diff --git a/INSTALLATION-es.md b/INSTALLATION-es.md index 39796e06..46e0aa64 100644 --- a/INSTALLATION-es.md +++ b/INSTALLATION-es.md @@ -55,6 +55,6 @@ Si bien se puede usar cualquier IDE, describimos cómo configurar VS Code Para el desarrollo de front-end, lea el [Client README](client/README.md). -Para el desorrollo de back-end, lea el [Score README](score/README.md). +Para el desorrollo de back-end, lea el [Data Pipeline README](data/data-pipeline/README.md). Para la implementación de software, lea el [Infrastructure README](infrastructure/README.md). \ No newline at end of file diff --git a/INSTALLATION.md b/INSTALLATION.md index 850d69db..9b19fea5 100644 --- a/INSTALLATION.md +++ b/INSTALLATION.md @@ -78,7 +78,7 @@ There is also a docker-compose file that will eventually include everything you If you wish to check out our client-side code (i.e. the GatsbyJS statically generated website with the map), check out the `client` directory and its [README](client/README.md). **Running the backend** -If you want to run the data pipeline with ETL and score generation, check out the `score` directory and its [README](score/README.md). +If you want to run the data pipeline with ETL and score generation, check out the `data/data-pipeline` directory and its [README](data/data-pipeline/README.md). **Deployment** For core team contributors working on deployment, check out the `infrastructure` directory and its [README](infrastructure/README.md) for information on deploying the backend to AWS. diff --git a/data/data-pipeline/README.md b/data/data-pipeline/README.md index 6f1e1fb8..e55fa2c8 100644 --- a/data/data-pipeline/README.md +++ b/data/data-pipeline/README.md @@ -34,7 +34,7 @@ This application is used to compare experimental versions of the Justice40 score _**NOTE:** These scores **do not** represent final versions of the Justice40 scores and are merely used for comparative purposes. As a result, the specific input columns and formulas used to calculate them are likely to change over time._ -### Score comparison workflow +### Score generation and comparison workflow The descriptions below provide a more detailed outline of what happens at each step of ETL and score calculation workflow. @@ -58,8 +58,8 @@ TODO add mermaid diagram 1. The `etl-run` command will execute the corresponding ETL script for each data source in `etl/sources/`. For example, `etl/sources/ejscreen/etl.py` is the ETL script for EJSCREEN data. 1. Each ETL script will extract the data from its original source, then format the data into `.csv` files that get stored in the relevant folder in `data/dataset/`. For example, HUD Housing data is stored in `data/dataset/hud_housing/usa.csv` -_**NOTE:** You have the option to pass the name of a specific data source to the `etl-run` command, which will limit the execution of the ETL process to that specific data source._ -_For example: `poetry run python application.py etl-run ejscreen` would only run the ETL process for EJSCREEN data._ +_**NOTE:** You have the option to pass the name of a specific data source to the `etl-run` command using the `-d` flag, which will limit the execution of the ETL process to that specific data source._ +_For example: `poetry run python application.py etl-run -d ejscreen` would only run the ETL process for EJSCREEN data._ #### Step 2: Calculate the Justice40 score experiments @@ -74,7 +74,31 @@ _For example: `poetry run python application.py etl-run ejscreen` would only run #### Step 3: Compare the Justice40 score experiments to other indices -1. TODO: Describe the steps for this +We are building a comparison tool to enable easy (or at least straightforward) comparison of the Justice40 score with other existing indices. The goal of having this is so that as we experiment and iterate with a scoring methodology, we can understand how our score overlaps with or differs from other indices that