{
"cells": [
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'matplotlib'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-60-ffb398b1b277>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0maltair\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0malt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'matplotlib'"
]
}
],
"source": [
"import pandas as pd\n",
"import altair as alt\n",
"import matplotlib"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Look at the metadata"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"metadata_df = pd.read_json('../../data/covidtracking/states-metadata.json')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>state</th>\n",
" <th>covid19SiteOld</th>\n",
" <th>covid19Site</th>\n",
" <th>covid19SiteSecondary</th>\n",
" <th>twitter</th>\n",
" <th>pui</th>\n",
" <th>pum</th>\n",
" <th>notes</th>\n",
" <th>name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>AK</td>\n",
" <td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-...</td>\n",
" <td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-...</td>\n",
" <td>NaN</td>\n",
" <td>@Alaska_DHSS</td>\n",
" <td>All data</td>\n",
" <td>False</td>\n",
" <td>Unclear if their reported number means \"person...</td>\n",
" <td>Alaska</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>AL</td>\n",
" <td>http://www.alabamapublichealth.gov/infectiousd...</td>\n",
" <td>https://alpublichealth.maps.arcgis.com/apps/op...</td>\n",
" <td>NaN</td>\n",
" <td>@alpublichealth</td>\n",
" <td>No data</td>\n",
" <td>False</td>\n",
" <td>Last negative count from 3/16.</td>\n",
" <td>Alabama</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>AR</td>\n",
" <td>https://www.healthy.arkansas.gov/programs-serv...</td>\n",
" <td>https://www.healthy.arkansas.gov/programs-serv...</td>\n",
" <td>NaN</td>\n",
" <td>@adhpio</td>\n",
" <td>All data</td>\n",
" <td>True</td>\n",
" <td>Pending = \"PUIs\"</td>\n",
" <td>Arkansas</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>AZ</td>\n",
" <td>https://www.azdhs.gov/preparedness/epidemiolog...</td>\n",
" <td>https://www.azdhs.gov/preparedness/epidemiolog...</td>\n",
" <td>NaN</td>\n",
" <td>@azdhs</td>\n",
" <td>All data</td>\n",
" <td>False</td>\n",
" <td>Negative = “Ruled Out”. Our total is slightly ...</td>\n",
" <td>Arizona</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>CA</td>\n",
" <td>https://www.cdph.ca.gov/Programs/CID/DCDC/Page...</td>\n",
" <td>https://www.latimes.com/projects/california-co...</td>\n",
" <td>NaN</td>\n",
" <td>@CAPublicHealth</td>\n",
" <td>Only positives</td>\n",
" <td>False</td>\n",
" <td>Only positives reported regularly. Add deaths ...</td>\n",
" <td>California</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" state covid19SiteOld \\\n",
"0 AK http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-... \n",
"1 AL http://www.alabamapublichealth.gov/infectiousd... \n",
"2 AR https://www.healthy.arkansas.gov/programs-serv... \n",
"3 AZ https://www.azdhs.gov/preparedness/epidemiolog... \n",
"4 CA https://www.cdph.ca.gov/Programs/CID/DCDC/Page... \n",
"\n",
" covid19Site covid19SiteSecondary \\\n",
"0 http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-... NaN \n",
"1 https://alpublichealth.maps.arcgis.com/apps/op... NaN \n",
"2 https://www.healthy.arkansas.gov/programs-serv... NaN \n",
"3 https://www.azdhs.gov/preparedness/epidemiolog... NaN \n",
