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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"library(jsonlite)\n",
"library(ggplot2)\n",
"options(repr.plot.width=14, repr.plot.height=8)\n",
"library(data.table)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Look at the metadata"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"metadata_df <- fromJSON(\"../../data/covidtracking/states-metadata.json\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 6 × 9</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>state</th><th scope=col>covid19SiteOld</th><th scope=col>covid19Site</th><th scope=col>covid19SiteSecondary</th><th scope=col>twitter</th><th scope=col>pui</th><th scope=col>pum</th><th scope=col>notes</th><th scope=col>name</th></tr>\n",
"\t<tr><th scope=col><chr></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><lgl></th><th scope=col><chr></th><th scope=col><chr></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>AK</td><td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx </td><td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/monitoring.aspx </td><td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx </td><td>@Alaska_DHSS </td><td>All data </td><td>FALSE</td><td>Unclear if their reported number means \"persons tested\" or \"specimens tested.\" We count them as \"persons tested\" because the header indicates this is the case. Total tests are taken from the annotations on the charts on the page. Negatives are calculated as totals – positives. Negatives reported on site have decreased at various times, without explanation. Latest update time taken from [this page](http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx). </td><td>Alaska </td></tr>\n",
"\t<tr><td>AL</td><td>http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html </td><td>https://alpublichealth.maps.arcgis.com/apps/opsdashboard/index.html#/6d2771faa9da4a2786a509d82c8cf0f7 </td><td>NA </td><td>@alpublichealth</td><td>No data </td><td>FALSE</td><td>Last negative count from 3/16. Last update time taken from [main page](http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html). </td><td>Alabama </td></tr>\n",
"\t<tr><td>AR</td><td>https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus </td><td>https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus </td><td>NA </td><td>@adhpio </td><td>All data </td><td> TRUE</td><td>Pending = \"PUIs\" </td><td>Arkansas </td></tr>\n",
"\t<tr><td>AS</td><td>http://www.samoagovt.ws/2020/03/ministry-of-health-coronavirus-covid-19-update-14-march-2020/ </td><td>http://www.samoagovt.ws/category/latest-news/ </td><td>https://www.facebook.com/amsamgov/ </td><td>NA </td><td>No Data </td><td>FALSE</td><td>American Samoa: No data, no confirmed cases yet. </td><td>American Samoa</td></tr>\n",
"\t<tr><td>AZ</td><td>https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php#novel-coronavirus-home</td><td>https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php#novel-coronavirus-home</td><td>NA </td><td>@azdhs </td><td>All data </td><td>FALSE</td><td>Negative = “Ruled Out”. Negatives are from public labs only. Our total is slightly higher than the state’s site because we also add in the additional positives from private labs, listed in the second table. </td><td>Arizona </td></tr>\n",
"\t<tr><td>CA</td><td>https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx </td><td>https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/ </td><td>https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx</td><td>@CAPublicHealth</td><td>Only positives</td><td>FALSE</td><td>We report positives from the [LA Times](https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/), which is aggregated from county-level data and is ahead of the official California data site. When using LA Times data for positives, we do not add deaths to the positive count: they are already included. Previously we added them in because the California state site had not been including them in the positive count. Negative numbers are inferred from Totals - Positives, taken from the [latest press release](https://www.cdph.ca.gov/Programs/OPA/Pages/NR20-028.aspx). We are not reporting pending numbers until they are reported regularly, or from a dashboard. We assume 1 test=1 person. </td><td>California </td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 6 × 9\n",
"\\begin{tabular}{r|lllllllll}\n",
" state & covid19SiteOld & covid19Site & covid19SiteSecondary & twitter & pui & pum & notes & name\\\\\n",
" <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <lgl> & <chr> & <chr>\\\\\n",
"\\hline\n",
"\t AK & http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx & http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/monitoring.aspx & http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx & @Alaska\\_DHSS & All data & FALSE & Unclear if their reported number means \"persons tested\" or \"specimens tested.\" We count them as \"persons tested\" because the header indicates this is the case. Total tests are taken from the annotations on the charts on the page. Negatives are calculated as totals – positives. Negatives reported on site have decreased at various times, without explanation. Latest update time taken from {[}this page{]}(http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx). & Alaska \\\\\n",
"\t AL & http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html & https://alpublichealth.maps.arcgis.com/apps/opsdashboard/index.html\\#/6d2771faa9da4a2786a509d82c8cf0f7 & NA & @alpublichealth & No data & FALSE & Last negative count from 3/16. Last update time taken from {[}main page{]}(http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html). & Alabama \\\\\n",
"\t AR & https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus & https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus & NA & @adhpio & All data & TRUE & Pending = \"PUIs\" & Arkansas \\\\\n",
"\t AS & http://www.samoagovt.ws/2020/03/ministry-of-health-coronavirus-covid-19-update-14-march-2020/ & http://www.samoagovt.ws/category/latest-news/ & https://www.facebook.com/amsamgov/ & NA & No Data & FALSE & American Samoa: No data, no confirmed cases yet. & American Samoa\\\\\n",
