R/funcs_add_new_data_series.R
In unicef-drp/CME.assistant: Reusable Assisting Functions for Data Analysis
Defines functions
add.new.series.by.ID
add.new.series.by.name
add.new.series.nmr
add.new.series.imr
add.new.series.u5mr
add.Original.Series.Name
revise.age.group
rbinddatasetNMR
rbinddataset
Documented in
add.new.series.by.ID
add.new.series.by.name
add.new.series.imr
add.new.series.nmr
add.new.series.u5mr
add.Original.Series.Name
rbinddataset
rbinddatasetNMR
revise.age.group
# functions to add new entries to master datasets for U5MR, IMR, NMR
# Add new series ----------------------------------------------------------
#' Row-bind two datasets, check duplicated keys and set order
#'
#' @param dt_master master dataset
#' @param dt_new new entries
#' @return `dt1` as `rbind(dt_master, dt_new)`
#' @export rbinddataset
rbinddataset <- function(dt_master, dt_new){
message("old nrow:", nrow(dt_master))
dt1 <- rbind(dt_master, dt_new)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
message("new nrow:", nrow(dt1))
if(nrow(dt_master) + nrow(dt_new) != nrow(dt1)) warning("check row numbers ")
return(dt1)
}
#' Row-bind two datasets for NMR with slight changes, check duplicated keys, set
#' order
#'
#' @param dt_master master dataset
#' @param dt_new new entries
#' @return `dt1` as `rbind(dt_master, dt_new)`
#' @export rbinddatasetNMR
rbinddatasetNMR <- function(dt_master, dt_new){
message("old nrow:", nrow(dt_master))
dt1 <- rbind(dt_master, dt_new)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
setorder(dt1, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
message("new nrow:", nrow(dt1))
if(nrow(dt_master) + nrow(dt_new) != nrow(dt1)) warning("check row numbers ")
return(dt1)
}
#' By default remove 25-34 and 10-19 age group in `dt_new_entries` for indirect
#' estimates
#'
#' function used by `add.new.series` functions, remove unwanted age groups
#' @param dt_new_entries dt of new entries to be added
#' @return dt_new_entries with 25-34 and 10-19 removed
#' @export revise.age.group
revise.age.group <- function(dt_new_entries){
if(nrow(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women=="25-34"])>0){
message("Remove AOW group '25-34' for ", paste(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("25-34"), unique(IGME_Key)], collapse = ", "))
dt_new_entries <- dt_new_entries[!(grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("25-34")), ]
}
if(nrow(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("10-19", "19-Oct"), ])>0){
message("Remove AOW group '10-19' for ", paste(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("10-19", "19-Oct"), unique(IGME_Key)], collapse = ", "))
dt_new_entries <- dt_new_entries[!(grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("10-19", "19-Oct")), ]
}
return(dt_new_entries)
}
#' Add an original series name
#'
#' Add `Original.Series.Name` column by the supplied `ori_name` argument
#'
#' @param dt_new_entries dt of new entries to be added
#' @param ori_name value for Original.Series.Name
#' @return dt_new_entries
#' @export add.Original.Series.Name
add.Original.Series.Name <- function(dt_new_entries, ori_name){
dt_new_entries[, Original.Series.Name:= as.character(Original.Series.Name)]
dt_new_entries[, Original.Series.Name:= ori_name]
return(dt_new_entries)
}
#' Add new U5MR or IMR entries (dt_new_entries)
#'
#' @param dt_master the U5MR master dataset
#' @param dt_new_entries dt of new entries to be added
#' @param remove_old if TRUE, remove old entries, if FALSE, set old entries to invisible and excluded
#' @return the new dt_master
#' @export add.new.series.u5mr
add.new.series.u5mr <- function(
dt_master,
dt_new_entries,
remove_old = FALSE
){
nrow_master_old <- copy(nrow(dt_master))
message("original nrow:", nrow_master_old)
dt_new_entries <- revise.age.group(dt_new_entries)
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# check reference date
if(dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, .N] >0){
warning("Might need to set invisible for data point more than 25 years prior to average date of the survey: ",
dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, IGME_Key[1]])
}
nrow_old <- nrow(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key),])
if(nrow_old > 0){
if(remove_old){
message("Remove ", nrow_old, " existing (perhaps old) entries: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)], collapse = ", "))
dt_master <- dt_master[!IGME_Key %in% unique(dt_new_entries$IGME_Key)]
