From 10323beafce8a9b841fc4b9f1bc70666b1b6de16 Mon Sep 17 00:00:00 2001 From: Darren Vengroff Date: Wed, 18 Dec 2024 09:41:49 -0500 Subject: [PATCH 1/6] Add a job to run nbmake on all the notebooks. --- .github/workflows/nbmake.yaml | 55 +++++++++++++++++++++++++++++++++++ 1 file changed, 55 insertions(+) create mode 100644 .github/workflows/nbmake.yaml diff --git a/.github/workflows/nbmake.yaml b/.github/workflows/nbmake.yaml new file mode 100644 index 0000000..d465a2e --- /dev/null +++ b/.github/workflows/nbmake.yaml @@ -0,0 +1,55 @@ +# Test run all the notebooks whenever we push a branch. + +name: nbmake + +on: + push: + branches-ignore: + - main + + # Allows you to run this workflow manually from the Actions tab + workflow_dispatch: + +jobs: + # List the notebooks + list-notebooks: + runs-on: ubuntu-latest + outputs: + matrix: ${{ steps.notebook-matrix.outputs.matrix }} + steps: + - uses: actions/checkout@v4 + - id: notebook-matrix + run: echo "matrix=$(find notebooks -name "*.ipynb" | jq -R -s -c 'split("\n")[:-1]')" >> $GITHUB_OUTPUT + nbmake: + needs: list-notebooks + runs-on: ubuntu-latest + strategy: + matrix: + notebook: ${{ fromJson(needs.list-notebooks.outputs.matrix) }} + fail-fast: false + steps: + + - uses: actions/checkout@v4 + + - name: Set up Python + id: setup-python + uses: actions/setup-python@v5 + with: + python-version: "3.12" + + - name: Install poetry + uses: abatilo/actions-poetry@v2 + + - name: Use poetry to install dependencies. + run: poetry install --without dev-db + + - name: Install API key + env: # Or as an environment variable + RA_API_KEY: ${{ secrets.RA_API_KEY }} + run: | + mkdir ~/.rwapi + echo "$RA_API_KEY" > ~/.rwapi/api_key.txt + + - name: Test the notebook + run: | + pytest --nbmake "${{matrix.notebook}}" From 11d0ceb25e2180dc145db72689e131c093f03856 Mon Sep 17 00:00:00 2001 From: Darren Vengroff Date: Wed, 18 Dec 2024 09:47:59 -0500 Subject: [PATCH 2/6] Get the tools we need. --- .github/workflows/nbmake.yaml | 2 +- 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files = [ [metadata] lock-version = "2.0" python-versions = "^3.11" -content-hash = "fc329065b42f307ab751226847d3a09f8136d4e1ea154808d8ddb2f7618f1e60" +content-hash = "baea9f3dc820e331fefeb7fa6a41a3289bc9930ceeff1b7f634eb18c0dd4e188" diff --git a/pyproject.toml b/pyproject.toml index e7c2b3c..4b10913 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,6 +12,14 @@ jupyterlab = "^4.3.2" ipywidgets = "^8.1.5" requests = "^2.28.0" +[tool.poetry.group.dev.dependencies] +black = {extras = ["jupyter"], version = "^24.10.0"} +flake8 = "^7.1.1" +ruff = "^0.8.3" + +[tool.poetry.group.test.dependencies] +pytest = "^8.3.4" + [build-system] requires = ["poetry-core"] From b4c44f6e52229b18c90cb60a6d6fb91a1b966a0b Mon Sep 17 00:00:00 2001 From: Darren Vengroff Date: Wed, 18 Dec 2024 09:56:37 -0500 Subject: [PATCH 3/6] Install the test group. --- .github/workflows/nbmake.yaml | 2 +- pyproject.toml | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/.github/workflows/nbmake.yaml b/.github/workflows/nbmake.yaml index 9a6cd55..f3187a3 100644 --- a/.github/workflows/nbmake.yaml +++ b/.github/workflows/nbmake.yaml @@ -41,7 +41,7 @@ jobs: uses: abatilo/actions-poetry@v2 - name: Use poetry to install dependencies. - run: poetry install + run: poetry install --with test - name: Install API key env: # Or as an environment variable diff --git a/pyproject.toml b/pyproject.toml index 4b10913..4bd3566 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,7 +20,6 @@ ruff = "^0.8.3" [tool.poetry.group.test.dependencies] pytest = "^8.3.4" - [build-system] requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" From 6d0b7275023115caa294821fd09e8cbb3685d18b Mon Sep 17 00:00:00 2001 From: Darren Vengroff Date: Wed, 18 Dec 2024 15:09:31 -0500 Subject: [PATCH 4/6] poetry run --- .github/workflows/nbmake.yaml | 2 +- poetry.lock | 47 ++++++++++++++++++++++++----------- pyproject.toml | 2 ++ 3 files changed, 35 insertions(+), 16 deletions(-) diff --git a/.github/workflows/nbmake.yaml b/.github/workflows/nbmake.yaml index f3187a3..a15eedc 100644 --- a/.github/workflows/nbmake.yaml +++ b/.github/workflows/nbmake.yaml @@ -52,4 +52,4 @@ jobs: - name: Test the notebook run: | - pytest --nbmake "${{matrix.notebook}}" + poetry run pytest --nbmake "${{matrix.notebook}}" diff --git a/poetry.lock b/poetry.lock index 77bb9c5..ffcd7f5 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1540,13 +1540,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (> [[package]] name = "jupyterlab" -version = "4.3.3" +version = "4.3.4" description = "JupyterLab computational environment" optional = false python-versions = ">=3.8" files = [ - {file = "jupyterlab-4.3.3-py3-none-any.whl", hash = "sha256:32a8fd30677e734ffcc3916a4758b9dab21b02015b668c60eb36f84357b7d4b1"}, - {file = "jupyterlab-4.3.3.tar.gz", hash = "sha256:76fa39e548fdac94dc1204af5956c556f54c785f70ee26aa47ea08eda4d5bbcd"}, + {file = "jupyterlab-4.3.4-py3-none-any.whl", hash = "sha256:b754c2601c5be6adf87cb5a1d8495d653ffb945f021939f77776acaa94dae952"}, + {file = "jupyterlab-4.3.4.tar.gz", hash = "sha256:f0bb9b09a04766e3423cccc2fc23169aa2ffedcdf8713e9e0fb33cac0b6859d0"}, ] [package.dependencies] @@ -1946,25 +1946,24 @@ files = [ [[package]] name = "nbclient" -version = "0.10.1" +version = "0.6.8" description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.7.0" files = [ - {file = "nbclient-0.10.1-py3-none-any.whl", hash = "sha256:949019b9240d66897e442888cfb618f69ef23dc71c01cb5fced8499c2cfc084d"}, - {file = "nbclient-0.10.1.tar.gz", hash = "sha256:3e93e348ab27e712acd46fccd809139e356eb9a31aab641d1a7991a6eb4e6f68"}, + {file = "nbclient-0.6.8-py3-none-any.whl", hash = "sha256:7cce8b415888539180535953f80ea2385cdbb444944cdeb73ffac1556fdbc228"}, + {file = "nbclient-0.6.8.tar.gz", hash = "sha256:268fde3457cafe1539e32eb1c6d796bbedb90b9e92bacd3e43d83413734bb0e8"}, ] [package.dependencies] -jupyter-client = ">=6.1.12" -jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0" -nbformat = ">=5.1" -traitlets = ">=5.4" +jupyter-client = ">=6.1.5" +nbformat = ">=5.0" +nest-asyncio = "*" +traitlets = ">=5.2.2" [package.extras] -dev = ["pre-commit"] -docs = ["autodoc-traits", "flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "mock", "moto", "myst-parser", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling", "testpath", "xmltodict"] -test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"] +sphinx = ["Sphinx (>=1.7)", "autodoc-traits", "mock", "moto", "myst-parser", "sphinx-book-theme"] +test = ["black", "check-manifest", "flake8", "ipykernel", "ipython", "ipywidgets", "mypy", "nbconvert", "pip (>=18.1)", "pre-commit", "pytest (>=4.1)", "pytest-asyncio", "pytest-cov (>=2.6.1)", "setuptools (>=60.0)", "testpath", "twine (>=1.11.0)", "xmltodict"] [[package]] name = "nbconvert" @@ -2024,6 +2023,24 @@ traitlets = ">=5.1" docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"] test = ["pep440", "pre-commit", "pytest", "testpath"] +[[package]] +name = "nbmake" +version = "1.5.4" +description = "Pytest plugin for testing notebooks" +optional = false +python-versions = "<4.0.0,>=3.8.0" +files = [ + {file = "nbmake-1.5.4-py3-none-any.whl", hash = "sha256:8e440a61a7d4ab303064aa86b8d2c088177c89960e2b4a0f91a768dc9f68382b"}, + {file = "nbmake-1.5.4.tar.gz", hash = "sha256:56417fe80d50069671122955532df6e26369a23f68b9c6e2191ae9cfef19abb2"}, +] + +[package.dependencies] +ipykernel = ">=5.4.0" +nbclient = ">=0.6.6,<0.7.0" +nbformat = ">=5.0.8,<6.0.0" +Pygments = ">=2.7.3,<3.0.0" +pytest = ">=6.1.0" + [[package]] name = "nbsphinx" version = "0.9.5" @@ -3763,4 +3780,4 @@ files = [ [metadata] lock-version = "2.0" python-versions = "^3.11" -content-hash = "baea9f3dc820e331fefeb7fa6a41a3289bc9930ceeff1b7f634eb18c0dd4e188" +content-hash = "0e00f5772f9db03b8ef89920d035b905fe135f523a8b627f2d9c8490c1372b61" diff --git a/pyproject.toml b/pyproject.toml index 4bd3566..7aa60ff 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,6 +4,7 @@ version = "0.1.0" description = "Demonstrate calling various RA APIs." authors = ["Darren Vengroff "] readme = "README.md" +package-mode = false [tool.poetry.dependencies] python = "^3.11" @@ -19,6 +20,7 @@ ruff = "^0.8.3" [tool.poetry.group.test.dependencies] pytest = "^8.3.4" +nbmake = "^1.5.4" [build-system] requires = ["poetry-core"] From 609eb12de613de943e5d2e27a060fbdc38e85f2e Mon Sep 17 00:00:00 2001 From: Darren Vengroff Date: Wed, 18 Dec 2024 15:20:18 -0500 Subject: [PATCH 5/6] Use the new API. --- notebooks/Health Impacts.ipynb | 1705 ++------------------------------ 1 file changed, 82 insertions(+), 1623 deletions(-) diff --git a/notebooks/Health Impacts.ipynb b/notebooks/Health Impacts.ipynb index 3fc4958..aed21f9 100644 --- a/notebooks/Health Impacts.ipynb +++ b/notebooks/Health Impacts.ipynb @@ -61,7 +61,8 @@ "outputs": [], "source": [ "import requests\n", - "import pandas as pd" + "import pandas as pd\n", + "from pathlib import Path" ] }, { @@ -74,13 +75,29 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 10, "id": "d969debb-d64a-46d6-a35e-c4744704981d", "metadata": {}, "outputs": [], "source": [ - "#URL = \"https://api.rewiringamerica.org/api/v1/health-impacts\"\n", - "URL = \"http://127.0.0.1:8080/api/v1/health-impacts/\"" + "URL = \"https://api.rewiringamerica.org/api/v1/health-impacts/\"\n", + "\n", + "API_KEY = None # Put your API key here, or better yet in the file ~/.rwapi/api_key.txt" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a96e96ab", + "metadata": {}, + "outputs": [], + "source": [ + "if API_KEY is None:\n", + " api_key_path = Path.home() / \".rwapi\" / \"api_key.txt\"\n", + "\n", + " if api_key_path.is_file():\n", + " with open(api_key_path) as f:\n", + " API_KEY = f.read().strip()" ] }, { @@ -107,7 +124,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 12, "id": "6ec6c453-4c96-4b5d-9b0b-625d867817aa", "metadata": {}, "outputs": [], @@ -132,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "id": "0be7df36-e82a-4b7e-badc-3a6858f297b0", "metadata": {}, "outputs": [], @@ -140,6 +157,7 @@ "headers = {\n", " \"Content-Type\": \"application/json\",\n", " \"Accept\": \"application/json\",\n", + " \"Authorization\": f\"Bearer {API_KEY}\"\n", "}" ] }, @@ -156,7 +174,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 14, "id": "25b413d2-b03f-4685-8d40-7aee05f36fd5", "metadata": {}, "outputs": [], @@ -167,17 +185,17 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "id": "fdcbf5e3-048e-4903-a773-3c81b8ca21db", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "200" + "401" ] }, - "execution_count": 6, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -188,17 +206,17 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "b0a4555e-04e4-4fdd-8c89-0cb474ed16cf", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'{\"data\":[{\"state\":\"WI\",\"premature_mortality_incidence_delta\":27.999598212086404,\"number_of_households\":2189591}]}'" + "'{\\n \"type\": \"https://httpproblems.com/http-status/404\",\\n \"title\": \"Not Found\",\\n \"status\": 404,\\n \"instance\": \"/api/v1/health_impacts/\",\\n \"trace\": {\\n \"timestamp\": \"2024-12-18T20:16:33.888Z\",\\n \"requestId\": \"6962b3c2-f447-433f-927b-06094432ac32\",\\n \"buildId\": \"41522c37-2c71-4e65-a2f9-c86f10298cc8\",\\n \"rayId\": \"8f41d4d38f674233\"\\n }\\n}'" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -224,67 +242,32 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "1ad2c02b-aa58-4389-85cb-71d38208f44a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "KeyError", + "evalue": "'data'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m df_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdata\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m)\n", + "\u001b[0;31mKeyError\u001b[0m: 'data'" + ] + } + ], "source": [ "df_data = pd.DataFrame(response.json()[\"data\"])" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "2c651847-38e7-4a3d-b461-a5977efaddc4", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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statepremature_mortality_incidence_deltanumber_of_households
0WI27.9995982189591
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" - ], - "text/plain": [ - " state premature_mortality_incidence_delta number_of_households\n", - "0 WI 27.999598 2189591" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df_data" ] @@ -311,7 +294,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "c0bb2ad4", "metadata": {}, "outputs": [], @@ -326,393 +309,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "290ec3a7", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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statepremature_mortality_incidence_deltanumber_of_households
0AL15.8625501409929
