Generating a non BOOLEAN result to a CSV using R - sql

Question

I have taken over a report from a college who has left the organisation. The report is written in R, it accesses an Oracle database, and runs SQL scripts into R.
The R code then pushes the data out to a csv. The difficulty I have is that it is pushing TRUE, FALSE or a blank cell to the csv. I want to update the code to print Updated, Not Updated, or a blank cell. I am struggling to find the correct place to make these updates.
Below is the code that generates the CSV, as well as a snippet that the code refers to, that may be generating the TRUE and FALSE that I referred to. Any help would be greatly appreciated.
# prepare a data frame based on Today_Active_address_wf for printing.
ForPrintONLYToday_Active_address_wf <- Today_Active_address_wf
# add an empty row to dataframe
ForPrintONLYToday_Active_address_wf[nrow(ForPrintONLYToday_Active_address_wf)+1, ] <- NA
# write today Active address wf data frame to .csv file
filename <- paste("Daily Address Change Workflow Report___", format(Sys.time(), "%Y-%m-%d__%Hh%M"), ".csv", sep ="")
filelocation <- "\\\\DCV-PANAPP-P001\\File Share\\BIS\\Data Administration\\Daily Workflow Reports\\"
filewrite <- paste(filelocation, filename, sep = "")
write.csv(ForPrintONLYToday_Active_address_wf, file = filewrite, row.names = FALSE, na="")
# add additional info (totals for each column)
addInfo1 <- c("Total_duplicated_WF"
,"Total_inconsistent_wf_addr"
,"Total_QAS_validated_addr"
,"Total_invalid_Wf_addr_date"
,"Postal_unmatched_with_valid_WF"
,"Total_No_Policy"
,"Total_home_risk"
,"Total_motor_risk"
,"Total_risk_addr_change"
)
addInfo2 <- c(sum(ForPrintONLYToday_Active_address_wf$dupCloseFlag, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$inconsistentDataFlag, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$WF_ADDRESS_VALIDATED, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$valid_addr_date == FALSE, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$MatchedPO_WF_addr == FALSE & ForPrintONLYToday_Active_address_wf$valid_addr_date == TRUE, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$hasNOpolicy, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$hasHomeRisk, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$hasMotorRisk, na.rm = TRUE)
,sum(ForPrintONLYToday_Active_address_wf$riskAddrChange_Flag, na.rm = TRUE)
)
addInfoTable <- as.table(setNames(addInfo2, addInfo1))
write.table(addInfoTable, file = filewrite, row.names = FALSE, col.names = FALSE, na="",append = TRUE, sep = ":,")
### Additional Function ###
# function that converts "Y" to TRUE and "N" to FALSE
yn_to_logical <- function(x) {
y <- rep.int(NA, length(x))
y[x == "Y"] <- TRUE
y[x == "N"] <- FALSE
y
} '
Thanks all, I know this is a pile of code, but R is not my strong point.

Answer 1

There are many ways to replace one set of values with another set of values. Here is one way:
# Create a simple data set that contains a column with "Y","N" and NAs (missing values)
df <- data.frame(x = sample(c("Y","N",NA), 10, replace = TRUE),
val = rnorm(10) )
df
# x val
# 1 N 0.56554865
# 2 <NA> -1.81437749
# 3 Y -1.21385694
# 4 Y -1.30173545
# 5 N -0.18994710
# 6 N -0.67519801
# 7 <NA> 0.02093869
# 8 N 0.69082204
# 9 Y 0.01715652
# 10 Y 1.34007199
# use function recode() from car package
library(car)
df$x <- recode(df$x, " 'Y' = 'Updated'; 'N' = 'Not Updated'")
df
# x val
# 1 Not Updated 0.56554865
# 2 <NA> -1.81437749
# 3 Updated -1.21385694
# 4 Updated -1.30173545
# 5 Not Updated -0.18994710
# 6 Not Updated -0.67519801
# 7 <NA> 0.02093869
# 8 Not Updated 0.69082204
# 9 Updated 0.01715652
# 10 Updated 1.34007199