"\t AZ & https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php\\#novel-coronavirus-home & https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php\\#novel-coronavirus-home & NA & @azdhs & All data & FALSE & Negative = “Ruled Out”. Negatives are from public labs only. Our total is slightly higher than the state’s site because we also add in the additional positives from private labs, listed in the second table. & Arizona \\\\\n",
"\t CA & https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx & https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/ & https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx & @CAPublicHealth & Only positives & FALSE & We report positives from the {[}LA Times{]}(https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/), which is aggregated from county-level data and is ahead of the official California data site. When using LA Times data for positives, we do not add deaths to the positive count: they are already included. Previously we added them in because the California state site had not been including them in the positive count. Negative numbers are inferred from Totals - Positives, taken from the {[}latest press release{]}(https://www.cdph.ca.gov/Programs/OPA/Pages/NR20-028.aspx). We are not reporting pending numbers until they are reported regularly, or from a dashboard. We assume 1 test=1 person. & California \\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 6 × 9\n",
"\n",
"| state <chr> | covid19SiteOld <chr> | covid19Site <chr> | covid19SiteSecondary <chr> | twitter <chr> | pui <chr> | pum <lgl> | notes <chr> | name <chr> |\n",
"|---|---|---|---|---|---|---|---|---|\n",
"| AK | http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx | http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/monitoring.aspx | http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx | @Alaska_DHSS | All data | FALSE | Unclear if their reported number means \"persons tested\" or \"specimens tested.\" We count them as \"persons tested\" because the header indicates this is the case. Total tests are taken from the annotations on the charts on the page. Negatives are calculated as totals – positives. Negatives reported on site have decreased at various times, without explanation. Latest update time taken from [this page](http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx). | Alaska |\n",
"| AL | http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html | https://alpublichealth.maps.arcgis.com/apps/opsdashboard/index.html#/6d2771faa9da4a2786a509d82c8cf0f7 | NA | @alpublichealth | No data | FALSE | Last negative count from 3/16. Last update time taken from [main page](http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html). | Alabama |\n",
"| AR | https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus | https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus | NA | @adhpio | All data | TRUE | Pending = \"PUIs\" | Arkansas |\n",
"| AS | http://www.samoagovt.ws/2020/03/ministry-of-health-coronavirus-covid-19-update-14-march-2020/ | http://www.samoagovt.ws/category/latest-news/ | https://www.facebook.com/amsamgov/ | NA | No Data | FALSE | American Samoa: No data, no confirmed cases yet. | American Samoa |\n",
"| AZ | https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php#novel-coronavirus-home | https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php#novel-coronavirus-home | NA | @azdhs | All data | FALSE | Negative = “Ruled Out”. Negatives are from public labs only. Our total is slightly higher than the state’s site because we also add in the additional positives from private labs, listed in the second table. | Arizona |\n",
"| CA | https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx | https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/ | https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx | @CAPublicHealth | Only positives | FALSE | We report positives from the [LA Times](https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/), which is aggregated from county-level data and is ahead of the official California data site. When using LA Times data for positives, we do not add deaths to the positive count: they are already included. Previously we added them in because the California state site had not been including them in the positive count. Negative numbers are inferred from Totals - Positives, taken from the [latest press release](https://www.cdph.ca.gov/Programs/OPA/Pages/NR20-028.aspx). We are not reporting pending numbers until they are reported regularly, or from a dashboard. We assume 1 test=1 person. | California |\n",
"\n"
],
"text/plain": [
" state\n",
"1 AK \n",
"2 AL \n",
"3 AR \n",
"4 AS \n",
"5 AZ \n",
"6 CA \n",
" covid19SiteOld \n",
"1 http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx \n",
"2 http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html \n",
"3 https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus \n",
"4 http://www.samoagovt.ws/2020/03/ministry-of-health-coronavirus-covid-19-update-14-march-2020/ \n",
"5 https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php#novel-coronavirus-home\n",
"6 https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx \n",
" covid19Site \n",
"1 http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/monitoring.aspx \n",
"2 https://alpublichealth.maps.arcgis.com/apps/opsdashboard/index.html#/6d2771faa9da4a2786a509d82c8cf0f7 \n",
"3 https://www.healthy.arkansas.gov/programs-services/topics/novel-coronavirus \n",
"4 http://www.samoagovt.ws/category/latest-news/ \n",
"5 https://www.azdhs.gov/preparedness/epidemiology-disease-control/infectious-disease-epidemiology/index.php#novel-coronavirus-home\n",
"6 https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/ \n",
" covid19SiteSecondary \n",
"1 http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx \n",
"2 NA \n",
"3 NA \n",
"4 https://www.facebook.com/amsamgov/ \n",
"5 NA \n",
"6 https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Immunization/ncov2019.aspx\n",
" twitter pui pum \n",
"1 @Alaska_DHSS All data FALSE\n",
"2 @alpublichealth No data FALSE\n",
"3 @adhpio All data TRUE\n",
"4 NA No Data FALSE\n",
"5 @azdhs All data FALSE\n",
