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Hi @jebyrnes
I noticed in the county data, that some rows are missing the location code (NYC, Kansas City, etc.). Generally, I think that in some of those cases, the data was not available on the county level, so they provided the aggregated city level. Here is an example:
library(covid19nytimes)
df <- refresh_covid19nytimes_counties()
df %>% dplyr::filter(date == as.Date("2020-05-18"), is.na(location_code)) %>%
dplyr::arrange(-value) %>%
head(10)
# A tibble: 10 x 7
date location location_type location_code location_code_type data_type value
<date> <chr> <chr> <chr> <chr> <chr> <dbl>
1 2020-05-18 New York City,New York county NA fips_code cases_total 198114
2 2020-05-18 New York City,New York county NA fips_code deaths_total 20298
3 2020-05-18 Unknown,Michigan county NA fips_code cases_total 3171
4 2020-05-18 Unknown,Puerto Rico county NA fips_code cases_total 2710
5 2020-05-18 Unknown,Georgia county NA fips_code cases_total 2216
6 2020-05-18 Unknown,Rhode Island county NA fips_code cases_total 2006
7 2020-05-18 Unknown,Guam county NA fips_code cases_total 1123
8 2020-05-18 Kansas City,Missouri county NA fips_code cases_total 901
9 2020-05-18 Unknown,New Jersey county NA fips_code cases_total 835
10 2020-05-18 Unknown,Massachusetts county NA fips_code cases_total 312
The text was updated successfully, but these errors were encountered:
Hi @jebyrnes
I noticed in the county data, that some rows are missing the location code (NYC, Kansas City, etc.). Generally, I think that in some of those cases, the data was not available on the county level, so they provided the aggregated city level. Here is an example:
The text was updated successfully, but these errors were encountered: