
File "/home/miker985/lib-code/pandas/pandas/io/stata.py", line 294, in <listcomp>
values = [base + relativedelta(days=int(d)) for d in deltas]
File "/home/miker985/.virtualenvs/tmp-3c950d2b6b7b8c2/lib/python3.7/site-packages/dateutil/relativedelta.py", line 405, in __radd__
return self.__add__(other)
File "/home/miker985/.virtualenvs/tmp-3c950d2b6b7b8c2/lib/python3.7/site-packages/dateutil/relativedelta.py", line 392, in __add__
microseconds=self.microseconds))
OverflowError: date value out of range
```
#### Describe the solution you'd like
I'd like a clearer message indicating the problem column. It would be easy to catch the `OverflowError` [in the loop doing the date conversion](https://github.com/pandas-dev/pandas/blob/309018c7ce7e9e31708f58af971ed92823921493/pandas/io/stata.py#L1678-L1686) and include the column name.
Desired detailed error: `OverflowError: Failed converting column tiempo_gen for format %dD_m_Y: date value out of range`
Alternative error: `OverflowError: date value out of range for column tiempo_gen`
[date_overflow.DTA.gz](https://github.com/pandas-dev/pandas/files/5169943/date_overflow.DTA.gz)
**I would be happy to submit a patch for this if the solution is approved**.
#### API breaking implications
I don't believe this would break or alter any APIs
#### Describe alternatives you've considered
* Add a flag `skip_invalid_dates` which changes behavior to skip converting dates IFF they would error. Instead of raising an exception it would be caught and a warning emitted along the lines of `"date value out of range for column tiempo_gen - skipping date conversion"`. This would allow users access to as much converted data as possible. This flag would default to `False` and be backwards compatible with the APIs.
* I would be happy to submit a patch for this if approved
* Refactor the `pandas.io.stata` API to allow for manual date conversion without using private functions.
#### Additional context
Output of `pd.show_versions()`
<details>
/home/miker985/.virtualenvs/tmp-3c950d2b6b7b8c2/lib/python3.7/site-packages/setuptools/distutils_patch.py:26: UserWarning: Distutils was imported before Setuptools. This usage is discouraged and may exhibit undesirable behaviors or errors. Please use Setuptools' objects directly or at least import Setuptools first.
"Distutils was imported before Setuptools. This usage is discouraged "
INSTALLED VERSIONS
------------------
commit : 76f74d53bf3682c84ad8e2e64c41dfdfae9975cc
python : 3.7.8.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-112-generic
Version : #113-Ubuntu SMP Thu Jul 9 23:41:39 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.0.dev0+230.g76f74d53b.dirty
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
This was the test I put together to hammer out all the details so I knew what was happening with the file
tl;dr
* The column contains values in the millions
* The date units are days, meaning the dates occur after the year 56,000
```python
import pandas as pd
def test_loading_bad_format():
"""
Demonstrate OverflowError is raised with pd.read_stata
"""
dta = "date_overflow.DTA"
try:
pd.read_stata(dta)
except OverflowError as e:
assert len(e.args) == 1
# this message is minimally useful.
# it should include at minimum the column causing the error
assert e.args[0] == "date value out of range"
# demonstrate cause
reader = pd.io.stata.StataReader(dta, convert_dates=False)
# date conversion is the cause here
df = reader.read()
# for one column
assert len(df.columns) == 1 and 'tiempo_gen' in df
min_val = df['tiempo_gen'].min()
# with very large values ...
assert min_val > 20_588_866
assert min_val < 20_588_867
# ... and a format indicating the units are days
# (20.5 million days is ~56,000 years)
assert len(reader.fmtlist) == 1 and reader.fmtlist[0] == '%dD_m_Y'
```
Example file - a subset of a real life file I ran into this issue with: [date_overflow.DTA.gz](https://github.com/pandas-dev/pandas/files/5170101/date_overflow.DTA.gz)
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NONE
| null |
- [x] closes #20012
- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Added center functionality for `VariableWindowIndexer`. Note - I am unsure if the NotImplementedError in lines 1966-1969 in rolling.py still correctly raises an error for offset based windows.
