I want to use sapply (or something similar) to convert certain columns to POSIXct in an R data.frame but maintain the datetime format of the columns. When I do it currently, it converts the format to numeric. How can I do this? An example is below.
#sample dataframe
df <- data.frame(
var1=c(5, 2),
char1=c('he', 'she'),
timestamp1=c('2019-01-01 20:30:08', '2019-01-02 08:27:34'),
timestamp2=c('2019-01-01 12:24:54', '2019-01-02 10:57:47'),
stringsAsFactors = F
)
#Convert only columns with 'timestamp' in name to POSIXct
df[grep('timestamp', names(df))] <- sapply(df[grep('timestamp', names(df))], function(x) as.POSIXct(x, format='%Y-%m-%d %H:%M:%S'))
df
var1 char1 timestamp1 timestamp2
1 5 he 1546392608 1546363494
2 2 she 1546435654 1546444667
Note: I can use as.posixlt instead of as.posixctand it works, but I want the data in POSIXct format. I also tried converting to POSIXlt first and then to POSIXct, but that also ended up converting the columns to numeric.
Use lapply rather than sapply. The "s" in sapply is for simplify and it turns the result into a matrix but sapply can't create a matrix of POSIXct values so it gets cast to a simple numeric matrix. But if you keep it a list, you don't lose the class.
df[grep('timestamp', names(df))] <- lapply(df[grep('timestamp', names(df))], function(x) as.POSIXct(x, format='%Y-%m-%d %H:%M:%S'))
You could also do this fairly easily with dplyr
library(dplyr)
df %>% mutate_at(vars(contains("timestamp")), as.POSIXct)
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