"4 https://www.latimes.com/projects/california-co... NaN \n",
"\n",
" twitter pui pum \\\n",
"0 @Alaska_DHSS All data False \n",
"1 @alpublichealth No data False \n",
"2 @adhpio All data True \n",
"3 @azdhs All data False \n",
"4 @CAPublicHealth Only positives False \n",
"\n",
" notes name \n",
"0 Unclear if their reported number means \"person... Alaska \n",
"1 Last negative count from 3/16. Alabama \n",
"2 Pending = \"PUIs\" Arkansas \n",
"3 Negative = “Ruled Out”. Our total is slightly ... Arizona \n",
"4 Only positives reported regularly. Add deaths ... California "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"metadata_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Look at the data"
]
},
{
"cell_type": "code",
"execution_count": 222,
"metadata": {},
"outputs": [],
"source": [
"data_df = pd.read_json('../../data/covidtracking/states-daily.json')\n",
"data_df['date'] = pd.to_datetime(data_df['date'], format=\"%Y%m%d\")"
]
},
{
"cell_type": "code",
"execution_count": 223,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>state</th>\n",
" <th>positive</th>\n",
" <th>negative</th>\n",
" <th>pending</th>\n",
" <th>death</th>\n",
" <th>total</th>\n",
" <th>dateChecked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2020-03-19</td>\n",
" <td>AK</td>\n",
" <td>6</td>\n",
" <td>400.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>406</td>\n",
" <td>2020-03-19T20:00:00Z</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2020-03-19</td>\n",
" <td>AL</td>\n",
" <td>68</td>\n",
" <td>28.0</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>96</td>\n",
" <td>2020-03-19T20:00:00Z</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2020-03-19</td>\n",
" <td>AR</td>\n",
" <td>46</td>\n",
" <td>310.0</td>\n",
" <td>113.0</td>\n",
" <td>NaN</td>\n",
" <td>469</td>\n",
" <td>2020-03-19T20:00:00Z</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2020-03-19</td>\n",
" <td>AS</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>2020-03-19T20:00:00Z</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2020-03-19</td>\n",
" <td>AZ</td>\n",
" <td>44</td>\n",
" <td>175.0</td>\n",
" <td>130.0</td>\n",
" <td>0.0</td>\n",
" <td>349</td>\n",
" <td>2020-03-19T20:00:00Z</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date state positive negative pending death total \\\n",
"0 2020-03-19 AK 6 400.0 NaN NaN 406 \n",
"1 2020-03-19 AL 68 28.0 NaN 0.0 96 \n",
"2 2020-03-19 AR 46 310.0 113.0 NaN 469 \n",
"3 2020-03-19 AS 0 NaN NaN 0.0 0 \n",
"4 2020-03-19 AZ 44 175.0 130.0 0.0 349 \n",
"\n",
" dateChecked \n",
"0 2020-03-19T20:00:00Z \n",
"1 2020-03-19T20:00:00Z \n",
"2 2020-03-19T20:00:00Z \n",
"3 2020-03-19T20:00:00Z \n",
"4 2020-03-19T20:00:00Z "
]
},
"execution_count": 223,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Daily counts and totals"
]
},
{
"cell_type": "code",
"execution_count": 257,
"metadata": {},
"outputs": [],
"source": [
"# compute daily differences\n",
"tdf = data_df.sort_values(['state', 'date'], ascending=[True, False]).set_index(['state', 'date'])\n",
"diffs_df = tdf[['positive', 'negative', 'death']].groupby(level='state').diff(periods=-1).dropna(how='all')\n",
"tdf_diff=tdf.join(diffs_df, rsuffix='_diff').reset_index()"
]
},
{
"cell_type": "code",
"execution_count": 276,
"metadata": {},
"outputs": [],
"source": [
"# \"Normalizing\" the totals\n",
"tdf_diff['total_10'] = tdf_diff['total']/10."