"6 @CAPublicHealth Only positives FALSE\n",
" notes \n",
"1 Unclear if their reported number means \"persons tested\" or \"specimens tested.\" We count them as \"persons tested\" because the header indicates this is the case. Total tests are taken from the annotations on the charts on the page. Negatives are calculated as totals – positives. Negatives reported on site have decreased at various times, without explanation. Latest update time taken from [this page](http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-19/default.aspx). \n",
"2 Last negative count from 3/16. Last update time taken from [main page](http://www.alabamapublichealth.gov/infectiousdiseases/2019-coronavirus.html). \n",
"3 Pending = \"PUIs\" \n",
"4 American Samoa: No data, no confirmed cases yet. \n",
"5 Negative = “Ruled Out”. Negatives are from public labs only. Our total is slightly higher than the state’s site because we also add in the additional positives from private labs, listed in the second table. \n",
"6 We report positives from the [LA Times](https://www.latimes.com/projects/california-coronavirus-cases-tracking-outbreak/), which is aggregated from county-level data and is ahead of the official California data site. When using LA Times data for positives, we do not add deaths to the positive count: they are already included. Previously we added them in because the California state site had not been including them in the positive count. Negative numbers are inferred from Totals - Positives, taken from the [latest press release](https://www.cdph.ca.gov/Programs/OPA/Pages/NR20-028.aspx). We are not reporting pending numbers until they are reported regularly, or from a dashboard. We assume 1 test=1 person. \n",
" name \n",
"1 Alaska \n",
"2 Alabama \n",
"3 Arkansas \n",
"4 American Samoa\n",
"5 Arizona \n",
"6 California "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"head(metadata_df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Look at the data"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"data_df <- fromJSON(\"../../data/covidtracking/states-daily.json\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 6 × 9</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>date</th><th scope=col>state</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>pending</th><th scope=col>hospitalized</th><th scope=col>death</th><th scope=col>total</th><th scope=col>dateChecked</th></tr>\n",
"\t<tr><th scope=col><int></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><int></th><th scope=col><int></th><th scope=col><lgl></th><th scope=col><int></th><th scope=col><int></th><th scope=col><chr></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>20200320</td><td>AK</td><td> 12</td><td> 686</td><td> NA</td><td>NA</td><td>NA</td><td> 698</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>20200320</td><td>AL</td><td> 81</td><td> 28</td><td> NA</td><td>NA</td><td> 0</td><td> 109</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>20200320</td><td>AR</td><td> 96</td><td> 351</td><td>203</td><td>NA</td><td>NA</td><td> 650</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>20200320</td><td>AS</td><td> 0</td><td> NA</td><td> NA</td><td>NA</td><td> 0</td><td> 0</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>20200320</td><td>AZ</td><td> 65</td><td> 211</td><td>101</td><td>NA</td><td> 0</td><td> 377</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>20200320</td><td>CA</td><td>1063</td><td>10424</td><td> NA</td><td>NA</td><td>20</td><td>11487</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 6 × 9\n",
"\\begin{tabular}{r|lllllllll}\n",
" date & state & positive & negative & pending & hospitalized & death & total & dateChecked\\\\\n",
" <int> & <chr> & <int> & <int> & <int> & <lgl> & <int> & <int> & <chr>\\\\\n",
"\\hline\n",
"\t 20200320 & AK & 12 & 686 & NA & NA & NA & 698 & 2020-03-20T20:00:00Z\\\\\n",
"\t 20200320 & AL & 81 & 28 & NA & NA & 0 & 109 & 2020-03-20T20:00:00Z\\\\\n",
"\t 20200320 & AR & 96 & 351 & 203 & NA & NA & 650 & 2020-03-20T20:00:00Z\\\\\n",
"\t 20200320 & AS & 0 & NA & NA & NA & 0 & 0 & 2020-03-20T20:00:00Z\\\\\n",
"\t 20200320 & AZ & 65 & 211 & 101 & NA & 0 & 377 & 2020-03-20T20:00:00Z\\\\\n",
"\t 20200320 & CA & 1063 & 10424 & NA & NA & 20 & 11487 & 2020-03-20T20:00:00Z\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 6 × 9\n",
"\n",
"| date <int> | state <chr> | positive <int> | negative <int> | pending <int> | hospitalized <lgl> | death <int> | total <int> | dateChecked <chr> |\n",
"|---|---|---|---|---|---|---|---|---|\n",
"| 20200320 | AK | 12 | 686 | NA | NA | NA | 698 | 2020-03-20T20:00:00Z |\n",
"| 20200320 | AL | 81 | 28 | NA | NA | 0 | 109 | 2020-03-20T20:00:00Z |\n",
"| 20200320 | AR | 96 | 351 | 203 | NA | NA | 650 | 2020-03-20T20:00:00Z |\n",
"| 20200320 | AS | 0 | NA | NA | NA | 0 | 0 | 2020-03-20T20:00:00Z |\n",
"| 20200320 | AZ | 65 | 211 | 101 | NA | 0 | 377 | 2020-03-20T20:00:00Z |\n",
"| 20200320 | CA | 1063 | 10424 | NA | NA | 20 | 11487 | 2020-03-20T20:00:00Z |\n",
"\n"
],
"text/plain": [
" date state positive negative pending hospitalized death total\n",
"1 20200320 AK 12 686 NA NA NA 698\n",
"2 20200320 AL 81 28 NA NA 0 109\n",
"3 20200320 AR 96 351 203 NA NA 650\n",
"4 20200320 AS 0 NA NA NA 0 0\n",
"5 20200320 AZ 65 211 101 NA 0 377\n",
"6 20200320 CA 1063 10424 NA NA 20 11487\n",
" dateChecked \n",
"1 2020-03-20T20:00:00Z\n",
"2 2020-03-20T20:00:00Z\n",
"3 2020-03-20T20:00:00Z\n",
"4 2020-03-20T20:00:00Z\n",
"5 2020-03-20T20:00:00Z\n",
"6 2020-03-20T20:00:00Z"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"head(data_df)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"data_df$date <- as.Date(paste(data_df$date), format=\"%Y%m%d\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 6 × 9</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>date</th><th scope=col>state</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>pending</th><th scope=col>hospitalized</th><th scope=col>death</th><th scope=col>total</th><th scope=col>dateChecked</th></tr>\n",