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| 2020-09-05T07:31:32Z
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|
MEMBER
| null |
```
pandas/core/dtypes/cast.py:1491: error: Incompatible return value type (got "Type[object]", expected "Union[dtype, ExtensionDtype]") [return-value]
pandas/core/dtypes/cast.py:1553: error: Incompatible types in assignment (expression has type "Type[object]", variable has type "Union[dtype, ExtensionDtype]") [assignment]
pandas/core/construction.py:601: error: Incompatible default for argument "dtype_if_empty" (default has type "Type[object]", argument has type "Union[ExtensionDtype, str, dtype, Type[str], Type[float], Type[int], Type[complex], Type[bool]]") [assignment]
pandas/core/generic.py:6217: error: Argument "dtype_if_empty" to "create_series_with_explicit_dtype" has incompatible type "Type[object]"; expected "Union[ExtensionDtype, str, dtype, Type[str], Type[float], Type[int], Type[complex], Type[bool]]" [arg-type]
pandas/tests/arrays/sparse/test_dtype.py:97: error: Argument 1 to "SparseDtype" has incompatible type "Type[object]"; expected "Union[ExtensionDtype, str, dtype, Type[str], Type[float], Type[int], Type[complex], Type[bool]]" [arg-type]
pandas/tests/arrays/sparse/test_dtype.py:172: error: Argument 1 to "SparseDtype" has incompatible type "Type[object]"; expected "Union[ExtensionDtype, str, dtype, Type[str], Type[float], Type[int], Type[complex], Type[bool]]" [arg-type]
pandas/tests/arrays/sparse/test_combine_concat.py:44: error: Argument 1 to "SparseDtype" has incompatible type "Type[object]"; expected "Union[ExtensionDtype, str, dtype, Type[str], Type[float], Type[int], Type[complex], Type[bool]]" [arg-type]
pandas/tests/arrays/sparse/test_array.py:561: error: Argument 1 to "SparseDtype" has incompatible type "Type[object]"; expected "Union[ExtensionDtype, str, dtype, Type[str], Type[float], Type[int], Type[complex], Type[bool]]" [arg-type]
```
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TYP: misc fixes for numpy types 2
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| 1
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| 2020-09-04T17:05:36Z
| 2020-09-04T17:03:46Z
|
MEMBER
| null |
```
pandas\core\dtypes\cast.py:681: error: Incompatible types in assignment (expression has type "DatetimeTZDtype", variable has type "dtype") [assignment]
pandas\core\dtypes\cast.py:715: error: Incompatible types in assignment (expression has type "IntervalDtype", variable has type "dtype") [assignment]
pandas\core\dtypes\common.py:1392: error: Item "dtype" of "Union[dtype, ExtensionDtype]" has no attribute "_is_boolean" [union-attr]
pandas\core\dtypes\common.py:111: error: Function "numpy.array" is not valid as a type [valid-type]
pandas\core\reshape\merge.py:1873: error: Function "numpy.array" is not valid as a type [valid-type]
```
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| 2
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| 2020-09-13T19:18:46Z
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|
MEMBER
| null |
```
pandas\core\reshape\merge.py:1931: error: Incompatible types in assignment (expression has type "ndarray", variable has type "ExtensionArray") [assignment]
pandas\core\reshape\merge.py:1932: error: Incompatible types in assignment (expression has type "ndarray", variable has type "ExtensionArray") [assignment]
pandas\core\reshape\merge.py:1941: error: Incompatible types in assignment (expression has type "ndarray", variable has type "ExtensionArray") [assignment]
pandas\core\reshape\merge.py:1950: error: Incompatible types in assignment (expression has type "ndarray", variable has type "ExtensionArray") [assignment]
pandas\core\reshape\merge.py:1951: error: Incompatible types in assignment (expression has type "ndarray", variable has type "ExtensionArray") [assignment]
pandas\io\pytables.py:5084: error: Incompatible types in assignment (expression has type "ndarray", variable has type "ExtensionArray") [assignment]
```
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| 692,276,152
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MDExOlB1bGxSZXF1ZXN0NDc4ODg4MjEz
| 36,101
|
CLN removing trailing commas
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| 4
| 2020-09-03T19:56:42Z
| 2020-09-05T12:39:23Z
| 2020-09-05T12:39:12Z
|
CONTRIBUTOR
| null |
This PR is related to #35925, both current and new versions of black passes these formatting,
also I'd like to mention that there seem to be a reported [bug](https://github.com/psf/black/issues/1629) in newer version of black which throws error after removing trailing comma from `pandas/tests/scalar/timestamp/test_constructors.py` that's why I didn't change this formatting.