]
},
{
"cell_type": "code",
"execution_count": 278,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" import sys\n",
"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" if __name__ == '__main__':\n"
]
},
{
"data": {
"text/html": [
"\n",
"<div id=\"altair-viz-a2f753a0d34f48da9107b4032abab8e2\"></div>\n",
"<script type=\"text/javascript\">\n",
" (function(spec, embedOpt){\n",
" const outputDiv = document.getElementById(\"altair-viz-a2f753a0d34f48da9107b4032abab8e2\");\n",
" const paths = {\n",
" \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
" \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
" \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n",
" \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
" };\n",
"\n",
" function loadScript(lib) {\n",
" return new Promise(function(resolve, reject) {\n",
" var s = document.createElement('script');\n",
" s.src = paths[lib];\n",
" s.async = true;\n",
" s.onload = () => resolve(paths[lib]);\n",
" s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" });\n",
" }\n",
"\n",
" function showError(err) {\n",
" outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
" throw err;\n",
" }\n",
"\n",
" function displayChart(vegaEmbed) {\n",
" vegaEmbed(outputDiv, spec, embedOpt)\n",
" .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
" }\n",
"\n",
" if(typeof define === \"function\" && define.amd) {\n",
" requirejs.config({paths});\n",
" require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
" } else if (typeof vegaEmbed === \"function\") {\n",
" displayChart(vegaEmbed);\n",
" } else {\n",
" loadScript(\"vega\")\n",
" .then(() => loadScript(\"vega-lite\"))\n",
" .then(() => loadScript(\"vega-embed\"))\n",
" .catch(showError)\n",
" .then(() => displayChart(vegaEmbed));\n",
" }\n",
" })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"hconcat\": [{\"layer\": [{\"mark\": {\"type\": \"bar\", \"size\": 10}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Daily positive\"}, \"field\": \"daily_positive\"}}, \"height\": 150, \"title\": \"WA\", \"width\": 250}, {\"layer\": [{\"mark\": {\"type\": \"line\", \"color\": \"red\"}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Total/10\"}, \"field\": \"total_10\"}}, \"height\": 150, \"title\": \"WA\", \"width\": 250}, {\"mark\": {\"type\": \"line\", \"color\": \"orange\"}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Positive\"}, \"field\": \"positive\"}}, \"height\": 150, \"title\": \"WA\", \"width\": 250}]}], \"data\": {\"name\": \"data-e3884ceed25bdc83e388c03b5394d76a\"}, \"resolve\": {\"scale\": {\"y\": \"independent\"}}}, {\"layer\": [{\"mark\": {\"type\": \"bar\", \"size\": 10}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Daily positive\"}, \"field\": \"daily_positive\"}}, \"height\": 150, \"title\": \"CA\", \"width\": 250}, {\"layer\": [{\"mark\": {\"type\": \"line\", \"color\": \"red\"}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Total/10\"}, \"field\": \"total_10\"}}, \"height\": 150, \"title\": \"CA\", \"width\": 250}, {\"mark\": {\"type\": \"line\", \"color\": \"orange\"}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Positive\"}, \"field\": \"positive\"}}, \"height\": 150, \"title\": \"CA\", \"width\": 250}]}], \"data\": {\"name\": \"data-5524f3d9a011a4455f9aef2d5f2b332f\"}, \"resolve\": {\"scale\": {\"y\": \"independent\"}}}, {\"layer\": [{\"mark\": {\"type\": \"bar\", \"size\": 