I have many dataframes imported from csv files, all having one similar column name: ActivityHour. Its class was imported as character, but I want to change it to date and time with the lubridate mdy_hms() function in R. So, I created a list of the dataframes and ran a for loop so that I do not write the code for each dataframe. However, whenever I try to run class() for ActivityHour for any of these dataframes in the terminal after running the for loop, the output is still character. Interestingly, if I include the class() function inside the for loop, the class of ActivityHour does become POSIXct. I would really appreciate your help! Thank you!
Here is the code I tried to run; I will use sample data:
hourlyIntensities1 <- data.frame(
Id = c(1,2,3,4),
ActivityHour = c("3/12/2016 12:00:00 AM","3/12/2016 2:00:00 AM","3/12/2016 4:00:00 PM","3/13/2016 1:00:00 AM"),
Intensity = c(2,5,3,9)
)
hourlyIntensities2 <- data.frame(
Id = c(1,2,3,4),
ActivityHour = c("4/12/2016 12:00:00 AM","4/12/2016 2:00:00 AM","4/12/2016 4:00:00 PM","4/13/2016 1:00:00 AM"),
Intensity = c(7,4,8,2)
)
hourlySteps1 <- data.frame(
Id = c(1,2,3,4),
ActivityHour = c("3/12/2016 12:00:00 AM","3/12/2016 2:00:00 AM","3/12/2016 4:00:00 PM","3/13/2016 1:00:00 AM"),
Steps = c(950, 784, 631, 982)
)
hourlySteps2 <- data.frame(
Id = c(1,2,3,4),
ActivityHour = c("3/12/2016 12:00:00 AM","3/12/2016 2:00:00 AM","3/12/2016 4:00:00 PM","3/13/2016 1:00:00 AM"),
Steps = c(740, 650, 875, 265)
)
hourly <- list(hourlyIntensities1, hourlyIntensities2, hourlySteps1, hourlySteps2)
for (df in hourly) {
df$ActivityHour <- mdy_hms(df$ActivityHour)
print(class(df$ActivityHour))
}
I got the following result:
[1] "POSIXct" "POSIXt"
[1] "POSIXct" "POSIXt"
[1] "POSIXct" "POSIXt"
[1] "POSIXct" "POSIXt"
Then, I ran the following...
print(class(hourlyIntensities1$ActivityHour))
...only to get this:
[1] "character"
If you (think you) need to change objects in your global environment in such way, you can loop through a list of object names and use get() & assign():
(hourly <- ls(pattern = "^hourly.*"))
#> [1] "hourlyIntensities1" "hourlyIntensities2" "hourlySteps1"
#> [4] "hourlySteps2"
str(hourlyIntensities1$ActivityHour)
#> chr [1:4] "3/12/2016 12:00:00 AM" "3/12/2016 2:00:00 AM" ...
for (df in hourly){
message("Updating ", df)
assign(df, transform(get(df), ActivityHour = lubridate::mdy_hms(ActivityHour)))
}
#> Updating hourlyIntensities1
#> Updating hourlyIntensities2
#> Updating hourlySteps1
#> Updating hourlySteps2
str(hourlyIntensities1$ActivityHour)
#> POSIXct[1:4], format: "2016-03-12 00:00:00" "2016-03-12 02:00:00" "2016-03-12 16:00:00" ...
More idiomatic approach would be building your workflow on top of lists and lapply() / purrr::map() & friends, perhaps just few threads to start with (it's also worth checking answers with latest updates, not just with highest number of votes) :
How to import multiple .csv files at once?
How do I make a list of data frames?