message("nrow after removing old entries:", nrow(dt_master))
} else {
# print those existing ones that are changed to 0
message("Change inclusion and visible for old entries to 0: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)],
collapse = ", "))
dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key), Inclusion:=0]
dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key), Visible := 0]
}
}
dt1 <- rbindlist(list(dt_master, dt_new_entries), use.names = TRUE)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
message("Newly added:", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow:", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_master) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
#' Add new IMR entries (dt_new_entries), now the same function as
#' `add.new.series.u5mr`
#'
#' Still kept in case needed in the future in case need to differentiate IMR
#' from U5MR process
#'
#' @param dt_IMR the IMR master dataset
#' @param dt_new_entries dt of new entries to be added
#' @param remove_old if TRUE, remove old entries, if FALSE, set old entries to
#' invisible and excluded
#' @return the new dt_IMR
#' @export add.new.series.imr
add.new.series.imr <- function(
dt_IMR,
dt_new_entries,
remove_old = FALSE
){
nrow_master_old <- copy(nrow(dt_IMR))
message("original nrow:", nrow(nrow_master_old))
dt_new_entries <- revise.age.group(dt_new_entries)
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# dt_new_entries$To.be.adjusted
# dt_IMR[, table(To.be.adjusted, useNA = "ifany")]
# dt_IMR$To.be.adjusted <- NA
if(nrow(dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key),]) > 0){
if(remove_old){
message("Remove existing (possibly old) entries: ",
paste(dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)], collapse = ", "))
dt_IMR <- dt_IMR[!IGME_Key %in% unique(dt_new_entries$IGME_Key)]
} else {
# print those existing ones that are changed to 0
message("Change inclusion and visible for old entries to 0: ",
paste(dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)],
collapse = ", "))
dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key), Inclusion:=0]
dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key), Visible := 0]
}
}
message("nrow after removing old entries:", nrow(dt_IMR))
dt1 <- rbindlist(list(dt_IMR, dt_new_entries), use.names = TRUE)
dt1[duplicated(dt1), unique(IGME_Key)]
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
message("Newly added:", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow:", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_IMR) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
#' Add new NMR entries (`dt_new_entries`)
#'
#' @param dt_nmr the NMR master dataset
#' @param dt_new_entries dt of new entries to be added
#' @param remove_old if TRUE, remove old entries, if FALSE, set old entries to
#' invisible and excluded
#' @return the new dt_nmr_new
#' @export add.new.series.nmr
add.new.series.nmr <- function(
dt_nmr,
dt_new_entries,
remove_old = FALSE
){
nrow_master_old <- copy(nrow(dt_nmr))
message("old nrow:", nrow_master_old)
dt_new_entries <- revise.age.group(dt_new_entries)
dt_new_entries <- create.IGME.key(dt_new_entries)
# mark MM adjustments
dt_new_entries[, Adjustment.in.U5MR:=as.character(Adjustment.in.U5MR)]
dt_new_entries[Country.Code%in%hiv.iso, Adjustment.in.U5MR:= "MM adjustment"]
key0s <- dt_new_entries[, unique(IGME_Key)]
if(nrow(dt_nmr[IGME_Key %in% key0s,]) > 0){
if(remove_old){
message("Remove existing (possibly old) entries: ",
paste(dt_nmr[IGME_Key %in% key0s, unique(IGME_Key)],
collapse = ", "))
dt_nmr <- dt_nmr[!IGME_Key %in% key0s]
} else {
# print those existing ones that are changed to 0
message("Change inclusion and visible for old entries to 0: ",
paste(dt_nmr[IGME_Key %in% key0s, unique(IGME_Key)],
collapse = ", "))
dt_nmr[IGME_Key %in% key0s, Inclusion:=0]
dt_nmr[IGME_Key %in% key0s, Visible := 0]
}
}
dt_nmr_new <- rbindlist(list(dt_nmr, dt_new_entries), fill = TRUE, use.names = TRUE)
if(nrow(dt_nmr) + nrow(dt_new_entries) != nrow(dt_nmr_new)) warning("check row numbers ")
if(ncol(dt_nmr) != ncol(dt_new_entries)) warning("check col numbers ")
setorder(dt_nmr_new, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
message("old ncol:", ncol(dt_nmr))
message("new ncol:", ncol(dt_nmr_new))
message("Newly added:", paste(key0s, collapse = ", "))
message("new nrow:", nrow(dt_nmr_new), " -adding- ", nrow(dt_nmr_new) - nrow_master_old)