```diff
diff --git a/pandas/tests/scalar/timestamp/test_constructors.py b/pandas/tests/scalar/timestamp/test_constructors.py
index 316a299ba..c70eacdfa 100644
--- a/pandas/tests/scalar/timestamp/test_constructors.py
+++ b/pandas/tests/scalar/timestamp/test_constructors.py
@@ -267,7 +267,7 @@ class TestTimestampConstructors:
hour=1,
minute=2,
second=3,
- microsecond=999999,
+ microsecond=999999
)
) == repr(Timestamp("2015-11-12 01:02:03.999999"))
~
```
The workaround to this is after removing trailing comma from above code run black with --fast which will add trailing comma back again and and will not format afterwards on re-running black without --fast
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| 0
| 2020-09-03T20:03:57Z
| 2020-09-13T19:15:53Z
| 2020-09-13T19:15:53Z
|
MEMBER
| null |
```
pandas\plotting\_matplotlib\tools.py:356: error: Incompatible return value type (got "ndarray", expected "Sequence[Any]") [return-value]
pandas\plotting\_matplotlib\tools.py:358: error: Incompatible return value type (got "Union[ndarray, Any]", expected "Sequence[Any]") [return-value]
pandas\plotting\_matplotlib\tools.py:359: error: Incompatible return value type (got "ndarray", expected "Sequence[Any]") [return-value]
pandas\core\dtypes\cast.py:1079: error: No overload variant of "to_datetime" matches argument types "ndarray", "str" [call-overload]
pandas\core\arrays\categorical.py:1818: error: Signature of "_ndarray" incompatible with supertype "NDArrayBackedExtensionArray" [override]
pandas/core/arrays/datetimelike.py:465: error: Signature of "_ndarray" incompatible with supertype "NDArrayBackedExtensionArray" [override]
```
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MDU6SXNzdWU2OTIzMjYxMTE=
| 36,103
|
QST: Why does Pandas change data type from object to float after reading 32768 rows from CSV file?
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[] | null | 11
| 2020-09-03T20:36:50Z
| 2020-09-09T20:40:24Z
| 2020-09-09T20:40:24Z
|
NONE
| null |
- [x] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
- [x] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
#### Question about pandas
Using Pandas 1.0.3.
I have a CSV with 43,00 rows. I noticed that one of the columns is object type even though it has floats. It looks like this happened because a few records contain a string that reads 'Bad Input'. However, after 32768 rows, the data becomes floats. I found it strange that this happens after exactly 32K rows.
I've used Pandas for a few years now, but I've never seen an inconsistency like this.
Is this a bug? How do I work around this?
**Note**: If you'd still like to submit a question, please read [this guide](
https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your question.
```python
# Your code here, if applicable
```
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STY: De-privatize functions in io.excel imported elsewhere
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| 0
| 2020-09-04T01:09:10Z
| 2020-09-04T20:56:48Z
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|
MEMBER
| null |
xref #36055
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DEPR: making copies when indexing along columns
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| 2020-09-04T01:37:00Z
| 2021-11-20T23:22:45Z
| 2020-09-05T19:01:35Z
|
MEMBER
| null |
- [x] closes #33780
- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
xref #33597 for what this might look like once the deprecation is enforced (nice perf bump)
cc @jorisvandenbossche my understanding is that we will need this deprecation for the all-1D world too. Is that correct? Any thoughts on nice ways to test this and avoid putting tm.assert_produces_warning in a zillion places across the code?
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| 1
| 2020-09-04T02:55:33Z
| 2020-09-11T01:20:21Z
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MEMBER
| null |
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CLN: clean `pandas/compat.__init__.py`
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MEMBER
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Remove `is_platform_32bit()` from `pandas/compat.__init__.py`, use `IS64` instead to improve consistency.
