Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Column() changed from object to string in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
df = pandas_read_json(f)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/frame.py", line 778, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 680, in _extract_index
raise ValueError(
ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 177, in _generate_tables
raise e
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Building Energy Benchmarking Dataset
⚠️ Synthetic Data Disclaimer: This dataset contains synthetically generated data for demonstration and testing purposes. It does not represent real buildings or actual energy performance data.
Overview
Portfolio-level building energy benchmarking data with energy intensity metrics, CO2 emissions, and sustainability ratings. Useful for comparing building performance across different types and locations.
Schema
{
"pipeline": "sustainable_building_benchmarking",
"generated_at": "ISO 8601 timestamp",
"portfolio_summary": {
"total_buildings": 12,
"total_floor_area_m2": 45680,
"avg_energy_intensity_kwh_m2": 98.4,
"portfolio_co2_tons": 892.5,
"top_performer_pct": 25,
"needs_improvement_pct": 33
},
"benchmark_categories": {
"energy_intensity": {
"excellent": "< 70 kWh/m²",
"good": "70-90 kWh/m²",
"average": "90-110 kWh/m²",
"poor": "> 110 kWh/m²"
}
},
"buildings": [
{
"building_id": "BLD-001",
"name": "Main Office Tower",
"location": "Stockholm",
"floor_area_m2": 5200,
"building_type": "Office | Laboratory | Retail | Hotel | Residential",
"year_built": 2018,
"energy_intensity_kwh_m2": 72.5,
"co2_intensity_kg_m2": 16.2,
"energy_percentile": 15,
"rating": "Excellent | Good | Average | Poor",
"certifications": ["LEED Gold", "BREEAM Excellent"]
}
]
}
Rating Categories
| Rating | Energy Intensity | Description |
|---|---|---|
| Excellent | < 70 kWh/m² | Top 25% performers |
| Good | 70-90 kWh/m² | Above average |
| Average | 90-110 kWh/m² | Typical performance |
| Poor | > 110 kWh/m² | Needs improvement |
Certifications
- LEED (Leadership in Energy and Environmental Design)
- BREEAM (Building Research Establishment Environmental Assessment Method)
- Energy Star
- Green Building Council certifications
Use Cases
- Portfolio energy management dashboards
- Building performance comparisons
- Sustainability reporting
- Energy efficiency prioritization
Update Schedule
This dataset is automatically updated daily at 00:00 UTC via GitHub Actions.
Source
Generated by the Sustainable-Building-Energy-Benchmarking-Pipeline project.
License
MIT License
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