return(dt_nmr_new)
}
#' Add new series, match by both `IGME_Key` and `Series.Name`
#'
#' This is a very strict match
#'
#' @param dt_master master dataset
#' @param dt_new_entries new entries
#' @param old_entries_action default to "hide", set old series (matched by both
#' `IGME_Key` and `Series.Name`) to invisible = 0 and inclusion = 0; if
#' "remove", remove old series; if "no_change": leave as it is
#'
#' @export
add.new.series.by.name <- function(
dt_master,
dt_new_entries,
old_entries_action = "no_change"
){
dt_master <- copy(dt_master)
nrow_master_old <- copy(nrow(dt_master))
if(!old_entries_action%in%c("hide", "remove", "no_change"))stop("Choose action from: ", paste(c("hide", "remove", "no_change"), collapse =", "))
message("original nrow:", nrow(dt_master))
dt_new_entries <- revise.age.group(dt_new_entries)
# if(trim_series_name){
# strings_to_remove <- " \\(calendar year\\)| \\(Adjusted\\)| \\(MM adjusted\\)| \\(NN adjusted\\)| \\(Preliminary\\)| \\(preliminary\\)| \\(LQ\\)| Excluding South Zone"
# dt_master[, Series.Name := gsub(strings_to_remove, "", Series.Name)]
# dt_master[, IGME_Key := gsub(strings_to_remove, "", IGME_Key)]
# }
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# check reference date
if(dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, .N] >0){
warning("Might need to set invisible for data point more than 25 years prior to average date of the survey: ",
dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, IGME_Key[1]])
}
# number of old rows?
nrow_old <- dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key)
& Series.Name%in%unique(dt_new_entries$Series.Name), .N]
if(nrow_old > 0){
if(old_entries_action == "hide"){
message("Change inclusion and visible for old entries to 0: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key)
& Series.Name%in%unique(dt_new_entries$Series.Name), unique(Series.Name)],
collapse = ", "))
dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key) &
Series.Name%in%unique(dt_new_entries$Series.Name),
`:=`(Inclusion = 0, Visible = 0)]
} else if (old_entries_action == "remove"){
message("Remove old series: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key)
& Series.Name%in%unique(dt_new_entries$Series.Name), unique(Series.Name)],
collapse = ", "))
message("Remove old rows: ", nrow_old)
dt_master <- dt_master[!(IGME_Key %in% unique(dt_new_entries$IGME_Key) &
Series.Name%in%unique(dt_new_entries$Series.Name)),]
} else {
message("Old series unchanged.")
}
}
dt1 <- rbindlist(list(dt_master, dt_new_entries), fill = TRUE, use.names = TRUE)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
if(dt_master$Indicator[1] == "log NMR/(U5MR-NMR)" ){
# sort different for NMR
setorder(dt1, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
} else {
# for u5 and older children (B3 system)
if("Inclusion.U5MR" %in% colnames(dt1)){
setorder(dt1, Country.Name, -Indicator, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion.U5MR)
} else {
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
}
}
message("newly added ", nrow(dt_new_entries), " rows: ", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow: ", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_master) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
#' Add new series, match by only `DataCatalogID`
#'
#' This is a lose match. It's occasionally useful because sometimes you
#' revise the series.name for the new series
#'
#' @param dt_master master dataset
#' @param dt_new_entries new entries
#' @param old_entries_action default to "hide", set old series (matched by both
#' `IGME_Key` and `Series.Name`) to invisible = 0 and inclusion = 0; if
#' "remove", remove old series; if "no_change": leave as it is
#' @export
add.new.series.by.ID <- function(
dt_master,
dt_new_entries,
old_entries_action = "no_change"
){
dt_master <- copy(dt_master)
nrow_master_old <- copy(nrow(dt_master))
if(!old_entries_action%in%c("hide", "remove", "no_change"))stop("Choose action from: ", paste(c("hide", "remove", "no_change"), collapse =", "))
message("original nrow:", nrow(dt_master))
dt_new_entries <- revise.age.group(dt_new_entries)
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# check reference date
if(dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, .N] >0){
warning("Might need to set invisible for data point more than 25 years prior to average date of the survey: ",
dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, IGME_Key[1]])
}
# number of old rows?
nrow_old <- dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID), .N]
if(nrow_old > 0){
if(old_entries_action == "hide"){
message("Change inclusion and visible for old entries to 0: ",
paste(dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID), unique(Series.Name)],
collapse = ", "))
dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID),
`:=`(Inclusion = 0, Visible = 0)]
} else if (old_entries_action == "remove"){
message("Remove old series: ",
paste(dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID), unique(Series.Name)],
collapse = ", "))
message("Remove old rows: ", nrow_old)
dt_master <- dt_master[!DataCatalogID %in% unique(dt_new_entries$DataCatalogID),]
} else {
message("Old series unchanged.")
}
}
dt1 <- rbindlist(list(dt_master, dt_new_entries), fill = TRUE, use.names = TRUE)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
if(dt_master$Indicator[1] == "log NMR/(U5MR-NMR)" ){
# sort different for NMR
setorder(dt1, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
} else {
# for u5 and older children (B3 system)
if("Inclusion.U5MR" %in% colnames(dt1)){
setorder(dt1, Country.Name, -Indicator, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion.U5MR)
} else {
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
}
}
message("newly added ", nrow(dt_new_entries), " rows: ", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow: ", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_master) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
unicef-drp/CME.assistant documentation built on June 13, 2025, 8:06 p.m.
R Package Documentation
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Defines functions add.new.series.by.ID add.new.series.by.name add.new.series.nmr add.new.series.imr add.new.series.u5mr add.Original.Series.Name revise.age.group rbinddatasetNMR rbinddataset
Documented in add.new.series.by.ID add.new.series.by.name add.new.series.imr add.new.series.nmr add.new.series.u5mr add.Original.Series.Name rbinddataset rbinddatasetNMR revise.age.group
# functions to add new entries to master datasets for U5MR, IMR, NMR
# Add new series ----------------------------------------------------------
#' Row-bind two datasets, check duplicated keys and set order
#'
#' @param dt_master master dataset
#' @param dt_new new entries
#' @return `dt1` as `rbind(dt_master, dt_new)`
#' @export rbinddataset
rbinddataset <- function(dt_master, dt_new){
message("old nrow:", nrow(dt_master))
dt1 <- rbind(dt_master, dt_new)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
message("new nrow:", nrow(dt1))
if(nrow(dt_master) + nrow(dt_new) != nrow(dt1)) warning("check row numbers ")
return(dt1)
}
#' Row-bind two datasets for NMR with slight changes, check duplicated keys, set
#' order
#'
#' @param dt_master master dataset
#' @param dt_new new entries
#' @return `dt1` as `rbind(dt_master, dt_new)`
#' @export rbinddatasetNMR
rbinddatasetNMR <- function(dt_master, dt_new){
message("old nrow:", nrow(dt_master))
dt1 <- rbind(dt_master, dt_new)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
setorder(dt1, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
message("new nrow:", nrow(dt1))
if(nrow(dt_master) + nrow(dt_new) != nrow(dt1)) warning("check row numbers ")
return(dt1)
}
#' By default remove 25-34 and 10-19 age group in `dt_new_entries` for indirect
#' estimates
#'
#' function used by `add.new.series` functions, remove unwanted age groups
#' @param dt_new_entries dt of new entries to be added
#' @return dt_new_entries with 25-34 and 10-19 removed
#' @export revise.age.group
revise.age.group <- function(dt_new_entries){
if(nrow(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women=="25-34"])>0){
message("Remove AOW group '25-34' for ", paste(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("25-34"), unique(IGME_Key)], collapse = ", "))
dt_new_entries <- dt_new_entries[!(grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("25-34")), ]
}
if(nrow(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("10-19", "19-Oct"), ])>0){
message("Remove AOW group '10-19' for ", paste(dt_new_entries[grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("10-19", "19-Oct"), unique(IGME_Key)], collapse = ", "))
dt_new_entries <- dt_new_entries[!(grepl("Indirect", Series.Type, ignore.case = TRUE) & Age.Group.of.Women%in%c("10-19", "19-Oct")), ]