1AR11.267364884020
2AZ2.9755781848670
3CA166.43674512098560
4CO27.3285651904118
5CT43.7845591290316
6DC10.717516236562
7DE11.109927299274
8FL10.9209494840199
9GA38.9722642898066
10IA8.6354221161018
11ID1.465138511865
12IL104.4448874599279
13IN32.7276872247702
14KS9.405204983536
15KY21.2646791295643
16LA13.3961551555692
17MA131.9831452449155
18MD89.9417861791043
19ME3.993857475545
20MI141.6406293679665
21MN26.0456842036322
22MO24.8055221954482
23MS7.573313844553
24MT0.663670364165
25NC33.7152452827606
26ND-0.755750281356
27NE7.346933676030
28NH7.853812469734
29NJ204.1867093061262
30NM3.719333669492
31NV6.369278954238
32NY870.0829236859572
33OH96.5126014281361
34OK18.1262031243343
35OR8.7812991274336
36PA199.9169814489835
37RI19.806513392252
38SC12.9035931373609
39SD1.107708308717
40TN23.1260461850365
41TX71.8514078269985
42UT6.068804873367
43VA47.6502022324458
44VT1.422156208233
45WA17.7123462294433
46WI27.9995982189591
47WV4.339894573851
48WY0.357306201937
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statepremature_mortality_incidence_deltanumber_of_householdsmortality_per_household
32NY870.08292368595720.000127
29NJ204.18670930612620.000067
17MA131.98314524491550.000054
37RI19.8065133922520.000050
18MD89.94178617910430.000050
6DC10.7175162365620.000045
36PA199.91698144898350.000045
20MI141.64062936796650.000038
7DE11.1099272992740.000037
5CT43.78455912903160.000034
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" - ], - "text/plain": [ - " state premature_mortality_incidence_delta number_of_households \\\n", - "32 NY 870.082923 6859572 \n", - "29 NJ 204.186709 3061262 \n", - "17 MA 131.983145 2449155 \n", - "37 RI 19.806513 392252 \n", - "18 MD 89.941786 1791043 \n", - "6 DC 10.717516 236562 \n", - "36 PA 199.916981 4489835 \n", - "20 MI 141.640629 3679665 \n", - "7 DE 11.109927 299274 \n", - "5 CT 43.784559 1290316 \n", - "\n", - " mortality_per_household \n", - "32 0.000127 \n", - "29 0.000067 \n", - "17 0.000054 \n", - "37 0.000050 \n", - "18 0.000050 \n", - "6 0.000045 \n", - "36 0.000045 \n", - "20 0.000038 \n", - "7 0.000037 \n", - "5 0.000034 " - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df_data_all_states[\"mortality_per_household\"] = (\n", " df_data_all_states[\"premature_mortality_incidence_delta\"] / df_data_all_states[\"number_of_households\"]\n", @@ -895,7 +362,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "6d25841e", "metadata": {}, "outputs": [], @@ -912,219 +379,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "639ba028", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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statepremature_mortality_incidence_deltacountynumber_of_households
0NJ2.48435300191768
1NJ56.538151003330509
2NJ16.011621005153027
3NJ23.783300007176998
4NJ0.73992900938257
5NJ1.42277901146731
6NJ18.586102013268039
7NJ12.13547801599274
8NJ27.337756017235109
9NJ0.68520601944794
10NJ2.219248021125424
11NJ8.060530023271913
12NJ9.018796025223729
13NJ2.621162027174819
14NJ5.849927029208717
15NJ4.099941031162228
16NJ1.20394803323245
17NJ0.969147035114528
18NJ0.45177003749637
19NJ9.287547039183293
20NJ0.68001504139225
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" - ], - "text/plain": [ - " state premature_mortality_incidence_delta county number_of_households\n", - "0 NJ 2.484353 001 91768\n", - "1 NJ 56.538151 003 330509\n", - "2 NJ 16.011621 005 153027\n", - "3 NJ 23.783300 007 176998\n", - "4 NJ 0.739929 009 38257\n", - "5 NJ 1.422779 011 46731\n", - "6 NJ 18.586102 013 268039\n", - "7 NJ 12.135478 015 99274\n", - "8 NJ 27.337756 017 235109\n", - "9 NJ 0.685206 019 44794\n", - "10 NJ 2.219248 021 125424\n", - "11 NJ 8.060530 023 271913\n", - "12 NJ 9.018796 025 223729\n", - "13 NJ 2.621162 027 174819\n", - "14 NJ 5.849927 029 208717\n", - "15 NJ 4.099941 031 162228\n", - "16 NJ 1.203948 033 23245\n", - "17 NJ 0.969147 035 114528\n", - "18 NJ 0.451770 037 49637\n", - "19 NJ 9.287547 039 183293\n", - "20 NJ 0.680015 041 39225" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df_data_nj_counties = pd.DataFrame(response_nj_counties.json()[\"data\"])\n", "df_data_nj_counties" @@ -1144,21 +402,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "047424fd", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'At the state level: 204.2; Summed over counties: 204.2.'" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "statewide_nj_mortality = df_data_all_states[df_data_all_states[\"state\"] == 'NJ'][\"premature_mortality_incidence_delta\"].iloc[0]\n", "sum_of_nj_county_mortality = df_data_nj_counties[\"premature_mortality_incidence_delta\"].sum()\n", @@ -1178,7 +425,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "d9183a7b", "metadata": {}, "outputs": [], @@ -1206,21 +453,10 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "eccd6394", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['data', 'warnings'])" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "response_nd_counties_json = response_nd_counties.json()\n", "\n", @@ -1237,21 +473,10 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "f9ca8c08", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['data'])" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "response_nj_counties.json().keys()" ] @@ -1266,21 +491,10 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "3a225045", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['Some results do not meet the recommended sample size of 5,000 households. Interpret these results with caution.']" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "response_nd_counties.json()[\"warnings\"]" ] @@ -1299,475 +513,10 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "878a23f3", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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statepremature_mortality_incidence_deltacountynumber_of_households
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statepremature_mortality_incidence_deltacountynumber_of_households
7ND-0.14850201533414
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statepm25-pri_kg_deltanh3_kg_deltanox_kg_deltavoc_kg_deltaso2_kg_deltanumber_of_households
0CT379625.2510185.174537e+054.971106e+061.952656e+05-7.025032e+041290316
1NJ72953.8553091.881648e+061.015888e+075.096962e+05-1.061043e+063061262
2NY744221.9921213.675171e+062.237453e+071.082938e+06-1.175397e+066859572
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statein_sqft_binpremature_mortality_incidence_deltanumber_of_households
0WI0-14999.4951581119372
1WI1500-24999.751330682809
2WI2500-54995.756183315497
3WI5500+2.99692871913
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" - ], - "text/plain": [ - " state in_sqft_bin premature_mortality_incidence_delta number_of_households\n", - "0 WI 0-1499 9.495158 1119372\n", - "1 WI 1500-2499 9.751330 682809\n", - "2 WI 2500-5499 5.756183 315497\n", - "3 WI 5500+ 2.996928 71913" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df_groups = pd.DataFrame(response_groups.json()[\"data\"])\n", "df_groups" @@ -2165,21 +646,10 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "id": "4e67d269", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'28.0'" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "grouped_sum = df_groups[\"premature_mortality_incidence_delta\"].sum()\n", "f\"{grouped_sum:.1f}\"" @@ -2204,7 +674,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "d0f4f7d6", "metadata": {}, "outputs": [], @@ -2225,7 +695,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "id": "92b36142", "metadata": {}, "outputs": [], @@ -2240,7 +710,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "d07ae82a", "metadata": {}, "outputs": [], @@ -2258,21 +728,10 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "id": "03a94766", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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statepremature_mortality_incidence_deltanumber_of_households
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" + ], + "text/plain": [ + " state premature_mortality_incidence_delta number_of_households\n", + "0 WI 27.999598 2189591" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_data" ] @@ -294,7 +308,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "c0bb2ad4", "metadata": {}, "outputs": [], @@ -309,10 +323,393 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "290ec3a7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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statepremature_mortality_incidence_deltanumber_of_households