communities, nonprofits, and governmentss use to inform decision making. + +Right now, our comparison tool exists simply as a python notebook in `data/data-pipeline/ipython/scoring_comparison.ipynb`. + +To run this comparison tool: + +1. Make sure you've gone through the above steps to run the data ETL and score generation. +1. From this directory (`data/data-pipeline`), navigate to the `ipython` directory: `cd ipython`. +1. Ensure you have `pandoc` installed on your computer. If you're on a Mac, run `brew install pandoc`; for other OSes, see pandoc's [installation guide](https://pandoc.org/installing.html). +1. Install the extra dependencies: +``` + pip install pypandoc + pip install requests + pip install us + pip install tqdm + pip install dynaconf + pip instal xlsxwriter +``` +1. Start the notebooks: `jupyter notebook` +1. In your browser, navigate to one of the URLs returned by the above command. +1. Select `scoring_comparison.ipynb` from the options in your browser. +1. Run through the steps in the notebook. You can step through them one at a time by clicking the "Run" button for each cell, or open the "Cell" menu and click "Run all" to run them all at once. +1. Reports and spreadsheets generated by the comparison tool will be available in `data/data-pipeline/data/comparison_outputs`. + +*NOTE:* This may take several minutes or over an hour to fully execute and generate the reports. ### Data Sources diff --git a/data/data-pipeline/ipython/scoring_comparison.ipynb b/data/data-pipeline/ipython/scoring_comparison.ipynb index 125cbb83..76c47c45 100644 --- a/data/data-pipeline/ipython/scoring_comparison.ipynb +++ b/data/data-pipeline/ipython/scoring_comparison.ipynb @@ -9,11 +9,6 @@ }, "outputs": [], "source": [ - "# Before running this script as it currently stands, you'll need to run these notebooks (in any order):\n", - "# * score_calc.ipynb\n", - "# * calenviroscreen_etl.ipynb\n", - "# * hud_recap_etl.ipynb\n", - "\n", "import collections\n", "import functools\n", "import IPython\n", @@ -92,7 +87,243 @@ "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.9/site-packages/IPython/core/interactiveshell.py:3169: DtypeWarning: Columns (87,88,90) have mixed types.Specify dtype option on import or set low_memory=False.\n", + " has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n" + ] + }, + { + "data": { + "text/html": [ + "
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---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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\n", + "\n", + " | GEOID10_TRACT | \n", + "Total Population | \n", + "California County | \n", + "ZIP | \n", + "Nearby City \\r\\n(to help approximate location only) | \n", + "Longitude | \n", + "Latitude | \n", + "calenviroscreen_score | \n", + "calenviroscreen_percentile | \n", + "DRAFT CES 4.0\\r\\nPercentile Range | \n", + "... | \n", + "Poverty | \n", + "Poverty Pctl | \n", + "Unemployment | \n", + "Unemployment Pctl | \n", + "Housing Burden | \n", + "Housing Burden Pctl | \n", + "Pop. Char. | \n", + "Pop. Char. Score | \n", + "Pop. Char. Pctl | \n", + "calenviroscreen_priority_community | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", + "06019001100 | \n", + "2760 | \n", + "Fresno | \n", + "93706 | \n", + "Fresno | \n", + "-119.78 | \n", + "36.71 | \n", + "94.61 | \n", + "100.00 | \n", + "95-100% (highest scores) | \n", + "... | \n", + "76.60 | \n", + "98.43 | \n", + "16.20 | \n", + "97.15 | \n", + "30.70 | \n", + "90.61 | \n", + "93.73 | \n", + "9.72 | \n", + "99.87 | \n", + "True | \n", + "
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4 | \n", + "06037204920 | \n", + "2639 | \n", + "Los Angeles | \n", + "90023 | \n", + "Los Angeles | \n", + "-118.20 | \n", + "34.02 | \n", + "82.90 | \n", + "99.95 | \n", + "95-100% (highest scores) | \n", + "... | \n", + "64.90 | \n", + "93.51 | \n", + "5.60 | \n", + "43.81 | \n", + "25.00 | \n", + "77.95 | \n", + "83.95 | \n", + "8.70 | \n", + "95.78 | \n", + "True | \n", + "