10}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Daily positive\"}, \"field\": \"daily_positive\"}}, \"height\": 150, \"title\": \"NY\", \"width\": 250}, {\"layer\": [{\"mark\": {\"type\": \"line\", \"color\": \"red\"}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Total/10\"}, \"field\": \"total_10\"}}, \"height\": 150, \"title\": \"NY\", \"width\": 250}, {\"mark\": {\"type\": \"line\", \"color\": \"orange\"}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"Date\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"axis\": {\"title\": \"Positive\"}, \"field\": \"positive\"}}, \"height\": 150, \"title\": \"NY\", \"width\": 250}]}], \"data\": {\"name\": \"data-294eebc48941097d786524a29c373ee4\"}, \"resolve\": {\"scale\": {\"y\": \"independent\"}}}], \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.2.json\", \"datasets\": {\"data-e3884ceed25bdc83e388c03b5394d76a\": [{\"state\": \"WA\", \"date\": \"2020-03-19T00:00:00\", \"positive\": 1187, \"negative\": 15918.0, \"pending\": null, \"death\": 66.0, \"total\": 17105, \"dateChecked\": \"2020-03-19T20:00:00Z\", \"positive_diff\": 175.0, \"negative_diff\": 2801.0, \"death_diff\": 14.0, \"total_10\": 1710.5, \"daily_positive\": 175.0}, {\"state\": \"WA\", \"date\": \"2020-03-18T00:00:00\", \"positive\": 1012, \"negative\": 13117.0, \"pending\": null, \"death\": 52.0, \"total\": 14129, \"dateChecked\": \"2020-03-18T20:00:00Z\", \"positive_diff\": 108.0, \"negative_diff\": 1535.0, \"death_diff\": 4.0, \"total_10\": 1412.9, \"daily_positive\": 108.0}, {\"state\": \"WA\", \"date\": \"2020-03-17T00:00:00\", \"positive\": 904, \"negative\": 11582.0, \"pending\": null, \"death\": 48.0, \"total\": 12486, \"dateChecked\": \"2020-03-17T20:00:00Z\", \"positive_diff\": 135.0, \"negative_diff\": 2131.0, \"death_diff\": 6.0, \"total_10\": 1248.6, \"daily_positive\": 135.0}, {\"state\": \"WA\", \"date\": \"2020-03-16T00:00:00\", \"positive\": 769, \"negative\": 9451.0, \"pending\": null, \"death\": 42.0, \"total\": 10220, \"dateChecked\": \"2020-03-16T20:00:00Z\", \"positive_diff\": 127.0, \"negative_diff\": 2329.0, \"death_diff\": 2.0, \"total_10\": 1022.0, \"daily_positive\": 127.0}, {\"state\": \"WA\", \"date\": \"2020-03-15T00:00:00\", \"positive\": 642, \"negative\": 7122.0, \"pending\": null, \"death\": 40.0, \"total\": 7764, \"dateChecked\": \"2020-03-15T20:00:00Z\", \"positive_diff\": 74.0, \"negative_diff\": 1121.0, \"death_diff\": 3.0, \"total_10\": 776.4, \"daily_positive\": 74.0}, {\"state\": \"WA\", \"date\": \"2020-03-14T00:00:00\", \"positive\": 568, \"negative\": 6001.0, \"pending\": null, \"death\": 37.0, \"total\": 6569, \"dateChecked\": \"2020-03-14T20:00:00Z\", \"positive_diff\": 111.0, \"negative_diff\": 1651.0, \"death_diff\": 6.0, \"total_10\": 656.9, \"daily_positive\": 111.0}, {\"state\": \"WA\", \"date\": \"2020-03-13T00:00:00\", \"positive\": 457, \"negative\": 4350.0, \"pending\": null, \"death\": 31.0, \"total\": 4807, \"dateChecked\": \"2020-03-13T20:00:00Z\", \"positive_diff\": 120.0, \"negative_diff\": 1313.0, \"death_diff\": 2.0, \"total_10\": 480.7, \"daily_positive\": 120.0}, {\"state\": \"WA\", \"date\": \"2020-03-12T00:00:00\", \"positive\": 337, \"negative\": 3037.0, \"pending\": null, \"death\": 29.0, \"total\": 3403, \"dateChecked\": \"2020-03-12T20:00:00Z\", \"positive_diff\": 70.0, \"negative_diff\": 