The goal of canadacovid is to provide a wrapper around the API service for the COVID-19 Tracker Canada. To see how the package was developed, see this post.
Install canadacovid from CRAN:
You can install the development version of canadacovid from GitHub:
To get the latest summary data:
library(canadacovid)
library(tidyverse)
summary_overall <- get_summary()
glimpse(summary_overall)
#> Rows: 1
#> Columns: 22
#> $ last_updated <dttm> 2022-01-20 18:10:02
#> $ latest_date <date> 2022-01-20
#> $ change_cases <int> 23167
#> $ change_fatalities <int> 210
#> $ change_tests <int> 81335
#> $ change_hospitalizations <int> -6
#> $ change_criticals <int> 8
#> $ change_recoveries <int> 30579
#> $ change_vaccinations <int> 198559
#> $ change_vaccinated <int> 14000
#> $ change_boosters_1 <int> 187385
#> $ change_vaccines_distributed <int> 0
#> $ total_cases <int> 2866146
#> $ total_fatalities <int> 32217
#> $ total_tests <int> 55885939
#> $ total_hospitalizations <int> 10609
#> $ total_criticals <int> 1203
#> $ total_recoveries <int> 2520615
#> $ total_vaccinations <int> 75105874
#> $ total_vaccinated <int> 29729902
#> $ total_boosters_1 <int> 13229157
#> $ total_vaccines_distributed <int> 84909134By default, this returns the aggregate data over all of Canada. Provide a split argument to get a summary by “province” or “region”:
summary_province <- get_summary(split = "province")
glimpse(summary_province)
#> Rows: 13
#> Columns: 23
#> $ last_updated <dttm> 2022-01-20 18:10:02, 2022-01-20 18:10:02,~
#> $ province <chr> "ON", "QC", "NS", "NB", "MB", "BC", "PE", ~
#> $ date <chr> "2022-01-20", "2022-01-20", "2022-01-20", ~
#> $ change_cases <int> 7757, 6528, 696, 488, 850, 2150, 0, 1171, ~
#> $ change_fatalities <int> 75, 98, 4, 3, 7, 15, 0, 0, 8, 0, 0, 0, 0
#> $ change_tests <int> 42907, 0, 4459, 4580, 2450, 12274, 0, 3513~
#> $ change_hospitalizations <int> -71, -14, 2, 1, 34, -4, 0, 16, 30, 0, 0, 0~
#> $ change_criticals <int> 5, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 0, 0
#> $ change_recoveries <int> 12578, 0, 0, 392, 6809, 3174, 0, 1092, 653~
#> $ change_vaccinations <int> 104845, 0, 18072, 10130, 8531, 59042, 0, 2~
#> $ change_vaccinated <int> 9205, 0, 306, 307, 913, 2001, 0, 1263, 5, ~
#> $ change_boosters_1 <int> 86274, 0, 17233, 9159, 6739, 54080, 0, 0, ~
#> $ change_vaccines_distributed <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
#> $ total_cases <int> 977194, 818947, 31874, 24489, 113196, 3057~
#> $ total_fatalities <int> 10801, 12639, 128, 199, 1485, 2520, 2, 961~
#> $ total_tests <int> 22288866, 15682022, 1674063, 666919, 13574~
#> $ total_hospitalizations <int> 4061, 3411, 85, 124, 665, 891, 8, 215, 113~
#> $ total_criticals <int> 594, 285, 12, 12, 50, 115, 4, 23, 108, 0, ~
#> $ total_recoveries <int> 887023, 747819, 17152, 19899, 75969, 26576~
#> $ total_vaccinations <int> 29769719, 16953912, 1998064, 1575232, 2681~
#> $ total_vaccinated <int> 11570076, 6734670, 798609, 626997, 1048824~
#> $ total_boosters_1 <int> 5793578, 2844797, 327601, 261910, 488289, ~
#> $ total_vaccines_distributed <int> 33390981, 19822969, 2243162, 1756685, 2987~Day-by-day reports are retrieved with get_reports:
reports_overall <- get_reports()
#> Called from: get_reports()
#> debug: reports %>% dplyr::mutate(dplyr::across(tidyselect::matches("^change|total"),
#> as.integer), dplyr::across(tidyselect::matches("^date"),
#> as.Date), last_updated = as.POSIXct(.data$last_updated, tz = "America/Regina"))
glimpse(reports_overall)
#> Rows: 727
#> Columns: 22
#> $ last_updated <dttm> 2022-01-20 18:10:02, 2022-01-20 18:10:02,~
#> $ date <date> 2020-01-25, 2020-01-26, 2020-01-27, 2020-~
#> $ change_cases <int> 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 2, 0, ~
#> $ change_fatalities <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_tests <int> 2, 4, 20, 10, 3, 26, 33, 23, 24, 16, 56, 5~
#> $ change_hospitalizations <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_criticals <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_recoveries <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_vaccinations <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_vaccinated <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_boosters_1 <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ change_vaccines_distributed <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_cases <int> 1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 4, 5, 7, 7, ~
#> $ total_fatalities <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_tests <int> 2, 6, 26, 36, 39, 65, 98, 121, 145, 161, 2~
#> $ total_hospitalizations <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_criticals <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_recoveries <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_vaccinations <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_vaccinated <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_boosters_1 <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~
#> $ total_vaccines_distributed <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~This function comes with a number of arguments to return very specific data:
reports_ns_fatalities_2021 <-
get_reports(province = "NS", stat = "fatalities",
after = "2021-01-01", before = "2021-12-31")
glimpse(reports_ns_fatalities_2021)
#> Rows: 365
#> Columns: 5
#> $ province <chr> "NS", "NS", "NS", "NS", "NS", "NS", "NS", "NS", "NS"~
#> $ last_updated <dttm> 2022-01-20 14:12:04, 2022-01-20 14:12:04, 2022-01-2~
#> $ date <date> 2021-01-01, 2021-01-02, 2021-01-03, 2021-01-04, 202~
#> $ change_fatalities <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0~
#> $ total_fatalities <int> 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, ~memoise functionality to avoid repeated API requests.