"\t<tr><th scope=col><date></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><int></th><th scope=col><int></th><th scope=col><lgl></th><th scope=col><int></th><th scope=col><int></th><th scope=col><chr></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>2020-03-20</td><td>AK</td><td> 12</td><td> 686</td><td> NA</td><td>NA</td><td>NA</td><td> 698</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AL</td><td> 81</td><td> 28</td><td> NA</td><td>NA</td><td> 0</td><td> 109</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AR</td><td> 96</td><td> 351</td><td>203</td><td>NA</td><td>NA</td><td> 650</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AS</td><td> 0</td><td> NA</td><td> NA</td><td>NA</td><td> 0</td><td> 0</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AZ</td><td> 65</td><td> 211</td><td>101</td><td>NA</td><td> 0</td><td> 377</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>CA</td><td>1063</td><td>10424</td><td> NA</td><td>NA</td><td>20</td><td>11487</td><td>2020-03-20T20:00:00Z</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 6 × 9\n",
"\\begin{tabular}{r|lllllllll}\n",
" date & state & positive & negative & pending & hospitalized & death & total & dateChecked\\\\\n",
" <date> & <chr> & <int> & <int> & <int> & <lgl> & <int> & <int> & <chr>\\\\\n",
"\\hline\n",
"\t 2020-03-20 & AK & 12 & 686 & NA & NA & NA & 698 & 2020-03-20T20:00:00Z\\\\\n",
"\t 2020-03-20 & AL & 81 & 28 & NA & NA & 0 & 109 & 2020-03-20T20:00:00Z\\\\\n",
"\t 2020-03-20 & AR & 96 & 351 & 203 & NA & NA & 650 & 2020-03-20T20:00:00Z\\\\\n",
"\t 2020-03-20 & AS & 0 & NA & NA & NA & 0 & 0 & 2020-03-20T20:00:00Z\\\\\n",
"\t 2020-03-20 & AZ & 65 & 211 & 101 & NA & 0 & 377 & 2020-03-20T20:00:00Z\\\\\n",
"\t 2020-03-20 & CA & 1063 & 10424 & NA & NA & 20 & 11487 & 2020-03-20T20:00:00Z\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 6 × 9\n",
"\n",
"| date <date> | state <chr> | positive <int> | negative <int> | pending <int> | hospitalized <lgl> | death <int> | total <int> | dateChecked <chr> |\n",
"|---|---|---|---|---|---|---|---|---|\n",
"| 2020-03-20 | AK | 12 | 686 | NA | NA | NA | 698 | 2020-03-20T20:00:00Z |\n",
"| 2020-03-20 | AL | 81 | 28 | NA | NA | 0 | 109 | 2020-03-20T20:00:00Z |\n",
"| 2020-03-20 | AR | 96 | 351 | 203 | NA | NA | 650 | 2020-03-20T20:00:00Z |\n",
"| 2020-03-20 | AS | 0 | NA | NA | NA | 0 | 0 | 2020-03-20T20:00:00Z |\n",
"| 2020-03-20 | AZ | 65 | 211 | 101 | NA | 0 | 377 | 2020-03-20T20:00:00Z |\n",
"| 2020-03-20 | CA | 1063 | 10424 | NA | NA | 20 | 11487 | 2020-03-20T20:00:00Z |\n",
"\n"
],
"text/plain": [
" date state positive negative pending hospitalized death total\n",
"1 2020-03-20 AK 12 686 NA NA NA 698\n",
"2 2020-03-20 AL 81 28 NA NA 0 109\n",
"3 2020-03-20 AR 96 351 203 NA NA 650\n",
"4 2020-03-20 AS 0 NA NA NA 0 0\n",
"5 2020-03-20 AZ 65 211 101 NA 0 377\n",
"6 2020-03-20 CA 1063 10424 NA NA 20 11487\n",
" dateChecked \n",
"1 2020-03-20T20:00:00Z\n",
"2 2020-03-20T20:00:00Z\n",
"3 2020-03-20T20:00:00Z\n",
"4 2020-03-20T20:00:00Z\n",
"5 2020-03-20T20:00:00Z\n",
"6 2020-03-20T20:00:00Z"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"head(data_df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Daily counts and totals"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.table: 6 × 9</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>date</th><th scope=col>state</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>pending</th><th scope=col>hospitalized</th><th scope=col>death</th><th scope=col>total</th><th scope=col>dateChecked</th></tr>\n",
"\t<tr><th scope=col><date></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><int></th><th scope=col><int></th><th scope=col><lgl></th><th scope=col><int></th><th scope=col><int></th><th scope=col><chr></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>2020-03-06</td><td>AK</td><td>0</td><td> 8</td><td> 1</td><td>NA</td><td>NA</td><td> 9</td><td>2020-03-06T21:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-07</td><td>AK</td><td>0</td><td>12</td><td> 2</td><td>NA</td><td>NA</td><td>14</td><td>2020-03-07T21:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-08</td><td>AK</td><td>0</td><td>14</td><td> 6</td><td>NA</td><td>NA</td><td>20</td><td>2020-03-08T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-09</td><td>AK</td><td>0</td><td>23</td><td> 9</td><td>NA</td><td>NA</td><td>32</td><td>2020-03-09T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-10</td><td>AK</td><td>0</td><td>23</td><td> 9</td><td>NA</td><td>NA</td><td>32</td><td>2020-03-10T20:00:00Z</td></tr>\n",
"\t<tr><td>2020-03-11</td><td>AK</td><td>0</td><td>46</td><td>14</td><td>NA</td><td>NA</td><td>60</td><td>2020-03-11T20:00:00Z</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.table: 6 × 9\n",
"\\begin{tabular}{r|lllllllll}\n",
" date & state & positive & negative & pending & hospitalized & death & total & dateChecked\\\\\n",
" <date> & <chr> & <int> & <int> & <int> & <lgl> & <int> & <int> & <chr>\\\\\n",
"\\hline\n",
"\t 2020-03-06 & AK & 0 & 8 & 1 & NA & NA & 9 & 2020-03-06T21:00:00Z\\\\\n",
"\t 2020-03-07 & AK & 0 & 12 & 2 & NA & NA & 14 & 2020-03-07T21:00:00Z\\\\\n",
"\t 2020-03-08 & AK & 0 & 14 & 6 & NA & NA & 20 & 2020-03-08T20:00:00Z\\\\\n",
"\t 2020-03-09 & AK & 0 & 23 & 9 & NA & NA & 32 & 2020-03-09T20:00:00Z\\\\\n",
"\t 2020-03-10 & AK & 0 & 23 & 9 & NA & NA & 32 & 2020-03-10T20:00:00Z\\\\\n",
"\t 2020-03-11 & AK & 0 & 46 & 14 & NA & NA & 60 & 2020-03-11T20:00:00Z\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.table: 6 × 9\n",
"\n",
"| date <date> | state <chr> | positive <int> | negative <int> | pending <int> | hospitalized <lgl> | death <int> | total <int> | dateChecked <chr> |\n",
"|---|---|---|---|---|---|---|---|---|\n",
"| 2020-03-06 | AK | 0 | 8 | 1 | NA | NA | 9 | 2020-03-06T21:00:00Z |\n",
"| 2020-03-07 | AK | 0 | 12 | 2 | NA | NA | 14 | 2020-03-07T21:00:00Z |\n",
"| 2020-03-08 | AK | 0 | 14 | 6 | NA | NA | 20 | 2020-03-08T20:00:00Z |\n",
"| 2020-03-09 | AK | 0 | 23 | 9 | NA | NA | 32 | 2020-03-09T20:00:00Z |\n",
"| 2020-03-10 | AK | 0 | 23 | 9 | NA | NA | 32 | 2020-03-10T20:00:00Z |\n",
"| 2020-03-11 | AK | 0 | 46 | 14 | NA | NA | 60 | 2020-03-11T20:00:00Z |\n",
"\n"
],
"text/plain": [
" date state positive negative pending hospitalized death total\n",
"1 2020-03-06 AK 0 8 1 NA NA 9 \n",
"2 2020-03-07 AK 0 12 2 NA NA 14 \n",
"3 2020-03-08 AK 0 14 6 NA NA 20 \n",
