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Part of "utils/Rt_review_exclusions.R" is dedicated to creating a point exclusions outlier csv file for the old pipeline (as opposed to manually typing in the point exclusions). See below for code segment.
When we retire the old pipeline we should make sure to delete this segment as well as it will no longer serve a purpose
`
Temp old-pipeline csv generator#####
# Save a version in temp folder.
# Need to copy and paste this in current blank outlier csv file
point_exclusions <- combined_df |>
dplyr::filter(!is.na(drop_dates)) |>
dplyr::mutate(
raw_confirm = NA,
clean_confirm = NA
) |>
dplyr::select(
reference_date,
report_date,
"geo_value",
"pathogen"
) |>
dplyr::mutate(
geo_value = tolower(geo_value),
pathogen = dplyr::case_when(pathogen == "Influenza" ~ "flu",
pathogen == "COVID-19" ~ "covid",
.default = as.character(pathogen)
)
)
message(paste0(
"saving ",
paste0(lubridate::ymd(report_date), ".csv"),
" in ", containter_name,
"/temp_outliers_for_old"
))
AzureStor::storage_write_csv(
cont = cont,
object = point_exclusions,
file = file.path(
"temp_outliers_for_old",
paste0(lubridate::ymd(report_date), ".csv")
)
)
`
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Part of "utils/Rt_review_exclusions.R" is dedicated to creating a point exclusions outlier csv file for the old pipeline (as opposed to manually typing in the point exclusions). See below for code segment.
When we retire the old pipeline we should make sure to delete this segment as well as it will no longer serve a purpose
`
Temp old-pipeline csv generator#####
`
The text was updated successfully, but these errors were encountered: