@@ -8,11 +8,24 @@ extra_datasets <- function() {
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# announce start
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cat(" Assembling extra datasets..." , fill = TRUE )
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+ # define maximum date for dataset
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+ dataset_max_date <- as.Date(" 2023-12-31" )
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+
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+ # function: filter for maximum date
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+ filter_max_date <- function (d , date_col = " date" ) {
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+ # ensure date col is correct type
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+ d [[date_col ]] <- as.Date(d [[date_col ]])
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+ # filter for maximum date
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+ dplyr :: filter(d , .data [[date_col ]] < = dataset_max_date )
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+ }
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+
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# PHAC wastewater dataset
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tryCatch(
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{
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# load data
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d <- read_d(" raw_data/active_ts/can/can_wastewater_copies_per_ml_subhr_ts.csv" , val_numeric = TRUE )
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+ # max date
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+ d <- filter_max_date(d )
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# write dataset
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utils :: write.csv(d , file.path(" extra_data" , " phac_wastewater" , " phac_wastewater.csv" ), row.names = FALSE , quote = 1 : 7 , na = " " )
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},
@@ -40,6 +53,9 @@ extra_datasets <- function() {
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cases_weekly = round(.data $ percent_positivity_weekly * .data $ tests_completed_weekly / 100 ),
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.data $ update
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)
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+ # max date
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+ ter <- filter_max_date(ter , " date_end" )
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+ # write dataset
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utils :: write.csv(ter , file.path(" extra_data" , " territories_rvdss_since_2022-09-03" , " territories_rvdss_since_2022-09-03.csv" ), row.names = FALSE , quote = 1 : 3 , na = " " )
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},
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error = function (e ) {
@@ -51,13 +67,14 @@ extra_datasets <- function() {
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# sk biweekly HR-level case snapshots
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tryCatch(
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{
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- # # process
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+ # process
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sk <- read_d(" raw_data/reports/sk/sk_crisp_report.csv" ) | >
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dplyr :: transmute(.data $ date_start , .data $ date_end , .data $ region , .data $ sub_region_1 , cases_weekly = .data $ cases ) | >
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dplyr :: filter(.data $ date_start > = as.Date(" 2022-12-25" ) & ! is.na(.data $ sub_region_1 ) & ! is.na(.data $ cases_weekly )) | >
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convert_hr_names()
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-
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- # # write file
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+ # max date
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+ sk <- filter_max_date(sk , " date_end" )
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+ # write file
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utils :: write.csv(sk , file.path(" extra_data" , " sk_biweekly_cases_hr" , " sk_biweekly_cases_hr.csv" ), row.names = FALSE , quote = 1 : 4 )
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rm(sk ) # clean up
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},
@@ -299,6 +316,8 @@ extra_datasets <- function() {
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tidyr :: pivot_wider(names_from = .data $ characteristics , values_from = .data $ value ) | >
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# sort by region (CAN first) and date
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dplyr :: arrange(dplyr :: if_else(.data $ region == " CAN" , 0 , 1 ), .data $ region , .data $ date )
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+ # max date
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+ statcan <- filter_max_date(statcan )
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# write dataset
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utils :: write.csv(statcan , file.path(" extra_data" , " statcan_excess_mortality" , " statcan_excess_mortality.csv" ), row.names = FALSE , quote = 1 : 2 )
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# write new release date
@@ -314,10 +333,14 @@ extra_datasets <- function() {
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# # hosp/ICU extra data report
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tryCatch(
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{
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+ # process
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d <- googlesheets4 :: read_sheet(
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ss = " 1ZTUb3fVzi6CLZAbU3lj6T6FTzl5Aq-arBNL49ru3VLo" ,
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sheet = " hospital_icu_extra" ,
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)
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+ # max date
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+ d <- filter_max_date(d )
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+ # write dataset
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utils :: write.csv(
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d ,
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file.path(" extra_data" , " hospital_icu_extra" , " hospital_icu_extra.csv" ),
@@ -345,6 +368,9 @@ extra_datasets <- function() {
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.data $ hosp_admissions ,
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.data $ icu_admissions
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)
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+ # max date
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+ d <- filter_max_date(d , " date_end" )
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+ # write dataset
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utils :: write.csv(
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d ,
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file.path(" extra_data" , " ns_extra_respiratory_watch" , " ns_extra_respiratory_watch.csv" ),
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