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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- en |
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tags: |
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- wellbeing |
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- flourishing |
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- llm |
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- classification |
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--- |
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### About the data |
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These are partial results from [The Geography of Human Flourishing Project](https://i-guide.io/spatial-ai-challenge-2024/accepted-abstracts/) analysis for the years 2010-2023. |
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This project is one of the 10 national projects awarded within the [Spatial AI-Challange 2024](https://i-guide.io/spatial-ai-challenge-2024/), |
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an international initiative at the crossroads of geospatial science and artificial intelligence. |
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At present only a subset of data for 2010-2012 are present. |
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Data are in the form of CSV or parquet. |
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In the datasets, FIPS is the FIPS code for a US state, county is the US county id, according to US Bureau of Census. |
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This data contain 46 Human Flourishing dimensions plus migration mood and corruption perception. |
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A reference paper will be uploaded. |
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## How to get the data with python |
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``` |
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from datasets import load_dataset |
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# Load the CSV |
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df_csv = load_dataset("siacus/flourishing", data_files="flourishingStateYear.csv").to_pandas() |
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# Load the Parquet |
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df_parquet = load_dataset("siacus/flourishing", data_files="flourishingStateYear.parquet").to_pandas() |
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``` |
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## How to get the data with R |
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There is no direct equivalent to ```datasets::load_dataset()``` from Hugging Face yet, so you can try this: |
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``` |
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# Load the CSV |
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library(data.table) |
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df_csv <- fread("https://huggingface.co/datasets/siacus/flourishing/resolve/main/flourishingStateYear.csv") |
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# Load the Parquet |
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library(arrow) |
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df_parquet <- read_parquet("https://huggingface.co/datasets/siacus/flourishing/resolve/main/flourishingStateYear.parquet") |
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``` |
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This dataset contains also two shape files archives |
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```cb_2021_us_county_20m.zip``` taken from [here](https://www2.census.gov/geo/tiger/GENZ2021/shp/cb_2021_us_county_20m.zip) and |
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```cb_2021_us_state_20m.zip``` taken from [here](https://www2.census.gov/geo/tiger/GENZ2021/shp/cb_2021_us_state_20m.zip) which can be useful to visualize the maps in python. |
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Unfortunately US Census Bureau web site is stopping download from bots/scripts, so we provide the files here. |
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To get them from python use this code |
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``` |
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import geopandas as gpd |
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states = gpd.read_file("https://huggingface.co/datasets/siacus/flourishing/resolve/main/cb_2021_us_state_20m.zip") |
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counties = gpd.read_file("https://huggingface.co/datasets/siacus/flourishing/resolve/main/cb_2021_us_county_20m.zip") |
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``` |
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