View source: R/covidtracking_com.R
covidtracker_data | R Documentation |
Get data from the COVID tracking project https://covidtracking.com/ including daily historical data on testing results, hospitalizations, deaths, and ICU and ventilated patients.
covidtracker_data()
From the COVID Tracking Project website:
The COVID Tracking Project collects information from 50 US states, the District of Columbia, and 5 other US territories to provide the most comprehensive testing data we can collect for the novel coronavirus, SARS-CoV-2. We attempt to report positive and negative results, pending tests, and total people tested for each state or district currently reporting that data.
A tidy tbl_df
Other data-import:
acaps_government_measures_data()
,
acaps_secondary_impact_data()
,
apple_mobility_data()
,
beoutbreakprepared_data()
,
cci_us_vaccine_data()
,
cdc_aggregated_projections()
,
cdc_excess_deaths()
,
cdc_social_vulnerability_index()
,
coronadatascraper_data()
,
coronanet_government_response_data()
,
cov_glue_lineage_data()
,
cov_glue_newick_data()
,
cov_glue_snp_lineage()
,
descartes_mobility_data()
,
ecdc_data()
,
econ_tracker_consumer_spending
,
econ_tracker_employment
,
econ_tracker_unemp_data
,
economist_excess_deaths()
,
financial_times_excess_deaths()
,
google_mobility_data()
,
government_policy_timeline()
,
jhu_data()
,
jhu_us_data()
,
kff_icu_beds()
,
nytimes_county_data()
,
oecd_unemployment_data()
,
owid_data()
,
param_estimates_published()
,
test_and_trace_data()
,
us_county_geo_details()
,
us_county_health_rankings()
,
us_healthcare_capacity()
,
us_hospital_details()
,
us_state_distancing_policy()
,
usa_facts_data()
,
who_cases()
Other case-tracking:
align_to_baseline()
,
beoutbreakprepared_data()
,
bulk_estimate_Rt()
,
combined_us_cases_data()
,
coronadatascraper_data()
,
ecdc_data()
,
estimate_Rt()
,
jhu_data()
,
nytimes_county_data()
,
owid_data()
,
plot_epicurve()
,
test_and_trace_data()
,
usa_facts_data()
,
who_cases()
library(dplyr) library(ggplot2) res = covidtracker_data() colnames(res) dim(res) dplyr::glimpse(res) # Hospitalizations by day in Maryland covidtracker_data() %>% dplyr::filter(state=='MD') %>% add_incidence_column(count_column='hospitalized') %>% ggplot(aes(x=date,y=inc)) + geom_smooth() + ylab("New Hospitalizations per day") + ggtitle('Hospitalizations in Maryland', subtitle = 'From covidtracker')
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