114114# ' },
115115# ' .window_size = 7
116116# ' ) %>%
117+ # ' ungroup() %>%
117118# ' dplyr::select(geo_value, time_value, cases, cases_7sd, cases_7dav)
118119# '
119120# ' # Use the geo_value or the ref_time_value in the slide computation
@@ -605,7 +606,8 @@ get_before_after_from_window <- function(window_size, align, time_type) {
605606# ' # Compute a 7-day trailing average on cases.
606607# ' cases_deaths_subset %>%
607608# ' group_by(geo_value) %>%
608- # ' epi_slide_opt(cases, .f = data.table::frollmean, .window_size = 7)
609+ # ' epi_slide_opt(cases, .f = data.table::frollmean, .window_size = 7) %>%
610+ # ' ungroup()
609611# '
610612# ' # Same as above, but adjust `frollmean` settings for speed, accuracy, and
611613# ' # to allow partially-missing windows.
@@ -615,7 +617,8 @@ get_before_after_from_window <- function(window_size, align, time_type) {
615617# ' cases,
616618# ' .f = data.table::frollmean, .window_size = 7,
617619# ' algo = "exact", hasNA = TRUE, na.rm = TRUE
618- # ' )
620+ # ' ) %>%
621+ # ' ungroup()
619622epi_slide_opt <- function (
620623 .x , .col_names , .f , ... ,
621624 .window_size = NULL , .align = c(" right" , " center" , " left" ),
@@ -919,20 +922,36 @@ epi_slide_opt <- function(
919922# '
920923# ' @export
921924# ' @examples
922- # ' # Compute a 7-day trailing average on cases .
923- # ' cases_deaths_subset %>%
925+ # ' # Compute a 7-day trailing average of case rates .
926+ # ' covid_case_death_rates_extended %>%
924927# ' group_by(geo_value) %>%
925- # ' epi_slide_mean(cases, .window_size = 7)
928+ # ' epi_slide_mean(case_rate, .window_size = 7) %>%
929+ # ' ungroup()
926930# '
927931# ' # Same as above, but adjust `frollmean` settings for speed, accuracy, and
928932# ' # to allow partially-missing windows.
929- # ' cases_deaths_subset %>%
933+ # ' covid_case_death_rates_extended %>%
930934# ' group_by(geo_value) %>%
931935# ' epi_slide_mean(
932- # ' cases ,
936+ # ' case_rate ,
933937# ' .window_size = 7,
934938# ' na.rm = TRUE, algo = "exact", hasNA = TRUE
935- # ' )
939+ # ' ) %>%
940+ # ' ungroup()
941+ # '
942+ # ' # Compute a 7-day trailing average of case rates and death rates, with custom
943+ # ' # output column names:
944+ # ' covid_case_death_rates_extended %>%
945+ # ' group_by(geo_value) %>%
946+ # ' epi_slide_mean(c(case_rate, death_rate),
947+ # ' .window_size = 7,
948+ # ' .new_col_names = c("smoothed_case_rate", "smoothed_death_rate")
949+ # ' ) %>%
950+ # ' ungroup()
951+ # ' covid_case_death_rates_extended %>%
952+ # ' group_by(geo_value) %>%
953+ # ' epi_slide_mean(c(case_rate, death_rate), .window_size = 7, .suffix = "_{.n}{.time_unit_abbr}_avg") %>%
954+ # ' ungroup()
936955epi_slide_mean <- function (
937956 .x , .col_names , ... ,
938957 .window_size = NULL , .align = c(" right" , " center" , " left" ),
@@ -995,8 +1014,22 @@ epi_slide_mean <- function(
9951014# ' @examples
9961015# ' # Compute a 7-day trailing sum on cases.
9971016# ' cases_deaths_subset %>%
1017+ # ' select(geo_value, time_value, cases) %>%
1018+ # ' group_by(geo_value) %>%
1019+ # ' epi_slide_sum(cases, .window_size = 7) %>%
1020+ # ' ungroup()
1021+ # '
1022+ # ' # Specify output column names and/or naming scheme:
1023+ # ' cases_deaths_subset %>%
1024+ # ' select(geo_value, time_value, cases) %>%
1025+ # ' group_by(geo_value) %>%
1026+ # ' epi_slide_sum(cases, .window_size = 7, .new_col_names = "case_sum") %>%
1027+ # ' ungroup()
1028+ # ' cases_deaths_subset %>%
1029+ # ' select(geo_value, time_value, cases) %>%
9981030# ' group_by(geo_value) %>%
999- # ' epi_slide_sum(cases, .window_size = 7)
1031+ # ' epi_slide_sum(cases, .window_size = 7, .prefix = "sum_") %>%
1032+ # ' ungroup()
10001033epi_slide_sum <- function (
10011034 .x , .col_names , ... ,
10021035 .window_size = NULL , .align = c(" right" , " center" , " left" ),
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