$```$

dt $=$ pandas.read$\_$csv$(\text{'}./$co$-$est$2019-$alldata.csv$\text{'},$ encoding$=$'lat$$n$-1\text{'})$

$[62]$ data $=$ df$.$to$\_$dict$(\text{'}$records$\text{'})$

db$.$populations.drop$()$

db$.$populations.insert$\_$many$($data$)$

print$("$Done$!")$

$```$

$$ Done!

Using the aggregation pipeline and the $\backslash$$out stage create a new dataset that just maps the state to total counts. Do this for all three data sets so you have:

casesdeaths$\_$state $=($state$,$ cases, deaths$)$

populations$\_$state $\backslash (=(\backslash )$ state, population $\backslash ()\backslash )$

vaccinations$\_$state $\backslash (=(\backslash )$ state, vaccinations$)$

$```$

$`$s $[64]$ ies have a running sum by date, taking the max of each county, then summing by state is correct math$)8$

$```$

$[66]\backslash$# Create the vaccinations$\_$state collection $($this dataset is by state and date. You don't want the sum of a$\text{'}$

Use the $\backslash$$lookup stage of the aggregation pipeline to join your three data sets by state. Note this won't be a perfect join $-$ to find out why look at the states or even the count of states in each set.

os $[67]($cases$/$population$),$ death rate $($deaths$/$population$),$ vaccination rate $($vaccinated$\_$people$/$population$).$

$[]\backslash$# Is there a correlation between infection or death rates with the vaccination rate for each state?