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data-raw/jhu_csse_county_level_subset.R

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@@ -23,7 +23,7 @@ jhu_csse_county_level_subset <- pub_covidcast(
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time_values = epirange(20200601, 20211231),
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) %>%
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select(geo_value, time_value, cases = value) %>%
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inner_join(y, by = "geo_value", relationship = "many-to-one", unmatched = c("error","drop")) %>%
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inner_join(y, by = "geo_value", relationship = "many-to-one", unmatched = c("error", "drop")) %>%
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as_epi_df()
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usethis::use_data(jhu_csse_county_level_subset, overwrite = TRUE)

vignettes/aggregation.Rmd

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@@ -124,7 +124,7 @@ state_naming <- read_csv("https://github.com/cmu-delphi/covidcast/raw/c89e4d2955
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# First make geo value more readable for tables, plots, etc.
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x <- x %>%
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inner_join(state_naming, by = "state_name", relationship = "many-to-one", unmatched = c("error","drop")) %>%
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inner_join(state_naming, by = "state_name", relationship = "many-to-one", unmatched = c("error", "drop")) %>%
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mutate(geo_value = paste(substr(county_name, 1, nchar(county_name) - 7), state_name, sep = ", ")) %>%
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select(geo_value, time_value, cases)
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