indianacovid19data has csv file types for all its datasets in the inst/extdata
directory. This function makes them easy to access.
path_to_file(name = NULL)
| name | Name of file in quotes with extension. If |
|---|
The function is similar to palmerpenguins::path_to_file() with a few edits.
The csv file for hosp_react_tab doesn't include the list columns.
path_to_file() #> [1] "age_cases_heat.csv" "age_death_line.csv" #> [3] "age_hosp_line.csv" "beds_vents_complete.csv" #> [5] "dash_ci_line.csv" "goog_mob_ind.csv" #> [7] "hosp_msas_line.csv" "hosp_react_tab.csv" #> [9] "illinois_tests_complete.csv" "ind_age_complete.csv" #> [11] "ind_race_complete.csv" "ind_tests_complete.csv" #> [13] "median_age_bubble.csv" "mich_tests_complete.csv" #> [15] "mort_hosp_line.csv" "msa_cases100_posrate_historic.csv" #> [17] "open_tab_reg.csv" "wisc_tests_complete.csv" path_to_file("hosp_msas_line.csv") #> [1] "/home/runner/work/_temp/Library/indianacovid19data/extdata/hosp_msas_line.csv" head(read.csv(path_to_file("hosp_msas_line.csv"))) #> date roll_mean_staff_short_perc mean_mort_rate roll_mean_admiss skewness #> 1 Dec 08 0.1767381 0.1276227 426.8571 0.8701146 #> 2 Dec 09 0.1767381 0.1290508 392.4286 0.8597092 #> 3 Dec 10 0.1793673 0.1301993 358.1429 0.8463110 #> 4 Dec 11 0.1812771 0.1300213 345.8571 0.8493029 #> 5 Dec 12 0.1802384 0.1281706 309.4286 0.8464296 #> 6 Dec 13 0.1791996 0.1302980 361.4286 0.8361402