researcher + visual artist
Clean covid dataset
source: https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv
import {
tidy,
groupBy,
summarize,
tally,
count,
n,
filter,
complete,
select,
pivotLonger,
negate,
sum,
mutate,
mutateWithSummary,
lag,
rename,
max,
sliceMax,
map,
} from '@pbeshai/tidyjs'
covid_data = FileAttachment("time_series_covid19_confirmed_global.csv").csv()
Object.keys(covid_data[0]).slice(0,4)
time_keys = Object.keys(covid_data[0]).slice(4)
formatTime = d3.timeFormat('%Y-%m-%d')
tidy_data = tidy(
covid_data,
pivotLonger({
cols: time_keys,
namesTo: 'date',
valuesTo: 'cases',
}),
rename({'Country/Region': 'country'}),
map(d => ({...d, date: formatTime(Date.parse(d.date))})),
groupBy(['country', 'date'], [
summarize({
cases: sum('cases'),
})
]),
mutateWithSummary({
prev_cases: lag('cases', { default: 0 }),
}),
mutate({
new_daily: (d) => d.cases - d.prev_cases,
})
)
tidy_data2 = tidy(
covid_data,
pivotLonger({
cols: time_keys,
namesTo: 'date',
valuesTo: 'cases',
}),
rename({'Country/Region': 'country'}),
map(d => ({...d, date: formatTime(Date.parse(d.date))})),
groupBy(['country', 'date'], [
summarize({
cases: sum('cases'),
})
]),
mutateWithSummary({
prev_cases: lag('cases', { default: 0 }),
}),
mutate({
new_daily: (d) => d.cases - d.prev_cases < 0 ? 0 : d.cases - d.prev_cases,
})
)
country_list = tidy(
tidy_data,
groupBy(['country'], [
summarize({
max_cases: max('cases'),
})
]),
sliceMax(10, 'max_cases'),
map(d => d.country)
)
tidier_data = tidy(
tidy_data2,
filter(d => country_list.includes(d.country)),
select(negate('prev_cases'))
)
Inputs.table(tidier_data)
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