"4 2020-03-09 AK 0 23 9 NA NA 32 \n",
"5 2020-03-10 AK 0 23 9 NA NA 32 \n",
"6 2020-03-11 AK 0 46 14 NA NA 60 \n",
" dateChecked \n",
"1 2020-03-06T21:00:00Z\n",
"2 2020-03-07T21:00:00Z\n",
"3 2020-03-08T20:00:00Z\n",
"4 2020-03-09T20:00:00Z\n",
"5 2020-03-10T20:00:00Z\n",
"6 2020-03-11T20:00:00Z"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# compute daily differences\n",
"data_df <- data.table(data_df)\n",
"tdf <- data.table(data_df)\n",
"setkey(tdf, state, date)\n",
"head(tdf)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"tdf[, diff_positive := positive - shift(positive), by = .(state)]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.table: 17 × 10</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>date</th><th scope=col>state</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>pending</th><th scope=col>hospitalized</th><th scope=col>death</th><th scope=col>total</th><th scope=col>dateChecked</th><th scope=col>diff_positive</th></tr>\n",
"\t<tr><th scope=col><date></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><int></th><th scope=col><int></th><th scope=col><lgl></th><th scope=col><int></th><th scope=col><int></th><th scope=col><chr></th><th scope=col><int></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>2020-03-04</td><td>WA</td><td> 39</td><td> NA</td><td>NA</td><td>NA</td><td>NA</td><td> 39</td><td>2020-03-04T21:00:00Z</td><td> NA</td></tr>\n",
"\t<tr><td>2020-03-05</td><td>WA</td><td> 70</td><td> NA</td><td>NA</td><td>NA</td><td>NA</td><td> 70</td><td>2020-03-05T21:00:00Z</td><td> 31</td></tr>\n",
"\t<tr><td>2020-03-06</td><td>WA</td><td> 79</td><td> 370</td><td>NA</td><td>NA</td><td>NA</td><td> 449</td><td>2020-03-06T21:00:00Z</td><td> 9</td></tr>\n",
"\t<tr><td>2020-03-07</td><td>WA</td><td> 102</td><td> 370</td><td>66</td><td>NA</td><td>NA</td><td> 538</td><td>2020-03-07T21:00:00Z</td><td> 23</td></tr>\n",
"\t<tr><td>2020-03-08</td><td>WA</td><td> 102</td><td> 640</td><td>60</td><td>NA</td><td>NA</td><td> 802</td><td>2020-03-08T20:00:00Z</td><td> 0</td></tr>\n",
"\t<tr><td>2020-03-09</td><td>WA</td><td> 136</td><td> 1110</td><td>NA</td><td>NA</td><td>NA</td><td> 1246</td><td>2020-03-09T20:00:00Z</td><td> 34</td></tr>\n",
"\t<tr><td>2020-03-10</td><td>WA</td><td> 162</td><td> 1110</td><td>NA</td><td>NA</td><td>NA</td><td> 1272</td><td>2020-03-10T20:00:00Z</td><td> 26</td></tr>\n",
"\t<tr><td>2020-03-11</td><td>WA</td><td> 267</td><td> 2175</td><td>NA</td><td>NA</td><td>24</td><td> 2466</td><td>2020-03-11T20:00:00Z</td><td>105</td></tr>\n",
"\t<tr><td>2020-03-12</td><td>WA</td><td> 337</td><td> 3037</td><td>NA</td><td>NA</td><td>29</td><td> 3403</td><td>2020-03-12T20:00:00Z</td><td> 70</td></tr>\n",
"\t<tr><td>2020-03-13</td><td>WA</td><td> 457</td><td> 4350</td><td>NA</td><td>NA</td><td>31</td><td> 4807</td><td>2020-03-13T20:00:00Z</td><td>120</td></tr>\n",
"\t<tr><td>2020-03-14</td><td>WA</td><td> 568</td><td> 6001</td><td>NA</td><td>NA</td><td>37</td><td> 6569</td><td>2020-03-14T20:00:00Z</td><td>111</td></tr>\n",
"\t<tr><td>2020-03-15</td><td>WA</td><td> 642</td><td> 7122</td><td>NA</td><td>NA</td><td>40</td><td> 7764</td><td>2020-03-15T20:00:00Z</td><td> 74</td></tr>\n",
"\t<tr><td>2020-03-16</td><td>WA</td><td> 769</td><td> 9451</td><td>NA</td><td>NA</td><td>42</td><td>10220</td><td>2020-03-16T20:00:00Z</td><td>127</td></tr>\n",
"\t<tr><td>2020-03-17</td><td>WA</td><td> 904</td><td>11582</td><td>NA</td><td>NA</td><td>48</td><td>12486</td><td>2020-03-17T20:00:00Z</td><td>135</td></tr>\n",
"\t<tr><td>2020-03-18</td><td>WA</td><td>1012</td><td>13117</td><td>NA</td><td>NA</td><td>52</td><td>14129</td><td>2020-03-18T20:00:00Z</td><td>108</td></tr>\n",
"\t<tr><td>2020-03-19</td><td>WA</td><td>1187</td><td>15918</td><td>NA</td><td>NA</td><td>66</td><td>17105</td><td>2020-03-19T20:00:00Z</td><td>175</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>WA</td><td>1376</td><td>19336</td><td>NA</td><td>NA</td><td>74</td><td>20712</td><td>2020-03-20T20:00:00Z</td><td>189</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.table: 17 × 10\n",
"\\begin{tabular}{r|llllllllll}\n",
" date & state & positive & negative & pending & hospitalized & death & total & dateChecked & diff\\_positive\\\\\n",
" <date> & <chr> & <int> & <int> & <int> & <lgl> & <int> & <int> & <chr> & <int>\\\\\n",
"\\hline\n",
"\t 2020-03-04 & WA & 39 & NA & NA & NA & NA & 39 & 2020-03-04T21:00:00Z & NA\\\\\n",
"\t 2020-03-05 & WA & 70 & NA & NA & NA & NA & 70 & 2020-03-05T21:00:00Z & 31\\\\\n",
"\t 2020-03-06 & WA & 79 & 370 & NA & NA & NA & 449 & 2020-03-06T21:00:00Z & 9\\\\\n",
"\t 2020-03-07 & WA & 102 & 370 & 66 & NA & NA & 538 & 2020-03-07T21:00:00Z & 23\\\\\n",
"\t 2020-03-08 & WA & 102 & 640 & 60 & NA & NA & 802 & 2020-03-08T20:00:00Z & 0\\\\\n",
"\t 2020-03-09 & WA & 136 & 1110 & NA & NA & NA & 1246 & 2020-03-09T20:00:00Z & 34\\\\\n",
"\t 2020-03-10 & WA & 162 & 1110 & NA & NA & NA & 1272 & 2020-03-10T20:00:00Z & 26\\\\\n",
"\t 2020-03-11 & WA & 267 & 2175 & NA & NA & 24 & 2466 & 2020-03-11T20:00:00Z & 105\\\\\n",
"\t 2020-03-12 & WA & 337 & 3037 & NA & NA & 29 & 3403 & 2020-03-12T20:00:00Z & 70\\\\\n",
"\t 2020-03-13 & WA & 457 & 4350 & NA & NA & 31 & 4807 & 2020-03-13T20:00:00Z & 120\\\\\n",
"\t 2020-03-14 & WA & 568 & 6001 & NA & NA & 37 & 6569 & 2020-03-14T20:00:00Z & 111\\\\\n",
"\t 2020-03-15 & WA & 642 & 7122 & NA & NA & 40 & 7764 & 2020-03-15T20:00:00Z & 74\\\\\n",
"\t 2020-03-16 & WA & 769 & 9451 & NA & NA & 42 & 10220 & 2020-03-16T20:00:00Z & 127\\\\\n",
"\t 2020-03-17 & WA & 904 & 11582 & NA & NA & 48 & 12486 & 2020-03-17T20:00:00Z & 135\\\\\n",
"\t 2020-03-18 & WA & 1012 & 13117 & NA & NA & 52 & 14129 & 2020-03-18T20:00:00Z & 108\\\\\n",
"\t 2020-03-19 & WA & 1187 & 15918 & NA & NA & 66 & 17105 & 2020-03-19T20:00:00Z & 175\\\\\n",
"\t 2020-03-20 & WA & 1376 & 19336 & NA & NA & 74 & 20712 & 2020-03-20T20:00:00Z & 189\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.table: 17 × 10\n",
"\n",
"| date <date> | state <chr> | positive <int> | negative <int> | pending <int> | hospitalized <lgl> | death <int> | total <int> | dateChecked <chr> | diff_positive <int> |\n",
"|---|---|---|---|---|---|---|---|---|---|\n",
"| 2020-03-04 | WA | 39 | NA | NA | NA | NA | 39 | 2020-03-04T21:00:00Z | NA |\n",