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CLN: use IS64 instead of is_platform_32bit #36108
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MEMBER
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- [x] closes #36108
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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QST:how can i cut down time when using pandas.style.to_excel()?
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| 2020-09-04T08:15:21Z
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|
NONE
| null |
#### Question about pandas
I tested the function **to_excel()** from the following code using xlsx file which size is **50**M.
the result is **df_style_red_mark** spend 350s ,but **df** spend 60s. And i want to know why it is?
how can i cut down time when using **df_style_red_mark**?
```python
df_style_red_mark = df.style.apply(...)
```
```python
df_style_red_mark.to_excel(...)
df.to_excel(...)
```
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BUG: read_csv with custom date parser and na_filter=True results in ValueError
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| 3
| 2020-09-04T08:46:14Z
| 2021-02-02T00:27:39Z
| 2021-02-02T00:27:39Z
|
NONE
| null |
```python
import numpy as np
import pandas as pd
from io import StringIO
def __custom_date_parser(time):
time_temp = time.astype(np.float).astype(np.int) # convert float seconds to int type
return pd.to_timedelta(time_temp, unit='s')
testdata = StringIO("""time e n h
41047.00 -98573.7297 871458.0640 389.0089
41048.00 -98573.7299 871458.0640 389.0089
41049.00 -98573.7300 871458.0642 389.0088
41050.00 -98573.7299 871458.0643 389.0088
41051.00 -98573.7302 871458.0640 389.0086
""")
df = pd.read_csv(testdata, delim_whitespace=True, parse_dates=True, date_parser=__custom_date_parser, index_col='time')
```
I noticed this problem when I executed a piece of old code which has worked before (a few months ago). Normally this code would parse a text file with GPS seconds of week as time and convert it to a TimeDeltaIndex. Now when I execute this, it results in a **ValueError: unit abbreviation w/o a number**. (Full stack trace below) I tracked it down to the default option **na_filter=True** in pd.read_csv. When i set it to False everything is working. With a bit of digging I think i found the source of the error in algorithms.py -> _ensure_data -> line 142.
```python
# datetimelike
vals_dtype = getattr(values, "dtype", None)
if needs_i8_conversion(vals_dtype) or needs_i8_conversion(dtype):
if is_period_dtype(vals_dtype) or is_period_dtype(dtype):
from pandas import PeriodIndex
values = PeriodIndex(values)
dtype = values.dtype
elif is_timedelta64_dtype(vals_dtype) or is_timedelta64_dtype(dtype):
from pandas import TimedeltaIndex
values = TimedeltaIndex(values) #This is line 142
dtype = values.dtype
else:
# Datetime
if values.ndim > 1 and is_datetime64_ns_dtype(vals_dtype):
# Avoid calling the DatetimeIndex constructor as it is 1D only
# Note: this is reached by DataFrame.rank calls GH#27027
# TODO(EA2D): special case not needed with 2D EAs
asi8 = values.view("i8")
dtype = values.dtype
return asi8, dtype
from pandas import DatetimeIndex
values = DatetimeIndex(values)
dtype = values.dtype
```
Here the function tries to parse **values** as TimeDeltaIndex, but values is ['' 'n/a' '-nan' '#N/A' '1.#QNAN' 'nan' '#NA' 'NaN' '-1.#QNAN' '#N/A N/A', '-NaN' 'N/A' 'NULL' '<NA>' 'null' '1.#IND' 'NA' '-1.#IND'] in this case. It executes this if statement, because **is_timedelta64_dtype(dtype)** is true in this case. I can't believe that this is expected behaviour, as it has worked before.
``` python-traceback
Traceback (most recent call last):
File "...\lib\site-packages\pandas\io\parsers.py", line 458, in _read
data = parser.read(nrows)
File "...\lib\site-packages\pandas\io\parsers.py", line 1186, in read
ret = self._engine.read(nrows)
File "...\lib\site-packages\pandas\io\parsers.py", line 2221, in read
index, names = self._make_index(data, alldata, names)
File "...\lib\site-packages\pandas\io\parsers.py", line 1667, in _make_index
index = self._agg_index(index)
File "...\lib\site-packages\pandas\io\parsers.py", line 1760, in _agg_index
arr, _ = self._infer_types(arr, col_na_values | col_na_fvalues)
File "...\lib\site-packages\pandas\io\parsers.py", line 1861, in _infer_types
mask = algorithms.isin(values, list(na_values))
File "...\lib\site-packages\pandas\core\algorithms.py", line 433, in isin
values, _ = _ensure_data(values, dtype=dtype)
File "...\lib\site-packages\pandas\core\algorithms.py", line 142, in _ensure_data
values = TimedeltaIndex(values)
File "...\lib\site-packages\pandas\core\indexes\timedeltas.py", line 157, in __new__
data, freq=freq, unit=unit, dtype=dtype, copy=copy
File "...\lib\site-packages\pandas\core\arrays\timedeltas.py", line 216, in _from_sequence
data, inferred_freq = sequence_to_td64ns(data, copy=copy, unit=unit)
File "...\lib\site-packages\pandas\core\arrays\timedeltas.py", line 930, in sequence_to_td64ns
data = objects_to_td64ns(data, unit=unit, errors=errors)
File "...\lib\site-packages\pandas\core\arrays\timedeltas.py", line 1040, in objects_to_td64ns
result = array_to_timedelta64(values, unit=unit, errors=errors)
File "pandas\_libs\tslibs\timedeltas.pyx", line 273, in pandas._libs.tslibs.timedeltas.array_to_timedelta64
File "pandas\_libs\tslibs\timedeltas.pyx", line 268, in pandas._libs.tslibs.timedeltas.array_to_timedelta64
File "pandas\_libs\tslibs\timedeltas.pyx", line 215, in pandas._libs.tslibs.timedeltas.convert_to_timedelta64
File "pandas\_libs\tslibs\timedeltas.pyx", line 428, in pandas._libs.tslibs.timedeltas.parse_timedelta_string
ValueError: unit abbreviation w/o a number
python-BaseException
```
<details>
INSTALLED VERSIONS
------------------
commit : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python : 3.7.9.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.1.1
numpy : 1.18.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0.post20200814
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.1.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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| 692,959,310
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MDExOlB1bGxSZXF1ZXN0NDc5NTAwMjIy
| 36,112
|
DOC: sync doc/source/whatsnew/v1.1.2.rst on 1.1.x
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| 1
| 2020-09-04T09:28:13Z
| 2020-09-04T11:44:29Z
| 2020-09-04T11:44:22Z
|
MEMBER
| null |
~~don't merge this yet. I'll make sure a test is failing first~~
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BUG: pandas.DataFrame().stack() raise an error, while expected is empty
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| 5
| 2020-09-04T11:06:46Z
| 2020-11-26T15:54:44Z
| 2020-11-26T15:54:44Z
|
NONE
| null |
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
pandas.DataFrame().stack()
pandas.DataFrame().stack(dropna = True)
```
#### Problem description
I expect that stack() of empty dataframe will be empty dataframe and not an exception
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REGR: fix consolidation/cache issue with take operation
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| 2020-09-05T06:04:33Z
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MEMBER
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Closes #35521
@jbrockmendel the "short term" fix for 1.1.2
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REGR: append tz-aware DataFrame with tz-naive values
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| 2021-01-28T22:36:17Z
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|
MEMBER
| null |
Closes #35460
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ENH: Standarization changing copy parameter to inplace
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| 1
| 2020-09-04T14:11:00Z
| 2020-09-04T16:54:48Z
| 2020-09-04T16:14:03Z
|
NONE
| null |
#### Is your feature request related to a problem?
No, it's not a problem
#### Describe the solution you'd like
Some functions like [astype](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.astype.html) (I don't know if there is another one) has the `copy` parameter, which has exactly the same functionality that `inplace` in the vast majority of the other methods.
Sometimes, even PyCharm is unable to infer the type of some objects, so I think that It'd be great to have only one way to make things, renaming `copy` to `inplace` and changing its default value to `False`.
This will make Pandas an even more easy-to-use tool and will simplify the documentation and general structure.
#### API breaking implications
The `copy` parameter will be changed to `inplace`. In the general cases where default values are used it don't represent a problem. In other cases an `AttributeError` will be reaised
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