862.0, \"death_diff\": 5.0, \"total_10\": 340.3, \"daily_positive\": 70.0}, {\"state\": \"WA\", \"date\": \"2020-03-11T00:00:00\", \"positive\": 267, \"negative\": 2175.0, \"pending\": null, \"death\": 24.0, \"total\": 2466, \"dateChecked\": \"2020-03-11T20:00:00Z\", \"positive_diff\": 105.0, \"negative_diff\": 1065.0, \"death_diff\": null, \"total_10\": 246.6, \"daily_positive\": 105.0}, {\"state\": \"WA\", \"date\": \"2020-03-10T00:00:00\", \"positive\": 162, \"negative\": 1110.0, \"pending\": null, \"death\": null, \"total\": 1272, \"dateChecked\": \"2020-03-10T20:00:00Z\", \"positive_diff\": 26.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 127.2, \"daily_positive\": 26.0}, {\"state\": \"WA\", \"date\": \"2020-03-09T00:00:00\", \"positive\": 136, \"negative\": 1110.0, \"pending\": null, \"death\": null, \"total\": 1246, \"dateChecked\": \"2020-03-09T20:00:00Z\", \"positive_diff\": 34.0, \"negative_diff\": 470.0, \"death_diff\": null, \"total_10\": 124.6, \"daily_positive\": 34.0}, {\"state\": \"WA\", \"date\": \"2020-03-08T00:00:00\", \"positive\": 102, \"negative\": 640.0, \"pending\": 60.0, \"death\": null, \"total\": 802, \"dateChecked\": \"2020-03-08T21:00:00Z\", \"positive_diff\": 0.0, \"negative_diff\": 270.0, \"death_diff\": null, \"total_10\": 80.2, \"daily_positive\": 0.0}, {\"state\": \"WA\", \"date\": \"2020-03-07T00:00:00\", \"positive\": 102, \"negative\": 370.0, \"pending\": 66.0, \"death\": null, \"total\": 538, \"dateChecked\": \"2020-03-07T21:00:00Z\", \"positive_diff\": 23.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 53.8, \"daily_positive\": 23.0}, {\"state\": \"WA\", \"date\": \"2020-03-06T00:00:00\", \"positive\": 79, \"negative\": 370.0, \"pending\": null, \"death\": null, \"total\": 449, \"dateChecked\": \"2020-03-06T21:00:00Z\", \"positive_diff\": 9.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 44.9, \"daily_positive\": 9.0}, {\"state\": \"WA\", \"date\": \"2020-03-05T00:00:00\", \"positive\": 70, \"negative\": null, \"pending\": null, \"death\": null, \"total\": 70, \"dateChecked\": \"2020-03-05T21:00:00Z\", \"positive_diff\": 31.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 7.0, \"daily_positive\": 31.0}, {\"state\": \"WA\", \"date\": \"2020-03-04T00:00:00\", \"positive\": 39, \"negative\": null, \"pending\": null, \"death\": null, \"total\": 39, \"dateChecked\": \"2020-03-04T21:00:00Z\", \"positive_diff\": null, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 3.9, \"daily_positive\": null}], \"data-5524f3d9a011a4455f9aef2d5f2b332f\": [{\"state\": \"CA\", \"date\": \"2020-03-19T00:00:00\", \"positive\": 924, \"negative\": 8787.0, \"pending\": null, \"death\": 18.0, \"total\": 9711, \"dateChecked\": \"2020-03-19T20:00:00Z\", \"positive_diff\": 313.0, \"negative_diff\": 806.0, \"death_diff\": 5.0, \"total_10\": 971.1, \"daily_positive\": 313.0}, {\"state\": \"CA\", \"date\": \"2020-03-18T00:00:00\", \"positive\": 611, \"negative\": 7981.0, \"pending\": null, \"death\": 13.0, \"total\": 8592, \"dateChecked\": \"2020-03-18T20:00:00Z\", \"positive_diff\": 128.0, \"negative_diff\": 0.0, \"death_diff\": 2.0, \"total_10\": 859.2, \"daily_positive\": 128.0}, {\"state\": \"CA\", \"date\": \"2020-03-17T00:00:00\", \"positive\": 483, \"negative\": 7981.0, \"pending\": null, \"death\": 11.0, \"total\": 8407, \"dateChecked\": \"2020-03-17T20:00:00Z\", \"positive_diff\": 148.0, \"negative_diff\": 0.0, \"death_diff\": 5.0, \"total_10\": 840.7, \"daily_positive\": 148.0}, {\"state\": \"CA\", \"date\": \"2020-03-16T00:00:00\", \"positive\": 335, \"negative\": 7981.0, \"pending\": null, \"death\": 6.0, \"total\": 8316, \"dateChecked\": \"2020-03-16T20:00:00Z\", \"positive_diff\": 42.0, \"negative_diff\": 7065.0, \"death_diff\": 1.0, \"total_10\": 831.6, \"daily_positive\": 42.0}, {\"state\": \"CA\", \"date\": \"2020-03-15T00:00:00\", \"positive\": 293, \"negative\": 916.0, \"pending\": null, \"death\": 5.0, \"total\": 1209, \"dateChecked\": \"2020-03-15T20:00:00Z\", \"positive_diff\": 41.0, \"negative_diff\": 0.0, \"death_diff\": 0.0, \"total_10\": 120.9, \"daily_positive\": 41.0}, {\"state\": \"CA\", \"date\": \"2020-03-14T00:00:00\", \"positive\": 252, \"negative\": 916.0, \"pending\": null, \"death\": 5.0, \"total\": 1168, \"dateChecked\": \"2020-03-14T20:00:00Z\", \"positive_diff\": 50.0, \"negative_diff\": 0.0, \"death_diff\": 1.0, \"total_10\": 116.8, \"daily_positive\": 50.0}, {\"state\": \"CA\", \"date\": \"2020-03-13T00:00:00\", \"positive\": 202, \"negative\": 916.0, \"pending\": null, \"death\": 4.0, \"total\": 1118, \"dateChecked\": \"2020-03-13T20:00:00Z\", \"positive_diff\": 0.0, \"negative_diff\": 0.0, \"death_diff\": 0.0, \"total_10\": 111.8, \"daily_positive\": 0.0}, {\"state\": \"CA\", \"date\": \"2020-03-12T00:00:00\", \"positive\": 202, \"negative\": 916.0, \"pending\": null, \"death\": 4.0, \"total\": 1118, \"dateChecked\": \"2020-03-12T20:00:00Z\", \"positive_diff\": 45.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 111.8, \"daily_positive\": 45.0}, {\"state\": \"CA\", \"date\": \"2020-03-11T00:00:00\", \"positive\": 157, \"negative\": 916.0, \"pending\": null, \"death\": null, \"total\": 1073, \"dateChecked\": \"2020-03-11T20:00:00Z\", \"positive_diff\": 24.0, \"negative_diff\": 226.0, \"death_diff\": null, \"total_10\": 107.3, \"daily_positive\": 24.0}, {\"state\": \"CA\", \"date\": \"2020-03-10T00:00:00\", \"positive\": 133, \"negative\": 690.0, \"pending\": null, \"death\": null, \"total\": 823, \"dateChecked\": \"2020-03-10T20:00:00Z\", \"positive_diff\": 19.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 82.3, \"daily_positive\": 19.0}, {\"state\": \"CA\", \"date\": \"2020-03-09T00:00:00\", \"positive\": 114, \"negative\": 690.0, \"pending\": null, \"death\": null, \"total\": 804, \"dateChecked\": \"2020-03-09T20:00:00Z\", \"positive_diff\": 26.0, \"negative_diff\": 228.0, \"death_diff\": null, \"total_10\": 80.4, \"daily_positive\": 26.0}, {\"state\": \"CA\", \"date\": \"2020-03-08T00:00:00\", \"positive\": 88, \"negative\": 462.0, \"pending\": null, \"death\": null, \"total\": 550, \"dateChecked\": \"2020-03-08T21:00:00Z\", \"positive_diff\": 19.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 55.0, \"daily_positive\": 19.0}, {\"state\": \"CA\", \"date\": \"2020-03-07T00:00:00\", \"positive\": 69, \"negative\": 462.0, \"pending\": null, \"death\": null, \"total\": 531, \"dateChecked\": \"2020-03-07T21:00:00Z\", \"positive_diff\": 9.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 53.1, \"daily_positive\": 9.0}, {\"state\": \"CA\", \"date\": \"2020-03-06T00:00:00\", \"positive\": 60, \"negative\": 462.0, \"pending\": null, \"death\": null, \"total\": 522, \"dateChecked\": \"2020-03-06T21:00:00Z\", \"positive_diff\": 7.