"| 2020-03-05 | WA | 70 | NA | NA | NA | NA | 70 | 2020-03-05T21:00:00Z | 31 |\n",
"| 2020-03-06 | WA | 79 | 370 | NA | NA | NA | 449 | 2020-03-06T21:00:00Z | 9 |\n",
"| 2020-03-07 | WA | 102 | 370 | 66 | NA | NA | 538 | 2020-03-07T21:00:00Z | 23 |\n",
"| 2020-03-08 | WA | 102 | 640 | 60 | NA | NA | 802 | 2020-03-08T20:00:00Z | 0 |\n",
"| 2020-03-09 | WA | 136 | 1110 | NA | NA | NA | 1246 | 2020-03-09T20:00:00Z | 34 |\n",
"| 2020-03-10 | WA | 162 | 1110 | NA | NA | NA | 1272 | 2020-03-10T20:00:00Z | 26 |\n",
"| 2020-03-11 | WA | 267 | 2175 | NA | NA | 24 | 2466 | 2020-03-11T20:00:00Z | 105 |\n",
"| 2020-03-12 | WA | 337 | 3037 | NA | NA | 29 | 3403 | 2020-03-12T20:00:00Z | 70 |\n",
"| 2020-03-13 | WA | 457 | 4350 | NA | NA | 31 | 4807 | 2020-03-13T20:00:00Z | 120 |\n",
"| 2020-03-14 | WA | 568 | 6001 | NA | NA | 37 | 6569 | 2020-03-14T20:00:00Z | 111 |\n",
"| 2020-03-15 | WA | 642 | 7122 | NA | NA | 40 | 7764 | 2020-03-15T20:00:00Z | 74 |\n",
"| 2020-03-16 | WA | 769 | 9451 | NA | NA | 42 | 10220 | 2020-03-16T20:00:00Z | 127 |\n",
"| 2020-03-17 | WA | 904 | 11582 | NA | NA | 48 | 12486 | 2020-03-17T20:00:00Z | 135 |\n",
"| 2020-03-18 | WA | 1012 | 13117 | NA | NA | 52 | 14129 | 2020-03-18T20:00:00Z | 108 |\n",
"| 2020-03-19 | WA | 1187 | 15918 | NA | NA | 66 | 17105 | 2020-03-19T20:00:00Z | 175 |\n",
"| 2020-03-20 | WA | 1376 | 19336 | NA | NA | 74 | 20712 | 2020-03-20T20:00:00Z | 189 |\n",
"\n"
],
"text/plain": [
" date state positive negative pending hospitalized death total\n",
"1 2020-03-04 WA 39 NA NA NA NA 39\n",
"2 2020-03-05 WA 70 NA NA NA NA 70\n",
"3 2020-03-06 WA 79 370 NA NA NA 449\n",
"4 2020-03-07 WA 102 370 66 NA NA 538\n",
"5 2020-03-08 WA 102 640 60 NA NA 802\n",
"6 2020-03-09 WA 136 1110 NA NA NA 1246\n",
"7 2020-03-10 WA 162 1110 NA NA NA 1272\n",
"8 2020-03-11 WA 267 2175 NA NA 24 2466\n",
"9 2020-03-12 WA 337 3037 NA NA 29 3403\n",
"10 2020-03-13 WA 457 4350 NA NA 31 4807\n",
"11 2020-03-14 WA 568 6001 NA NA 37 6569\n",
"12 2020-03-15 WA 642 7122 NA NA 40 7764\n",
"13 2020-03-16 WA 769 9451 NA NA 42 10220\n",
"14 2020-03-17 WA 904 11582 NA NA 48 12486\n",
"15 2020-03-18 WA 1012 13117 NA NA 52 14129\n",
"16 2020-03-19 WA 1187 15918 NA NA 66 17105\n",
"17 2020-03-20 WA 1376 19336 NA NA 74 20712\n",
" dateChecked diff_positive\n",
"1 2020-03-04T21:00:00Z NA \n",
"2 2020-03-05T21:00:00Z 31 \n",
"3 2020-03-06T21:00:00Z 9 \n",
"4 2020-03-07T21:00:00Z 23 \n",
"5 2020-03-08T20:00:00Z 0 \n",
"6 2020-03-09T20:00:00Z 34 \n",
"7 2020-03-10T20:00:00Z 26 \n",
"8 2020-03-11T20:00:00Z 105 \n",
"9 2020-03-12T20:00:00Z 70 \n",
"10 2020-03-13T20:00:00Z 120 \n",
"11 2020-03-14T20:00:00Z 111 \n",
"12 2020-03-15T20:00:00Z 74 \n",
"13 2020-03-16T20:00:00Z 127 \n",
"14 2020-03-17T20:00:00Z 135 \n",
"15 2020-03-18T20:00:00Z 108 \n",
"16 2020-03-19T20:00:00Z 175 \n",
"17 2020-03-20T20:00:00Z 189 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"tdf_state <- tdf[state == \"WA\"]\n",
"tdf_state"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Warning message:\n",
"“Removed 1 rows containing missing values (geom_bar).”\n"
]
},
{
"data": {
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CRBQgkSSZCQHIJUMkEiCRJKkEiChOQQ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\nLhIkMzPrIkEyM7Mu+v/pJAld6FZrEgAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 480,
"width": 840
},
"text/plain": {
"height": 480,
"width": 840
}
},
"output_type": "display_data"
}
],
"source": [
"ggplot(data = tdf_state, aes(x = date, y = diff_positive)) +\n",
" labs(title = \"WA\", y = \"Daily positive\") +\n",
" geom_bar(stat = \"identity\", position = position_dodge(width=1))\n",
" #. scale_y_continuous(sec.axis = sec_axis(~.*15, name = \"Positive\")) +\n",
" # geom_line(aes(y = total, colour = \"red\"), position = \"stack\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Counts per 100k"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"data_df <- as.data.table(data_df)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.table: 6 × 3</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>State</th><th scope=col>ST</th><th scope=col>Population</th></tr>\n",
"\t<tr><th scope=col><chr></th><th scope=col><chr></th><th scope=col><int></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>Alaska </td><td>AK</td><td> 731545</td></tr>\n",
"\t<tr><td>Alabama </td><td>AL</td><td> 4903185</td></tr>\n",
"\t<tr><td>Arkansas </td><td>AR</td><td> 3017825</td></tr>\n",
"\t<tr><td>Arizona </td><td>AZ</td><td> 7278717</td></tr>\n",
"\t<tr><td>California</td><td>CA</td><td>39512223</td></tr>\n",
"\t<tr><td>Colorado </td><td>CO</td><td> 5758736</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.table: 6 × 3\n",
"\\begin{tabular}{r|lll}\n",
" State & ST & Population\\\\\n",
" <chr> & <chr> & <int>\\\\\n",
"\\hline\n",
"\t Alaska & AK & 731545\\\\\n",
"\t Alabama & AL & 4903185\\\\\n",
"\t Arkansas & AR & 3017825\\\\\n",
"\t Arizona & AZ & 7278717\\\\\n",
"\t California & CA & 39512223\\\\\n",
"\t Colorado & CO & 5758736\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.table: 6 × 3\n",
"\n",
"| State <chr> | ST <chr> | Population <int> |\n",
"|---|---|---|\n",
"| Alaska | AK | 731545 |\n",
"| Alabama | AL | 4903185 |\n",
"| Arkansas | AR | 3017825 |\n",
"| Arizona | AZ | 7278717 |\n",
"| California | CA | 39512223 |\n",
"| Colorado | CO | 5758736 |\n",
"\n"
],
"text/plain": [
" State ST Population\n",
"1 Alaska AK 731545 \n",
"2 Alabama AL 4903185 \n",
"3 Arkansas AR 3017825 \n",
"4 Arizona AZ 7278717 \n",
"5 California CA 39512223 \n",
"6 Colorado CO 5758736 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pop_df <- fread(\"../../data/geodata/us_pop_fung_2019.csv\")\n",
"setkey(pop_df, ST)\n",
"head(pop_df)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"'Most recent test date 2020-03-20'"
],
"text/latex": [
"'Most recent test date 2020-03-20'"
],
"text/markdown": [
"'Most recent test date 2020-03-20'"
],
"text/plain": [
"[1] \"Most recent test date 2020-03-20\""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"'56 states/territories have data on this date.'"
],
"text/latex": [
"'56 states/territories have data on this date.'"
],
"text/markdown": [
"'56 states/territories have data on this date.'"