0AL15.8625501409929
1AR11.267364884020
2AZ2.9755781848670
3CA166.43674512098560
4CO27.3285651904118
5CT43.7845591290316
6DC10.717516236562
7DE11.109927299274
8FL10.9209494840199
9GA38.9722642898066
10IA8.6354221161018
11ID1.465138511865
12IL104.4448874599279
13IN32.7276872247702
14KS9.405204983536
15KY21.2646791295643
16LA13.3961551555692
17MA131.9831452449155
18MD89.9417861791043
19ME3.993857475545
20MI141.6406293679665
21MN26.0456842036322
22MO24.8055221954482
23MS7.573313844553
24MT0.663670364165
25NC33.7152452827606
26ND-0.755750281356
27NE7.346933676030
28NH7.853812469734
29NJ204.1867093061262
30NM3.719333669492
31NV6.369278954238
32NY870.0829236859572
33OH96.5126014281361
34OK18.1262031243343
35OR8.7812991274336
36PA199.9169814489835
37RI19.806513392252
38SC12.9035931373609
39SD1.107708308717
40TN23.1260461850365
41TX71.8514078269985
42UT6.068804873367
43VA47.6502022324458
44VT1.422156208233
45WA17.7123462294433
46WI27.9995982189591
47WV4.339894573851
48WY0.357306201937
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" + ], + "text/plain": [ + " state premature_mortality_incidence_delta number_of_households\n", + "0 AL 15.862550 1409929\n", + "1 AR 11.267364 884020\n", + "2 AZ 2.975578 1848670\n", + "3 CA 166.436745 12098560\n", + "4 CO 27.328565 1904118\n", + "5 CT 43.784559 1290316\n", + "6 DC 10.717516 236562\n", + "7 DE 11.109927 299274\n", + "8 FL 10.920949 4840199\n", + "9 GA 38.972264 2898066\n", + "10 IA 8.635422 1161018\n", + "11 ID 1.465138 511865\n", + "12 IL 104.444887 4599279\n", + "13 IN 32.727687 2247702\n", + "14 KS 9.405204 983536\n", + "15 KY 21.264679 1295643\n", + "16 LA 13.396155 1555692\n", + "17 MA 131.983145 2449155\n", + "18 MD 89.941786 1791043\n", + "19 ME 3.993857 475545\n", + "20 MI 141.640629 3679665\n", + "21 MN 26.045684 2036322\n", + "22 MO 24.805522 1954482\n", + "23 MS 7.573313 844553\n", + "24 MT 0.663670 364165\n", + "25 NC 33.715245 2827606\n", + "26 ND -0.755750 281356\n", + "27 NE 7.346933 676030\n", + "28 NH 7.853812 469734\n", + "29 NJ 204.186709 3061262\n", + "30 NM 3.719333 669492\n", + "31 NV 6.369278 954238\n", + "32 NY 870.082923 6859572\n", + "33 OH 96.512601 4281361\n", + "34 OK 18.126203 1243343\n", + "35 OR 8.781299 1274336\n", + "36 PA 199.916981 4489835\n", + "37 RI 19.806513 392252\n", + "38 SC 12.903593 1373609\n", + "39 SD 1.107708 308717\n", + "40 TN 23.126046 1850365\n", + "41 TX 71.851407 8269985\n", + "42 UT 6.068804 873367\n", + "43 VA 47.650202 2324458\n", + "44 VT 1.422156 208233\n", + "45 WA 17.712346 2294433\n", + "46 WI 27.999598 2189591\n", + "47 WV 4.339894 573851\n", + "48 WY 0.357306 201937" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_data_all_states = pd.DataFrame(response_all_states.json()[\"data\"])\n", "df_data_all_states" @@ -336,10 +733,143 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "0380351f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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statepremature_mortality_incidence_deltanumber_of_householdsmortality_per_household
32NY870.08292368595720.000127
29NJ204.18670930612620.000067
17MA131.98314524491550.000054
37RI19.8065133922520.000050
18MD89.94178617910430.000050
6DC10.7175162365620.000045
36PA199.91698144898350.000045
20MI141.64062936796650.000038
7DE11.1099272992740.000037
5CT43.78455912903160.000034
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" + ], + "text/plain": [ + " state premature_mortality_incidence_delta number_of_households \\\n", + "32 NY 870.082923 6859572 \n", + "29 NJ 204.186709 3061262 \n", + "17 MA 131.983145 2449155 \n", + "37 RI 19.806513 392252 \n", + "18 MD 89.941786 1791043 \n", + "6 DC 10.717516 236562 \n", + "36 PA 199.916981 4489835 \n", + "20 MI 141.640629 3679665 \n", + "7 DE 11.109927 299274 \n", + "5 CT 43.784559 1290316 \n", + "\n", + " mortality_per_household \n", + "32 0.000127 \n", + "29 0.000067 \n", + "17 0.000054 \n", + "37 0.000050 \n", + "18 0.000050 \n", + "6 0.000045 \n", + "36 0.000045 \n", + "20 0.000038 \n", + "7 0.000037 \n", + "5 0.000034 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_data_all_states[\"mortality_per_household\"] = (\n", " df_data_all_states[\"premature_mortality_incidence_delta\"] / df_data_all_states[\"number_of_households\"]\n", @@ -362,7 +892,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "6d25841e", "metadata": {}, "outputs": [], @@ -379,10 +909,219 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "639ba028", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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statepremature_mortality_incidence_deltacountynumber_of_households
0NJ2.48435300191768
1NJ56.538151003330509
2NJ16.011621005153027
3NJ23.783300007176998
4NJ0.73992900938257
5NJ1.42277901146731
6NJ18.586102013268039
7NJ12.13547801599274
8NJ27.337756017235109
9NJ0.68520601944794
10NJ2.219248021125424
11NJ8.060530023271913
12NJ9.018796025223729
13NJ2.621162027174819
14NJ5.849927029208717
15NJ4.099941031162228
16NJ1.20394803323245
17NJ0.969147035114528
18NJ0.45177003749637
19NJ9.287547039183293
20NJ0.68001504139225
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" + ], + "text/plain": [ + " state premature_mortality_incidence_delta county number_of_households\n", + "0 NJ 2.484353 001 91768\n", + "1 NJ 56.538151 003 330509\n", + "2 NJ 16.011621 005 153027\n", + "3 NJ 23.783300 007 176998\n", + "4 NJ 0.739929 009 38257\n", + "5 NJ 1.422779 011 46731\n", + "6 NJ 18.586102 013 268039\n", + "7 NJ 12.135478 015 99274\n", + "8 NJ 27.337756 017 235109\n", + "9 NJ 0.685206 019 44794\n", + "10 NJ 2.219248 021 125424\n", + "11 NJ 8.060530 023 271913\n", + "12 NJ 9.018796 025 223729\n", + "13 NJ 2.621162 027 174819\n", + "14 NJ 5.849927 029 208717\n", + "15 NJ 4.099941 031 162228\n", + "16 NJ 1.203948 033 23245\n", + "17 NJ 0.969147 035 114528\n", + "18 NJ 0.451770 037 49637\n", + "19 NJ 9.287547 039 183293\n", + "20 NJ 0.680015 041 39225" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_data_nj_counties = pd.DataFrame(response_nj_counties.json()[\"data\"])\n", "df_data_nj_counties" @@ -402,10 +1141,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "047424fd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'At the state level: 204.2; Summed over counties: 204.2.'" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "statewide_nj_mortality = df_data_all_states[df_data_all_states[\"state\"] == 'NJ'][\"premature_mortality_incidence_delta\"].iloc[0]\n", "sum_of_nj_county_mortality = df_data_nj_counties[\"premature_mortality_incidence_delta\"].sum()\n", @@ -425,7 +1175,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "d9183a7b", "metadata": {}, "outputs": [], @@ -453,10 +1203,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "eccd6394", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['data', 'warnings'])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "response_nd_counties_json = response_nd_counties.json()\n", "\n", @@ -473,10 +1234,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "f9ca8c08", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['data'])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "response_nj_counties.json().keys()" ] @@ -491,10 +1263,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "3a225045", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "['Some results do not meet the recommended sample size of 5,000 households. Interpret these results with caution.']" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "response_nd_counties.json()[\"warnings\"]" ] @@ -513,10 +1296,475 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "878a23f3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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statepremature_mortality_incidence_deltacountynumber_of_households
0ND-0.0073020011211
1ND-0.0084860033632
2ND-0.0218050052421
3ND-0.002022007242
4ND-0.0145240092906
5ND-0.006226011726
6ND-0.0041930131211
7ND-0.14850201533414
8ND0.09825101766828
9ND-0.0021010191937
10ND0.0105240211937
11ND-0.005450023969
12ND-0.0069180251695
13ND-0.001642027726
14ND0.0052660291695
15ND-0.0218540311453
16ND-0.006495033726
17ND-0.02519003525424
18ND-0.0118190371695
19ND-0.0103670391453
20ND-0.0085580411211
21ND-0.0096830431695
22ND0.0067690451453
23ND-0.0044420471211
24ND-0.0079350492663
25ND0.0000570511695
26ND-0.0380460532663
27ND-0.0228730554358
28ND-0.0320140573390
29ND-0.07014705911622
30ND-0.0317710614358
31ND0.000766063969
32ND0.000813065969
33ND-0.0159190672421