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 52.2, \"daily_positive\": 7.0}, {\"state\": \"CA\", \"date\": \"2020-03-05T00:00:00\", \"positive\": 53, \"negative\": 462.0, \"pending\": null, \"death\": null, \"total\": 515, \"dateChecked\": \"2020-03-05T21:00:00Z\", \"positive_diff\": 0.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 51.5, \"daily_positive\": 0.0}, {\"state\": \"CA\", \"date\": \"2020-03-04T00:00:00\", \"positive\": 53, \"negative\": 462.0, \"pending\": null, \"death\": null, \"total\": 515, \"dateChecked\": \"2020-03-04T21:00:00Z\", \"positive_diff\": null, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 51.5, \"daily_positive\": null}], \"data-294eebc48941097d786524a29c373ee4\": [{\"state\": \"NY\", \"date\": \"2020-03-19T00:00:00\", \"positive\": 4152, \"negative\": 18132.0, \"pending\": null, \"death\": 12.0, \"total\": 22284, \"dateChecked\": \"2020-03-19T20:00:00Z\", \"positive_diff\": 1770.0, \"negative_diff\": 5917.0, \"death_diff\": 0.0, \"total_10\": 2228.4, \"daily_positive\": 1770.0}, {\"state\": \"NY\", \"date\": \"2020-03-18T00:00:00\", \"positive\": 2382, \"negative\": 12215.0, \"pending\": null, \"death\": 12.0, \"total\": 14597, \"dateChecked\": \"2020-03-18T20:00:00Z\", \"positive_diff\": 682.0, \"negative_diff\": 6709.0, \"death_diff\": 5.0, \"total_10\": 1459.7, \"daily_positive\": 682.0}, {\"state\": \"NY\", \"date\": \"2020-03-17T00:00:00\", \"positive\": 1700, \"negative\": 5506.0, \"pending\": null, \"death\": 7.0, \"total\": 7206, \"dateChecked\": \"2020-03-17T20:00:00Z\", \"positive_diff\": 750.0, \"negative_diff\": 1184.0, \"death_diff\": 0.0, \"total_10\": 720.6, \"daily_positive\": 750.0}, {\"state\": \"NY\", \"date\": \"2020-03-16T00:00:00\", \"positive\": 950, \"negative\": 4322.0, \"pending\": null, \"death\": 7.0, \"total\": 5272, \"dateChecked\": \"2020-03-16T20:00:00Z\", \"positive_diff\": 221.0, \"negative_diff\": -221.0, \"death_diff\": 4.0, \"total_10\": 527.2, \"daily_positive\": 221.0}, {\"state\": \"NY\", \"date\": \"2020-03-15T00:00:00\", \"positive\": 729, \"negative\": 4543.0, \"pending\": null, \"death\": 3.0, \"total\": 5272, \"dateChecked\": \"2020-03-15T20:00:00Z\", \"positive_diff\": 205.0, \"negative_diff\": 1764.0, \"death_diff\": null, \"total_10\": 527.2, \"daily_positive\": 205.0}, {\"state\": \"NY\", \"date\": \"2020-03-14T00:00:00\", \"positive\": 524, \"negative\": 2779.0, \"pending\": null, \"death\": null, \"total\": 3303, \"dateChecked\": \"2020-03-14T20:00:00Z\", \"positive_diff\": 103.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 330.3, \"daily_positive\": 103.0}, {\"state\": \"NY\", \"date\": \"2020-03-13T00:00:00\", \"positive\": 421, \"negative\": 2779.0, \"pending\": null, \"death\": null, \"total\": 3200, \"dateChecked\": \"2020-03-13T20:00:00Z\", \"positive_diff\": 205.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 320.0, \"daily_positive\": 205.0}, {\"state\": \"NY\", \"date\": \"2020-03-12T00:00:00\", \"positive\": 216, \"negative\": null, \"pending\": null, \"death\": null, \"total\": 216, \"dateChecked\": \"2020-03-12T20:00:00Z\", \"positive_diff\": 0.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 21.6, \"daily_positive\": 0.0}, {\"state\": \"NY\", \"date\": \"2020-03-11T00:00:00\", \"positive\": 216, \"negative\": null, \"pending\": null, \"death\": null, \"total\": 216, \"dateChecked\": \"2020-03-11T20:00:00Z\", \"positive_diff\": 43.