}
return(dt_new_entries)
}
#' Add an original series name
#'
#' Add `Original.Series.Name` column by the supplied `ori_name` argument
#'
#' @param dt_new_entries dt of new entries to be added
#' @param ori_name value for Original.Series.Name
#' @return dt_new_entries
#' @export add.Original.Series.Name
add.Original.Series.Name <- function(dt_new_entries, ori_name){
dt_new_entries[, Original.Series.Name:= as.character(Original.Series.Name)]
dt_new_entries[, Original.Series.Name:= ori_name]
return(dt_new_entries)
}
#' Add new U5MR or IMR entries (dt_new_entries)
#'
#' @param dt_master the U5MR master dataset
#' @param dt_new_entries dt of new entries to be added
#' @param remove_old if TRUE, remove old entries, if FALSE, set old entries to invisible and excluded
#' @return the new dt_master
#' @export add.new.series.u5mr
add.new.series.u5mr <- function(
dt_master,
dt_new_entries,
remove_old = FALSE
){
nrow_master_old <- copy(nrow(dt_master))
message("original nrow:", nrow_master_old)
dt_new_entries <- revise.age.group(dt_new_entries)
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# check reference date
if(dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, .N] >0){
warning("Might need to set invisible for data point more than 25 years prior to average date of the survey: ",
dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, IGME_Key[1]])
}
nrow_old <- nrow(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key),])
if(nrow_old > 0){
if(remove_old){
message("Remove ", nrow_old, " existing (perhaps old) entries: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)], collapse = ", "))
dt_master <- dt_master[!IGME_Key %in% unique(dt_new_entries$IGME_Key)]
message("nrow after removing old entries:", nrow(dt_master))
} else {
# print those existing ones that are changed to 0
message("Change inclusion and visible for old entries to 0: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)],
collapse = ", "))
dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key), Inclusion:=0]
dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key), Visible := 0]
}
}
dt1 <- rbindlist(list(dt_master, dt_new_entries), use.names = TRUE)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
message("Newly added:", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow:", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_master) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
#' Add new IMR entries (dt_new_entries), now the same function as
#' `add.new.series.u5mr`
#'
#' Still kept in case needed in the future in case need to differentiate IMR
#' from U5MR process
#'
#' @param dt_IMR the IMR master dataset
#' @param dt_new_entries dt of new entries to be added
#' @param remove_old if TRUE, remove old entries, if FALSE, set old entries to
#' invisible and excluded
#' @return the new dt_IMR
#' @export add.new.series.imr
add.new.series.imr <- function(
dt_IMR,
dt_new_entries,
remove_old = FALSE
){
nrow_master_old <- copy(nrow(dt_IMR))
message("original nrow:", nrow(nrow_master_old))
dt_new_entries <- revise.age.group(dt_new_entries)
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# dt_new_entries$To.be.adjusted
# dt_IMR[, table(To.be.adjusted, useNA = "ifany")]
# dt_IMR$To.be.adjusted <- NA
if(nrow(dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key),]) > 0){
if(remove_old){
message("Remove existing (possibly old) entries: ",
paste(dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)], collapse = ", "))
dt_IMR <- dt_IMR[!IGME_Key %in% unique(dt_new_entries$IGME_Key)]
} else {
# print those existing ones that are changed to 0
message("Change inclusion and visible for old entries to 0: ",
paste(dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key),
unique(IGME_Key)],
collapse = ", "))
dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key), Inclusion:=0]
dt_IMR[IGME_Key %in% unique(dt_new_entries$IGME_Key), Visible := 0]
}
}
message("nrow after removing old entries:", nrow(dt_IMR))
dt1 <- rbindlist(list(dt_IMR, dt_new_entries), use.names = TRUE)
dt1[duplicated(dt1), unique(IGME_Key)]
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
message("Newly added:", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow:", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_IMR) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
