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# This turns the CDC mortality data[0] into a format useful for my
# excess mortality spreadsheet. The US format is by far the worst one
# I have dealt with, as expected.
#
# This requires miller for transforming the CSV appropriately.
#
# Params:
# state: abbreviation of the state to extract ('US' for whole country)
# period: time period (either "2020" for current data, or anything else
# for historical averages)
#
# Call as:
# mlr --icsv --ojson cat weekly.csv | \
# jq -rsf us_mortality.jq --arg state US --arg period 2020
#
# [0]: https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm
def filter_period(period):
if period == "2020"
then . | map(select(.["Time Period"] == 2020))
else . | map(select(.["Time Period"] == "2015-2019"))
end;
def collate_weeks(period):
(. | map(.["Number of Deaths"]) | add) as $count
| {
count: (if period == "2020" then $count else $count / 5 end),
week: .[0].Week,
};
. | map(select(.Type == "Predicted (weighted)"))
| map(select(.["State Abbreviation"] == $state))
| filter_period($period)
| group_by(.Week)
| map(collate_weeks($period))
| .[] | "week \(.week): \(.count)"
|
