How to vectorize this loop

Question

The following is the ConvertToLocal function, which accepts a Names and Times data frame and performs time zone conversion with some if statements. How can I vectorize this so that I don't use loops?

Thanks.

Here is the code:

 ConvertToLocal<-function(data) { Name<-data$Name Time<-data$Time for(i in 1:length(Name)) { if(Name[i]== "Bob" | Name[i] == "Al" ) { Time[i]<-format(Time[i],tz="America/Los_Angeles") }else if (Name[i] == "Mike" | Name[i] == "Tom" ) { Time[i]<-format(Time[i],tz="Asia/Singapore") }else if (Name[i] == "Fred") { Time[i]<- format(Time[i],tz="Europe/London") } } return(Time) } Time<-c(as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC"),as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC"),as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC"),as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC")) Name<-c("BOB","Al","Mike","Fred") data<- data.frame(Name = Name, Time = Time) ConvertToLocal(data) 

Answer 1

Another approach would be to create a lookup table and then use mapply

Using a data table to simplify merging

 library(data.table) DT <- data.table(data) TimeZones <-rbindlist(list( data.table(Name = c('Bob', 'Al'), tz = 'America/Los_Angeles' ), data.table(Name = c('Mike', 'Tom'), tz = 'Asia/Singapore'), data.table(Name = 'Fred', tz = 'Europe/London') )) setkey(DT, Name) setkey(TimeZones, Name) final <- TimeZones[DT][, local := mapply(Time, tz = tz, FUN = format)] final # Name tz Time local # 1: Al America/Los_Angeles 2015-02-04 01:27:35 2015-02-03 06:27:35 # 2: Bob America/Los_Angeles 2015-02-04 01:27:35 2015-02-03 06:27:35 # 3: Fred Europe/London 2015-02-04 01:27:35 2015-02-03 14:27:35 # 4: Mike Asia/Singapore 2015-02-04 01:27:35 2015-02-03 22:27:35 

Answer 2

You can easily do 3 conversions in 3 separate vectorized steps.

 Time <- c(as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC"), as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC"), as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC"), as.POSIXct("2015-02-03 14:27:35.943", tz = "UTC")) Name <- c("BOB","Al","Mike","Fred") data <- data.frame(Name = Name, Time = Time) ConvertToLocal <- function(dat) { tzs <- c("America/Los_Angeles", "Asia/Singapore", "Europe/London") groups <- list(c("Bob", "Al"), c("Mike", "Tom"), c("Fred")) for (i in seq_along(groups)) { take <- dat$Name %in% groups[[i]] dat$Time[take] <- format(dat$Time[take], tz = tzs[i], usetz = TRUE) } dat } 

which gives, for example, data

 > ConvertToLocal(data) Name Time 1 BOB 2015-02-03 08:27:35.943 2 Al 2015-02-03 06:27:35.943 3 Mike 2015-02-03 22:27:35.943 4 Fred 2015-02-03 14:27:35.943 

Answer 3

try the following:

 ConvertToLocal<-function(data) { Name<-data$Name Time<-data$Time indx <- Name== "Bob" | Name == "Al" Time[indx]<-format(Time[indx],tz="America/Los_Angeles") indx <- Name == "Mike" | Name == "Tom" Time[indx]<-format(Time[indx],tz="Asia/Singapore") indx <- Name == "Fred" Time[indx]<- format(Time[indx],tz="Europe/London") return(Time) } 

Answer 4

Here is another option using mapply and ifelse :

  Name <- data$Name Time <- data$Time mapply(function(x,y)format(x,tz=y),Time, ifelse(Name %in% c("Bob","Al" ), "America/Los_Angeles", ifelse(Name %in% c("Mike","Tom" ), "Asia/Singapore", ifelse(Name == "Fred","Europe/London",""))))