34ND-0.0027150692179
35ND-0.0125600714843
36ND-0.0019970731937
37ND-0.004708075484
38ND-0.0047600776295
39ND-0.0177180794843
40ND-0.0033270811937
41ND-0.000022083726
42ND0.003352085969
43ND0.001723087242
44ND-0.0424720899443
45ND-0.006990091969
46ND-0.0426520937506
47ND-0.003209095969
48ND-0.0068590973148
49ND-0.0375260994358
50ND-0.07653410123002
51ND-0.0017271032179
52ND-0.07121110512349
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statepremature_mortality_incidence_deltacountynumber_of_households
7ND-0.14850201533414
8ND0.09825101766828
17ND-0.02519003525424
29ND-0.07014705911622
38ND-0.0047600776295
44ND-0.0424720899443
46ND-0.0426520937506
50ND-0.07653410123002
52ND-0.07121110512349
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" + ], + "text/plain": [ + " state premature_mortality_incidence_delta county number_of_households\n", + "7 ND -0.148502 015 33414\n", + "8 ND 0.098251 017 66828\n", + "17 ND -0.025190 035 25424\n", + "29 ND -0.070147 059 11622\n", + "38 ND -0.004760 077 6295\n", + "44 ND -0.042472 089 9443\n", + "46 ND -0.042652 093 7506\n", + "50 ND -0.076534 101 23002\n", + "52 ND -0.071211 105 12349" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_data_nd_counties[df_data_nd_counties[\"number_of_households\"] >= 5000]" ] @@ -547,7 +1908,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "fd08bac9", "metadata": {}, "outputs": [], @@ -561,7 +1922,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "182dbe37", "metadata": {}, "outputs": [], @@ -571,10 +1932,92 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "b60d00f2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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statepm25-pri_kg_deltanh3_kg_deltanox_kg_deltavoc_kg_deltaso2_kg_deltanumber_of_households
0CT379625.2510185.174537e+054.971106e+061.952656e+05-7.025032e+041290316
1NJ72953.8553091.881648e+061.015888e+075.096962e+05-1.061043e+063061262
2NY744221.9921213.675171e+062.237453e+071.082938e+06-1.175397e+066859572
\n", + "
" + ], + "text/plain": [ + " state pm25-pri_kg_delta nh3_kg_delta nox_kg_delta voc_kg_delta \\\n", + "0 CT 379625.251018 5.174537e+05 4.971106e+06 1.952656e+05 \n", + "1 NJ 72953.855309 1.881648e+06 1.015888e+07 5.096962e+05 \n", + "2 NY 744221.992121 3.675171e+06 2.237453e+07 1.082938e+06 \n", + "\n", + " so2_kg_delta number_of_households \n", + "0 -7.025032e+04 1290316 \n", + "1 -1.061043e+06 3061262 \n", + "2 -1.175397e+06 6859572 " + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_data_bulk = pd.DataFrame(response_bulk.json()[\"data\"])\n", "df_data_bulk" @@ -602,7 +2045,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "c7254f2d", "metadata": {}, "outputs": [], @@ -627,10 +2070,83 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "2a2ce9b4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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statein_sqft_binpremature_mortality_incidence_deltanumber_of_households
0WI0-14999.4951581119372
1WI1500-24999.751330682809
2WI2500-54995.756183315497
3WI5500+2.99692871913
\n", + "
" + ], + "text/plain": [ + " state in_sqft_bin premature_mortality_incidence_delta number_of_households\n", + "0 WI 0-1499 9.495158 1119372\n", + "1 WI 1500-2499 9.751330 682809\n", + "2 WI 2500-5499 5.756183 315497\n", + "3 WI 5500+ 2.996928 71913" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df_groups = pd.DataFrame(response_groups.json()[\"data\"])\n", "df_groups" @@ -646,10 +2162,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "id": "4e67d269", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'28.0'" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "grouped_sum = df_groups[\"premature_mortality_incidence_delta\"].sum()\n", "f\"{grouped_sum:.1f}\"" @@ -674,7 +2201,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "d0f4f7d6", "metadata": {}, "outputs": [], @@ -695,7 +2222,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "92b36142", "metadata": {}, "outputs": [], @@ -710,7 +2237,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "d07ae82a", "metadata": {}, "outputs": [], @@ -728,10 +2255,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "03a94766", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "ax = cem.plot_map(\n", " gdf_map,\n",