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@jsfenfen
Created March 5, 2021 00:02
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Save jsfenfen/4163f6d3b3d10f6ad49293bd3f7a9c82 to your computer and use it in GitHub Desktop.
library(ggplot2)
library(dplyr)
# See https://healthdata.gov/dataset/covid-19-reported-patient-impact-and-hospital-capacity-state-timeseries
fileurl = "https://healthdata.gov/sites/default/files/reported_hospital_utilization_timeseries_20210227_1306.csv"
hospraw <- read.csv(url(fileurl), header=TRUE, sep=",")
# parse the dates
hospraw$dateob = as.Date(hospraw$date)
# Look at every state at once
# Also filter out negative numbers so the scale doesn't get messed up
hospraw %>% filter(previous_day_admission_pediatric_covid_suspected>0) %>% ggplot(aes(x=dateob,y=previous_day_admission_pediatric_covid_suspected)) + geom_line() + facet_wrap( ~ state, scales = "free" ) + xlab("") + xlim(as.Date('2020-07-01'), as.Date('2021-03-01'))
# Look at just OR and WA
hospraw %>% filter(state=="OR" | state=="WA" ) %>% ggplot(aes(x=dateob,y=previous_day_admission_pediatric_covid_suspected, color=state)) + geom_line() + xlab("Date")
# Coverage of pediatric suspected is not the cause of this anomaly
hospraw %>% filter(previous_day_admission_pediatric_covid_suspected_coverage>0) %>% ggplot(aes(x=dateob,y=previous_day_admission_pediatric_covid_suspected_coverage)) + geom_line() + facet_wrap( ~ state, scales = "free" ) + xlab("Date") + xlim(as.Date('2020-07-01'), as.Date('2021-03-01'))
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