],
"text/plain": [
"[1] \"56 states/territories have data on this date.\""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"most_recent_test_date <- max(data_df$date)\n",
"most_recent_df <- data_df[date == most_recent_test_date]\n",
"paste(\"Most recent test date\", most_recent_test_date)\n",
"paste(nrow(most_recent_df), \"states/territories have data on this date.\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.table: 6 × 11</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>state</th><th scope=col>date</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>pending</th><th scope=col>hospitalized</th><th scope=col>death</th><th scope=col>total</th><th scope=col>dateChecked</th><th scope=col>State</th><th scope=col>Population</th></tr>\n",
"\t<tr><th scope=col><chr></th><th scope=col><date></th><th scope=col><int></th><th scope=col><int></th><th scope=col><int></th><th scope=col><lgl></th><th scope=col><int></th><th scope=col><int></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><int></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>AK</td><td>2020-03-20</td><td> 12</td><td> 686</td><td> NA</td><td>NA</td><td>NA</td><td> 698</td><td>2020-03-20T20:00:00Z</td><td>Alaska </td><td> 731545</td></tr>\n",
"\t<tr><td>AL</td><td>2020-03-20</td><td> 81</td><td> 28</td><td> NA</td><td>NA</td><td> 0</td><td> 109</td><td>2020-03-20T20:00:00Z</td><td>Alabama </td><td> 4903185</td></tr>\n",
"\t<tr><td>AR</td><td>2020-03-20</td><td> 96</td><td> 351</td><td>203</td><td>NA</td><td>NA</td><td> 650</td><td>2020-03-20T20:00:00Z</td><td>Arkansas </td><td> 3017825</td></tr>\n",
"\t<tr><td>AS</td><td>2020-03-20</td><td> 0</td><td> NA</td><td> NA</td><td>NA</td><td> 0</td><td> 0</td><td>2020-03-20T20:00:00Z</td><td>NA </td><td> NA</td></tr>\n",
"\t<tr><td>AZ</td><td>2020-03-20</td><td> 65</td><td> 211</td><td>101</td><td>NA</td><td> 0</td><td> 377</td><td>2020-03-20T20:00:00Z</td><td>Arizona </td><td> 7278717</td></tr>\n",
"\t<tr><td>CA</td><td>2020-03-20</td><td>1063</td><td>10424</td><td> NA</td><td>NA</td><td>20</td><td>11487</td><td>2020-03-20T20:00:00Z</td><td>California</td><td>39512223</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.table: 6 × 11\n",
"\\begin{tabular}{r|lllllllllll}\n",
" state & date & positive & negative & pending & hospitalized & death & total & dateChecked & State & Population\\\\\n",
" <chr> & <date> & <int> & <int> & <int> & <lgl> & <int> & <int> & <chr> & <chr> & <int>\\\\\n",
"\\hline\n",
"\t AK & 2020-03-20 & 12 & 686 & NA & NA & NA & 698 & 2020-03-20T20:00:00Z & Alaska & 731545\\\\\n",
"\t AL & 2020-03-20 & 81 & 28 & NA & NA & 0 & 109 & 2020-03-20T20:00:00Z & Alabama & 4903185\\\\\n",
"\t AR & 2020-03-20 & 96 & 351 & 203 & NA & NA & 650 & 2020-03-20T20:00:00Z & Arkansas & 3017825\\\\\n",
"\t AS & 2020-03-20 & 0 & NA & NA & NA & 0 & 0 & 2020-03-20T20:00:00Z & NA & NA\\\\\n",
"\t AZ & 2020-03-20 & 65 & 211 & 101 & NA & 0 & 377 & 2020-03-20T20:00:00Z & Arizona & 7278717\\\\\n",
"\t CA & 2020-03-20 & 1063 & 10424 & NA & NA & 20 & 11487 & 2020-03-20T20:00:00Z & California & 39512223\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.table: 6 × 11\n",
"\n",
"| state <chr> | date <date> | positive <int> | negative <int> | pending <int> | hospitalized <lgl> | death <int> | total <int> | dateChecked <chr> | State <chr> | Population <int> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|\n",
"| AK | 2020-03-20 | 12 | 686 | NA | NA | NA | 698 | 2020-03-20T20:00:00Z | Alaska | 731545 |\n",
"| AL | 2020-03-20 | 81 | 28 | NA | NA | 0 | 109 | 2020-03-20T20:00:00Z | Alabama | 4903185 |\n",
"| AR | 2020-03-20 | 96 | 351 | 203 | NA | NA | 650 | 2020-03-20T20:00:00Z | Arkansas | 3017825 |\n",
"| AS | 2020-03-20 | 0 | NA | NA | NA | 0 | 0 | 2020-03-20T20:00:00Z | NA | NA |\n",
"| AZ | 2020-03-20 | 65 | 211 | 101 | NA | 0 | 377 | 2020-03-20T20:00:00Z | Arizona | 7278717 |\n",
"| CA | 2020-03-20 | 1063 | 10424 | NA | NA | 20 | 11487 | 2020-03-20T20:00:00Z | California | 39512223 |\n",
"\n"
],
"text/plain": [
" state date positive negative pending hospitalized death total\n",
"1 AK 2020-03-20 12 686 NA NA NA 698\n",
"2 AL 2020-03-20 81 28 NA NA 0 109\n",
"3 AR 2020-03-20 96 351 203 NA NA 650\n",
"4 AS 2020-03-20 0 NA NA NA 0 0\n",
"5 AZ 2020-03-20 65 211 101 NA 0 377\n",
"6 CA 2020-03-20 1063 10424 NA NA 20 11487\n",
" dateChecked State Population\n",
"1 2020-03-20T20:00:00Z Alaska 731545 \n",
"2 2020-03-20T20:00:00Z Alabama 4903185 \n",
"3 2020-03-20T20:00:00Z Arkansas 3017825 \n",
"4 2020-03-20T20:00:00Z NA NA \n",
"5 2020-03-20T20:00:00Z Arizona 7278717 \n",
"6 2020-03-20T20:00:00Z California 39512223 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"most_recent_df <- merge(most_recent_df, pop_df, by.x = \"state\", by.y = \"ST\", all = TRUE)\n",
"head(most_recent_df)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.table: 6 × 3</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>date</th><th scope=col>state</th><th scope=col>total_100k</th></tr>\n",
"\t<tr><th scope=col><date></th><th scope=col><chr></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>2020-03-20</td><td>AK</td><td>95.414499</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AL</td><td> 2.223045</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AR</td><td>21.538691</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AS</td><td> NA</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>AZ</td><td> 5.179484</td></tr>\n",
"\t<tr><td>2020-03-20</td><td>CA</td><td>29.072017</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.table: 6 × 3\n",
"\\begin{tabular}{r|lll}\n",
" date & state & total\\_100k\\\\\n",
" <date> & <chr> & <dbl>\\\\\n",
"\\hline\n",
"\t 2020-03-20 & AK & 95.414499\\\\\n",
"\t 2020-03-20 & AL & 2.223045\\\\\n",
"\t 2020-03-20 & AR & 21.538691\\\\\n",
"\t 2020-03-20 & AS & NA\\\\\n",
"\t 2020-03-20 & AZ & 5.179484\\\\\n",
"\t 2020-03-20 & CA & 29.072017\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.table: 6 × 3\n",
"\n",
"| date <date> | state <chr> | total_100k <dbl> |\n",
"|---|---|---|\n",
"| 2020-03-20 | AK | 95.414499 |\n",
"| 2020-03-20 | AL | 2.223045 |\n",
"| 2020-03-20 | AR | 21.538691 |\n",
"| 2020-03-20 | AS | NA |\n",
"| 2020-03-20 | AZ | 5.179484 |\n",
"| 2020-03-20 | CA | 29.072017 |\n",
"\n"
],
"text/plain": [
" date state total_100k\n",
"1 2020-03-20 AK 95.414499 \n",
"2 2020-03-20 AL 2.223045 \n",
"3 2020-03-20 AR 21.538691 \n",
"4 2020-03-20 AS NA \n",
"5 2020-03-20 AZ 5.179484 \n",
"6 2020-03-20 CA 29.072017 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"most_recent_df[, total_100k := total / Population * 100000]\n",
"head(most_recent_df[, .(date, state, total_100k)])"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.table: 6 × 12</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>state</th><th scope=col>date</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>pending</th><th scope=col>hospitalized</th><th scope=col>death</th><th scope=col>total</th><th scope=col>dateChecked</th><th scope=col>State</th><th scope=col>Population</th><th scope=col>total_100k</th></tr>\n",
"\t<tr><th scope=col><chr></th><th scope=col><date></th><th scope=col><int></th><th scope=col><int></th><th scope=col><int></th><th scope=col><lgl></th><th scope=col><int></th><th scope=col><int></th><th scope=col><chr></th><th scope=col><chr></th><th scope=col><int></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>AS</td><td>2020-03-20</td><td> 0</td><td> NA</td><td>NA</td><td>NA</td><td> 0</td><td> 0</td><td>2020-03-20T20:00:00Z</td><td>NA </td><td> NA</td><td> NA</td></tr>\n",
"\t<tr><td>GU</td><td>2020-03-20</td><td>14</td><td> 86</td><td>NA</td><td>NA</td><td>NA</td><td>100</td><td>2020-03-20T20:00:00Z</td><td>NA </td><td> NA</td><td> NA</td></tr>\n",
"\t<tr><td>MP</td><td>2020-03-20</td><td> 0</td><td> NA</td><td>NA</td><td>NA</td><td> 0</td><td> 0</td><td>2020-03-20T20:00:00Z</td><td>NA </td><td> NA</td><td> NA</td></tr>\n",
"\t<tr><td>PR</td><td>2020-03-20</td><td>14</td><td>114</td><td>52</td><td>NA</td><td>NA</td><td>180</td><td>2020-03-20T20:00:00Z</td><td>NA </td><td> NA</td><td> NA</td></tr>\n",
"\t<tr><td>VI</td><td>2020-03-20</td><td> 3</td><td> NA</td><td>NA</td><td>NA</td><td> 0</td><td> 3</td><td>2020-03-20T20:00:00Z</td><td>NA </td><td> NA</td><td> NA</td></tr>\n",
"\t<tr><td>AL</td><td>2020-03-20</td><td>81</td><td> 28</td><td>NA</td><td>NA</td><td> 0</td><td>109</td><td>2020-03-20T20:00:00Z</td><td>Alabama</td><td>4903185</td><td>2.223045</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.table: 6 × 12\n",
"\\begin{tabular}{r|llllllllllll}\n",
" state & date & positive & negative & pending & hospitalized & death & total & dateChecked & State & Population & total\\_100k\\\\\n",
" <chr> & <date> & <int> & <int> & <int> & <lgl> & <int> & <int> & <chr> & <chr> & <int> & <dbl>\\\\\n",
"\\hline\n",
"\t AS & 2020-03-20 & 0 & NA & NA & NA & 0 & 0 & 2020-03-20T20:00:00Z & NA & NA & NA\\\\\n",
"\t GU & 2020-03-20 & 14 & 86 & NA & NA & NA & 100 & 2020-03-20T20:00:00Z & NA & NA & NA\\\\\n",
"\t MP & 2020-03-20 & 0 & NA & NA & NA & 0 & 0 & 2020-03-20T20:00:00Z & NA & NA & NA\\\\\n",
"\t PR & 2020-03-20 & 14 & 114 & 52 & NA & NA & 180 & 2020-03-20T20:00:00Z & NA & NA & NA\\\\\n",
"\t VI & 2020-03-20 & 3 & NA & NA & NA & 0 & 3 & 2020-03-20T20:00:00Z & NA & NA & NA\\\\\n",
"\t AL & 2020-03-20 & 81 & 28 & NA & NA & 0 & 109 & 2020-03-20T20:00:00Z & Alabama & 4903185 & 2.223045\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.table: 6 × 12\n",
"\n",
"| state <chr> | date <date> | positive <int> | negative <int> | pending <int> | hospitalized <lgl> | death <int> | total <int> | dateChecked <chr> | State <chr> | Population <int> | total_100k <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| AS | 2020-03-20 | 0 | NA | NA | NA | 0 | 0 | 2020-03-20T20:00:00Z | NA | NA | NA |\n",
"| GU | 2020-03-20 | 14 | 86 | NA | NA | NA | 100 | 2020-03-20T20:00:00Z | NA | NA | NA |\n",
"| MP | 2020-03-20 | 0 | NA | NA | NA | 0 | 0 | 2020-03-20T20:00:00Z | NA | NA | NA |\n",
"| PR | 2020-03-20 | 14 | 114 | 52 | NA | NA | 180 | 2020-03-20T20:00:00Z | NA | NA | NA |\n",
"| VI | 2020-03-20 | 3 | NA | NA | NA | 0 | 3 | 2020-03-20T20:00:00Z | NA | NA | NA |\n",
"| AL | 2020-03-20 | 81 | 28 | NA | NA | 0 | 109 | 2020-03-20T20:00:00Z | Alabama | 4903185 | 2.223045 |\n",
"\n"
],
"text/plain": [
" state date positive negative pending hospitalized death total\n",
"1 AS 2020-03-20 0 NA NA NA 0 0 \n",
"2 GU 2020-03-20 14 86 NA NA NA 100 \n",
"3 MP 2020-03-20 0 NA NA NA 0 0 \n",
"4 PR 2020-03-20 14 114 52 NA NA 180 \n",
"5 VI 2020-03-20 3 NA NA NA 0 3 \n",
"6 AL 2020-03-20 81 28 NA NA 0 109 \n",
" dateChecked State Population total_100k\n",
"1 2020-03-20T20:00:00Z NA NA NA \n",
"2 2020-03-20T20:00:00Z NA NA NA \n",
"3 2020-03-20T20:00:00Z NA NA NA \n",
"4 2020-03-20T20:00:00Z NA NA NA \n",
"5 2020-03-20T20:00:00Z NA NA NA \n",
"6 2020-03-20T20:00:00Z Alabama 4903185 2.223045 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"setkey(most_recent_df, total_100k)\n",
"head(most_recent_df)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"most_recent_df[, state := factor(state, levels = c(state))]"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Warning message:\n",
"“Removed 5 rows containing missing values (geom_bar).”\n"
]
},
{
"data": {
"image/png": 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+4FkAAJkGyvKyC5AFKsE+4FkAAJkGyv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\n5qx6hgAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 480,
"width": 840
},
"text/plain": {
"height": 480,
"width": 840
}
},
"output_type": "display_data"
}
],
"source": [
"ggplot(data = most_recent_df, aes(x = state, y = total_100k)) +\n",