#' Add new NMR entries (`dt_new_entries`)
#'
#' @param dt_nmr the NMR master dataset
#' @param dt_new_entries dt of new entries to be added
#' @param remove_old if TRUE, remove old entries, if FALSE, set old entries to
#' invisible and excluded
#' @return the new dt_nmr_new
#' @export add.new.series.nmr
add.new.series.nmr <- function(
dt_nmr,
dt_new_entries,
remove_old = FALSE
){
nrow_master_old <- copy(nrow(dt_nmr))
message("old nrow:", nrow_master_old)
dt_new_entries <- revise.age.group(dt_new_entries)
dt_new_entries <- create.IGME.key(dt_new_entries)
# mark MM adjustments
dt_new_entries[, Adjustment.in.U5MR:=as.character(Adjustment.in.U5MR)]
dt_new_entries[Country.Code%in%hiv.iso, Adjustment.in.U5MR:= "MM adjustment"]
key0s <- dt_new_entries[, unique(IGME_Key)]
if(nrow(dt_nmr[IGME_Key %in% key0s,]) > 0){
if(remove_old){
message("Remove existing (possibly old) entries: ",
paste(dt_nmr[IGME_Key %in% key0s, unique(IGME_Key)],
collapse = ", "))
dt_nmr <- dt_nmr[!IGME_Key %in% key0s]
} else {
# print those existing ones that are changed to 0
message("Change inclusion and visible for old entries to 0: ",
paste(dt_nmr[IGME_Key %in% key0s, unique(IGME_Key)],
collapse = ", "))
dt_nmr[IGME_Key %in% key0s, Inclusion:=0]
dt_nmr[IGME_Key %in% key0s, Visible := 0]
}
}
dt_nmr_new <- rbindlist(list(dt_nmr, dt_new_entries), fill = TRUE, use.names = TRUE)
if(nrow(dt_nmr) + nrow(dt_new_entries) != nrow(dt_nmr_new)) warning("check row numbers ")
if(ncol(dt_nmr) != ncol(dt_new_entries)) warning("check col numbers ")
setorder(dt_nmr_new, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
message("old ncol:", ncol(dt_nmr))
message("new ncol:", ncol(dt_nmr_new))
message("Newly added:", paste(key0s, collapse = ", "))
message("new nrow:", nrow(dt_nmr_new), " -adding- ", nrow(dt_nmr_new) - nrow_master_old)
return(dt_nmr_new)
}
#' Add new series, match by both `IGME_Key` and `Series.Name`
#'
#' This is a very strict match
#'
#' @param dt_master master dataset
#' @param dt_new_entries new entries
#' @param old_entries_action default to "hide", set old series (matched by both
#' `IGME_Key` and `Series.Name`) to invisible = 0 and inclusion = 0; if
#' "remove", remove old series; if "no_change": leave as it is
#'
#' @export
add.new.series.by.name <- function(
dt_master,
dt_new_entries,
old_entries_action = "no_change"
){
dt_master <- copy(dt_master)
nrow_master_old <- copy(nrow(dt_master))
if(!old_entries_action%in%c("hide", "remove", "no_change"))stop("Choose action from: ", paste(c("hide", "remove", "no_change"), collapse =", "))
message("original nrow:", nrow(dt_master))
dt_new_entries <- revise.age.group(dt_new_entries)
# if(trim_series_name){
# strings_to_remove <- " \\(calendar year\\)| \\(Adjusted\\)| \\(MM adjusted\\)| \\(NN adjusted\\)| \\(Preliminary\\)| \\(preliminary\\)| \\(LQ\\)| Excluding South Zone"
# dt_master[, Series.Name := gsub(strings_to_remove, "", Series.Name)]
# dt_master[, IGME_Key := gsub(strings_to_remove, "", IGME_Key)]
# }
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# check reference date
if(dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, .N] >0){
warning("Might need to set invisible for data point more than 25 years prior to average date of the survey: ",
dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, IGME_Key[1]])
}
# number of old rows?
nrow_old <- dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key)
& Series.Name%in%unique(dt_new_entries$Series.Name), .N]
if(nrow_old > 0){
if(old_entries_action == "hide"){
message("Change inclusion and visible for old entries to 0: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key)
& Series.Name%in%unique(dt_new_entries$Series.Name), unique(Series.Name)],
collapse = ", "))
dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key) &
Series.Name%in%unique(dt_new_entries$Series.Name),
`:=`(Inclusion = 0, Visible = 0)]
} else if (old_entries_action == "remove"){
message("Remove old series: ",
paste(dt_master[IGME_Key %in% unique(dt_new_entries$IGME_Key)
& Series.Name%in%unique(dt_new_entries$Series.Name), unique(Series.Name)],
collapse = ", "))
message("Remove old rows: ", nrow_old)
dt_master <- dt_master[!(IGME_Key %in% unique(dt_new_entries$IGME_Key) &
Series.Name%in%unique(dt_new_entries$Series.Name)),]
} else {
message("Old series unchanged.")