5 rows × 59 columns
\n", + "\n", + " | FID | \n", + "GEOID10_TRACT | \n", + "STATE | \n", + "STUSAB | \n", + "STATE_NAME | \n", + "COUNTY | \n", + "COUNTY_NAME | \n", + "CNTY_FIPS | \n", + "TRACT | \n", + "RCAP_90 | \n", + "RCAP_00 | \n", + "RCAP_10 | \n", + "hud_recap_priority_community | \n", + "SHAPE_Length | \n", + "SHAPE_Area | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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4 | \n", + "30078 | \n", + "01001020500 | \n", + "1 | \n", + "AL | \n", + "Alabama | \n", + "1 | \n", + "Autauga | \n", + "1001 | \n", + "20500 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.16 | \n", + "0.00 | \n", + "
\n", + " | GEOID10_TRACT | \n", + "Total Population | \n", + "California County | \n", + "ZIP | \n", + "Nearby City \\r\\n(to help approximate location only) | \n", + "Longitude | \n", + "Latitude | \n", + "calenviroscreen_score | \n", + "calenviroscreen_percentile | \n", + "DRAFT CES 4.0\\r\\nPercentile Range | \n", + "... | \n", + "COUNTY | \n", + "COUNTY_NAME | \n", + "CNTY_FIPS | \n", + "TRACT | \n", + "RCAP_90 | \n", + "RCAP_00 | \n", + "RCAP_10 | \n", + "hud_recap_priority_community | \n", + "SHAPE_Length | \n", + "SHAPE_Area | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", + "06019001100 | \n", + "2760.00 | \n", + "Fresno | \n", + "93706.00 | \n", + "Fresno | \n", + "-119.78 | \n", + "36.71 | \n", + "94.61 | \n", + "100.00 | \n", + "95-100% (highest scores) | \n", + "... | \n", + "19 | \n", + "Fresno | \n", + "6019 | \n", + "1100 | \n", + "0.00 | \n", + "1.00 | \n", + "1.00 | \n", + "True | \n", + "0.09 | \n", + "0.00 | \n", + "
1 | \n", + "06077000700 | \n", + "4177.00 | \n", + "San Joaquin | \n", + "95206.00 | \n", + "Stockton | \n", + "-121.29 | \n", + "37.94 | \n", + "90.83 | \n", + "99.99 | \n", + "95-100% (highest scores) | \n", + "... | \n", + "77 | \n", + "San Joaquin | \n", + "6077 | \n", + "700 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "True | \n", + "0.07 | \n", + "0.00 | \n", + "
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4 | \n", + "06037204920 | \n", + "2639.00 | \n", + "Los Angeles | \n", + "90023.00 | \n", + "Los Angeles | \n", + "-118.20 | \n", + "34.02 | \n", + "82.90 | \n", + "99.95 | \n", + "95-100% (highest scores) | \n", + "... | \n", + "37 | \n", + "Los Angeles | \n", + "6037 | \n", + "204920 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.04 | \n", + "0.00 | \n", + "
5 rows × 73 columns
\n", + "\n", + " | GEOID10 | \n", + "Housing burden (percent) | \n", + "Total population | \n", + "Air toxics cancer risk | \n", + "Respiratory hazard index | \n", + "Diesel particulate matter | \n", + "Particulate matter (PM2.5) | \n", + "Ozone_x | \n", + "Traffic proximity and volume | \n", + "Proximity to RMP sites | \n", + "... | \n", + "COUNTY | \n", + "COUNTY_NAME | \n", + "CNTY_FIPS | \n", + "TRACT | \n", + "RCAP_90 | \n", + "RCAP_00 | \n", + "RCAP_10 | \n", + "hud_recap_priority_community | \n", + "SHAPE_Length | \n", + "SHAPE_Area | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", + "010010201001 | \n", + "0.15 | \n", + "692 | \n", + "49.38 | \n", + "0.79 | \n", + "0.28 | \n", + "10.00 | \n", + "40.12 | \n", + "91.02 | \n", + "0.09 | \n", + "... | \n", + "1.00 | \n", + "Autauga | \n", + "1001.00 | \n", + "20100.00 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.15 | \n", + "0.00 | \n", + "
1 | \n", + "010010201002 | \n", + "0.15 | \n", + "1153 | \n", + "49.38 | \n", + "0.79 | \n", + "0.28 | \n", + "10.00 | \n", + "40.12 | \n", + "2.62 | \n", + "0.07 | \n", + "... | \n", + "1.00 | \n", + "Autauga | \n", + "1001.00 | \n", + "20100.00 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.15 | \n", + "0.00 | \n", + "
2 | \n", + "010010202001 | \n", + "0.25 | \n", + "1020 | \n", + "50.32 | \n", + "0.81 | \n", + "0.30 | \n", + "10.07 | \n", + "40.22 | \n", + "4.68 | \n", + "0.08 | \n", + "... | \n", + "1.00 | \n", + "Autauga | \n", + "1001.00 | \n", + "20200.00 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.09 | \n", + "0.00 | \n", + "
3 | \n", + "010010202002 | \n", + "0.25 | \n", + "1152 | \n", + "50.32 | \n", + "0.81 | \n", + "0.30 | \n", + "10.07 | \n", + "40.22 | \n", + "218.65 | \n", + "0.09 | \n", + "... | \n", + "1.00 | \n", + "Autauga | \n", + "1001.00 | \n", + "20200.00 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.09 | \n", + "0.00 | \n", + "
4 | \n", + "010010203001 | \n", + "0.21 | \n", + "2555 | \n", + "50.77 | \n", + "0.82 | \n", + "0.36 | \n", + "10.12 | \n", + "40.31 | \n", + "69.64 | \n", + "0.08 | \n", + "... | \n", + "1.00 | \n", + "Autauga | \n", + "1001.00 | \n", + "20300.00 | \n", + "0.00 | \n", + "0.00 | \n", + "0.00 | \n", + "False | \n", + "0.10 | \n", + "0.00 | \n", + "
5 rows × 165 columns
\n", + "\n", + " | \n", + " | GEOID10_STATE | \n", + "State name | \n", + "Total CBGs in state | \n", + "Total population in state | \n", + "Score A (top 25th percentile) (priority population) | \n", + "Score A (top 25th percentile) (total CBGs) | \n", + "Score A (top 25th percentile) (percent CBGs) | \n", + "Score A (top 25th percentile) (percent population) | \n", + "Score B (top 25th percentile) (priority population) | \n", + "Score B (top 25th percentile) (total CBGs) | \n", + "... | \n", + "Score E (top 25th percentile) (percent CBGs) | \n", + "Score E (top 25th percentile) (percent population) | \n", + "calenviroscreen_priority_community (priority population) | \n", + "calenviroscreen_priority_community (total CBGs) | \n", + "calenviroscreen_priority_community (percent CBGs) | \n", + "calenviroscreen_priority_community (percent population) | \n", + "hud_recap_priority_community (priority population) | \n", + "hud_recap_priority_community (total CBGs) | \n", + "hud_recap_priority_community (percent CBGs) | \n", + "hud_recap_priority_community (percent population) | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
GEOID10_STATE | \n", + "\n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " | \n", + " |
01 | \n", + "0 | \n", + "01 | \n", + "Alabama | \n", + "3438 | \n", + "4850771 | \n", + "1547345 | \n", + "1326 | \n", + "0.39 | \n", + "0.32 | \n", + "1556417 | \n", + "1323 | \n", + "... | \n", + "0.23 | \n", + "0.19 | \n", + "0 | \n", + "0 | \n", + "0.00 | \n", + "0.00 | \n", + "235117 | \n", + "258 | \n", + "0.08 | \n", + "0.05 | \n", + "
02 | \n", + "0 | \n", + "02 | \n", + "Alaska | \n", + "534 | \n", + "738565 | \n", + "63868 | \n", + "57 | \n", + "0.11 | \n", + "0.09 | \n", + "63868 | \n", + "57 | \n", + "... | \n", + "0.14 | \n", + "0.12 | \n", + "0 | \n", + "0 | \n", + "0.00 | \n", + "0.00 | \n", + "6536 | \n", + "8 | \n", + "0.01 | \n", + "0.01 | \n", + "
04 | \n", + "0 | \n", + "04 | \n", + "Arizona | \n", + "4178 | \n", + "6809946 | \n", + "1956052 | \n", + "1230 | \n", + "0.29 | \n", + "0.29 | \n", + "1960856 | \n", + "1231 | \n", + "... | \n", + "0.30 | \n", + "0.30 | \n", + "0 | \n", + "0 | \n", + "0.00 | \n", + "0.00 | \n", + "560353 | \n", + "378 | \n", + "0.09 | \n", + "0.08 | \n", + "
05 | \n", + "0 | \n", + "05 | \n", + "Arkansas | \n", + "2147 | \n", + "2977944 | \n", + "960799 | \n", + "817 | \n", + "0.38 | \n", + "0.32 | \n", + "975780 | \n", + "826 | \n", + "... | \n", + "0.20 | \n", + "0.18 | \n", + "0 | \n", + "0 | \n", + "0.00 | \n", + "0.00 | \n", + "101200 | \n", + "106 | \n", + "0.05 | \n", + "0.03 | \n", + "
06 | \n", + "0 | \n", + "06 | \n", + "California | \n", + "23212 | \n", + "38982847 | \n", + "12610810 | \n", + "7102 | \n", + "0.31 | \n", + "0.32 | \n", + "12556846 | \n", + "7065 | \n", + "... | \n", + "0.40 | \n", + "0.42 | \n", + "9610287 | \n", + "5690 | \n", + "0.25 | \n", + "0.25 | \n", + "1748765 | \n", + "1013 | \n", + "0.04 | \n", + "0.04 | \n", + "
5 rows × 32 columns
\n", + "