Format Date field from excel into a timeseries into csv

format_time.R

# If not installed please install the gdata package by using this command
#install.packages("gdata")

require(gdata)

#df = read.xls("demo.txt", sheet = 1, header = TRUE, method="tab")
df = read.csv("demo.txt", header = TRUE, sep="\t")


numberOfDays <- function(date) {
    m <- format(date, format="%m")

    while (format(date, format="%m") == m) {
        date <- date + 1
    }

    return(as.integer(format(date - 1, format="%d")))
}

newDates = NULL
dates = as.character(df$PERIOD)

total = length(dates)
pb <- txtProgressBar(min = 0, max = total, style = 3)

for (i in 1:length(dates)) {
 #make sure we dont have a trailing space
 dates[i] = trimws(dates[i])
 #append this row with a fake day in order to use it as a date object
 dates[i] = paste(dates[i], "-01", sep="")
 #now get the number of days from this date
 days_in_month = numberOfDays(as.Date(dates[i]))
 #now cut that fake day and paste the new one
 dates[i] = substr(dates[i],1,nchar(dates[i])-3)
 #and add the number of days per month
 dates[i] = paste(dates[i], paste("-",days_in_month, sep=""), sep="")
 #fill the new list
 newDates[i] = as.character(as.Date(dates[i], format="%Y-%m-%d"))

 Sys.sleep(0.1)
 setTxtProgressBar(pb, i)
}

close(pb)
# Now that we have the new dates format we can replace the entire Date columbiadatascience

df$PERIOD = format(as.Date(newDates), "%d-%h-%Y")

write.csv(df, file = "date_formatted.csv")