see www.diegoolano.com/us_per_capita_covid
The following are the notes I took while creating this. Mostly for use for developers interested in it and not end users.
from prior map viz I based this off of http://diegoolano.com/electionmap/from_2012_to_2016/republican-per.html
head change.csv
fips,County,rdiff16_per,rdiff16_raw,ddiff16_per,ddiff16_raw
get county COVID data from NYTimes
#https://github.com/nytimes/covid-19-data wget https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv
head us-counties.csv
date,county,state,fips,cases,deaths
to get populations per county from US Census
SUMLEV,REGION,DIVISION,STATE,COUNTY,STNAME,CTYNAME,CENSUS2010POP,ESTIMATESBASE2010,POPESTIMATE2010,POPESTIMATE2011,POPESTIMATE2012,POPESTIMATE2013,POPESTIMATE2014,POPESTIMATE2015,POPESTIMATE2016,POPESTIMATE2017,POPESTIMATE2018,POPESTIMATE2019,NPOPCHG_2010,NPOPCHG_2011,NPOPCHG_2012,NPOPCHG_2013,NPOPCHG_2014,NPOPCHG_2015,NPOPCHG_2016,NPOPCHG_2017,NPOPCHG_2018,NPOPCHG_2019,BIRTHS2010,BIRTHS2011,BIRTHS2012,BIRTHS2013,BIRTHS2014,BIRTHS2015,BIRTHS2016,BIRTHS2017,BIRTHS2018,BIRTHS2019,DEATHS2010,DEATHS2011,DEATHS2012,DEATHS2013,DEATHS2014,DEATHS2015,DEATHS2016,DEATHS2017,DEATHS2018,DEATHS2019,NATURALINC2010,NATURALINC2011,NATURALINC2012,NATURALINC2013,NATURALINC2014,NATURALINC2015,NATURALINC2016,NATURALINC2017,NATURALINC2018,NATURALINC2019,INTERNATIONALMIG2010,INTERNATIONALMIG2011,INTERNATIONALMIG2012,INTERNATIONALMIG2013,INTERNATIONALMIG2014,INTERNATIONALMIG2015,INTERNATIONALMIG2016,INTERNATIONALMIG2017,INTERNATIONALMIG2018,INTERNATIONALMIG2019,DOMESTICMIG2010,DOMESTICMIG2011,DOMESTICMIG2012,DOMESTICMIG2013,DOMESTICMIG2014,DOMESTICMIG2015,DOMESTICMIG2016,DOMESTICMIG2017,DOMESTICMIG2018,DOMESTICMIG2019,NETMIG2010,NETMIG2011,NETMIG2012,NETMIG2013,NETMIG2014,NETMIG2015,NETMIG2016,NETMIG2017,NETMIG2018,NETMIG2019,RESIDUAL2010,RESIDUAL2011,RESIDUAL2012,RESIDUAL2013,RESIDUAL2014,RESIDUAL2015,RESIDUAL2016,RESIDUAL2017,RESIDUAL2018,RESIDUAL2019,GQESTIMATESBASE2010,GQESTIMATES2010,GQESTIMATES2011,GQESTIMATES2012,GQESTIMATES2013,GQESTIMATES2014,GQESTIMATES2015,GQESTIMATES2016,GQESTIMATES2017,GQESTIMATES2018,GQESTIMATES2019,RBIRTH2011,RBIRTH2012,RBIRTH2013,RBIRTH2014,RBIRTH2015,RBIRTH2016,RBIRTH2017,RBIRTH2018,RBIRTH2019,RDEATH2011,RDEATH2012,RDEATH2013,RDEATH2014,RDEATH2015,RDEATH2016,RDEATH2017,RDEATH2018,RDEATH2019,RNATURALINC2011,RNATURALINC2012,RNATURALINC2013,RNATURALINC2014,RNATURALINC2015,RNATURALINC2016,RNATURALINC2017,RNATURALINC2018,RNATURALINC2019,RINTERNATIONALMIG2011,RINTERNATIONALMIG2012,RINTERNATIONALMIG2013,RINTERNATIONALMIG2014,RINTERNATIONALMIG2015,RINTERNATIONALMIG2016,RINTERNATIONALMIG2017,RINTERNATIONALMIG2018,RINTERNATIONALMIG2019,RDOMESTICMIG2011,RDOMESTICMIG2012,RDOMESTICMIG2013,RDOMESTICMIG2014,RDOMESTICMIG2015,RDOMESTICMIG2016,RDOMESTICMIG2017,RDOMESTICMIG2018,RDOMESTICMIG2019,RNETMIG2011,RNETMIG2012,RNETMIG2013,RNETMIG2014,RNETMIG2015,RNETMIG2016,RNETMIG2017,RNETMIG2018,RNETMIG2019
to just use POPESTIMATE2019 from US census data
cat co-est2019-alldata.csv | cut -d ',' -f 4-7,19 > county_popestimate2019.csv
then do vim stuff to simplify it to just get the following csv
fips,stname,ctyname,pop2019
then do vim stuff ( since us-counties is for many dates )
cp us-counties.csv us-counties0404.csv
some counties don't have numbers for now
wc -l us-counties0404.csv # 2409 wc -l county_popestimate2019.csv # 3194