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 21.6, \"daily_positive\": 43.0}, {\"state\": \"NY\", \"date\": \"2020-03-10T00:00:00\", \"positive\": 173, \"negative\": 92.0, \"pending\": null, \"death\": null, \"total\": 265, \"dateChecked\": \"2020-03-10T20:00:00Z\", \"positive_diff\": 31.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 26.5, \"daily_positive\": 31.0}, {\"state\": \"NY\", \"date\": \"2020-03-09T00:00:00\", \"positive\": 142, \"negative\": 92.0, \"pending\": null, \"death\": null, \"total\": 234, \"dateChecked\": \"2020-03-09T20:00:00Z\", \"positive_diff\": 37.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 23.4, \"daily_positive\": 37.0}, {\"state\": \"NY\", \"date\": \"2020-03-08T00:00:00\", \"positive\": 105, \"negative\": 92.0, \"pending\": null, \"death\": null, \"total\": 197, \"dateChecked\": \"2020-03-08T21:00:00Z\", \"positive_diff\": 29.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 19.7, \"daily_positive\": 29.0}, {\"state\": \"NY\", \"date\": \"2020-03-07T00:00:00\", \"positive\": 76, \"negative\": 92.0, \"pending\": 236.0, \"death\": null, \"total\": 404, \"dateChecked\": \"2020-03-07T21:00:00Z\", \"positive_diff\": 43.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 40.4, \"daily_positive\": 43.0}, {\"state\": \"NY\", \"date\": \"2020-03-06T00:00:00\", \"positive\": 33, \"negative\": 92.0, \"pending\": 236.0, \"death\": null, \"total\": 361, \"dateChecked\": \"2020-03-06T21:00:00Z\", \"positive_diff\": 11.0, \"negative_diff\": 16.0, \"death_diff\": null, \"total_10\": 36.1, \"daily_positive\": 11.0}, {\"state\": \"NY\", \"date\": \"2020-03-05T00:00:00\", \"positive\": 22, \"negative\": 76.0, \"pending\": 24.0, \"death\": null, \"total\": 122, \"dateChecked\": \"2020-03-05T21:00:00Z\", \"positive_diff\": 16.0, \"negative_diff\": 28.0, \"death_diff\": null, \"total_10\": 12.2, \"daily_positive\": 16.0}, {\"state\": \"NY\", \"date\": \"2020-03-04T00:00:00\", \"positive\": 6, \"negative\": 48.0, \"pending\": 24.0, \"death\": null, \"total\": 78, \"dateChecked\": \"2020-03-04T21:00:00Z\", \"positive_diff\": null, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 7.8, \"daily_positive\": null}]}}, {\"mode\": \"vega-lite\"});\n",
"</script>"
],
"text/plain": [
"alt.HConcatChart(...)"
]
},
"execution_count": 278,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# produce the charts for a few states\n",
"\n",
"charts=[]\n",
"for state in ['WA', 'CA', 'NY']: \n",
" state_df = tdf_diff[tdf_diff['state'] == state]\n",
"\n",
" state_df['daily_positive'] = state_df['positive'][::-1].diff()\n",
"\n",
" state_df['total_10'] = state_df['total']/10.\n",
"\n",
" base = alt.Chart(state_df, title=state).encode(alt.X('date', axis=alt.Axis(title='Date'))).properties(width=250, height=150)\n",
" dailies = base.mark_bar(size=10).encode(alt.Y('daily_positive', axis=alt.Axis(title='Daily positive')))\n",
"\n",
" totals = base.mark_line(color='red').encode(alt.Y('total_10', axis=alt.Axis(title='Total/10'))) \n",
" positives = totals.mark_line(color='orange').encode(alt.Y('positive', axis=alt.Axis(title='Positive')))\n",
" cumulative = totals + positives\n",
"\n",
" charts.append(alt.layer(dailies, cumulative).resolve_scale(y='independent'))\n",
"\n",
"\n",
"alt.hconcat(*charts)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}