}
}
dt1 <- rbindlist(list(dt_master, dt_new_entries), fill = TRUE, use.names = TRUE)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
if(dt_master$Indicator[1] == "log NMR/(U5MR-NMR)" ){
# sort different for NMR
setorder(dt1, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
} else {
# for u5 and older children (B3 system)
if("Inclusion.U5MR" %in% colnames(dt1)){
setorder(dt1, Country.Name, -Indicator, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion.U5MR)
} else {
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
}
}
message("newly added ", nrow(dt_new_entries), " rows: ", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow: ", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_master) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
#' Add new series, match by only `DataCatalogID`
#'
#' This is a lose match. It's occasionally useful because sometimes you
#' revise the series.name for the new series
#'
#' @param dt_master master dataset
#' @param dt_new_entries new entries
#' @param old_entries_action default to "hide", set old series (matched by both
#' `IGME_Key` and `Series.Name`) to invisible = 0 and inclusion = 0; if
#' "remove", remove old series; if "no_change": leave as it is
#' @export
add.new.series.by.ID <- function(
dt_master,
dt_new_entries,
old_entries_action = "no_change"
){
dt_master <- copy(dt_master)
nrow_master_old <- copy(nrow(dt_master))
if(!old_entries_action%in%c("hide", "remove", "no_change"))stop("Choose action from: ", paste(c("hide", "remove", "no_change"), collapse =", "))
message("original nrow:", nrow(dt_master))
dt_new_entries <- revise.age.group(dt_new_entries)
# recreate IGME Key
dt_new_entries <- create.IGME.key(dt_new_entries)
# check reference date
if(dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, .N] >0){
warning("Might need to set invisible for data point more than 25 years prior to average date of the survey: ",
dt_new_entries[(Average.date.of.Survey - Reference.Date > 25) & Visible==1, IGME_Key[1]])
}
# number of old rows?
nrow_old <- dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID), .N]
if(nrow_old > 0){
if(old_entries_action == "hide"){
message("Change inclusion and visible for old entries to 0: ",
paste(dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID), unique(Series.Name)],
collapse = ", "))
dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID),
`:=`(Inclusion = 0, Visible = 0)]
} else if (old_entries_action == "remove"){
message("Remove old series: ",
paste(dt_master[DataCatalogID %in% unique(dt_new_entries$DataCatalogID), unique(Series.Name)],
collapse = ", "))
message("Remove old rows: ", nrow_old)
dt_master <- dt_master[!DataCatalogID %in% unique(dt_new_entries$DataCatalogID),]
} else {
message("Old series unchanged.")
}
}
dt1 <- rbindlist(list(dt_master, dt_new_entries), fill = TRUE, use.names = TRUE)
dup_key <- dt1[duplicated(dt1), unique(IGME_Key)]
if(length(dup_key)>0) message("Notice duplicated series: ", paste(dup_key, collapse = ", "))
if(dt_master$Indicator[1] == "log NMR/(U5MR-NMR)" ){
# sort different for NMR
setorder(dt1, Country.Name, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, -Inclusion)
} else {
# for u5 and older children (B3 system)
if("Inclusion.U5MR" %in% colnames(dt1)){
setorder(dt1, Country.Name, -Indicator, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion.U5MR)
} else {
setorder(dt1, Country.Name, -Indicator, -Sex, -End.date.of.Survey, Series.Name, Series.Type, -Date.Of.Data.Added, -Reference.Date, - Inclusion)
}
}
message("newly added ", nrow(dt_new_entries), " rows: ", paste(unique(dt_new_entries$IGME_Key), collapse = ", "))
message("new nrow: ", nrow(dt1), " -adding- ", nrow(dt1) - nrow_master_old)
if(nrow(dt_master) + nrow(dt_new_entries) != nrow(dt1)) warning("check row numbers match")
return(dt1)
}
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