I can't replicate your problem with the sample data you have provided
library(dplyr)
sample_df <- data.frame(
stringsAsFactors = FALSE,
ID_1 = c(500353496,500353496,
500353496,500276744,500353496,500353496,500271964,
500310573),
ID_2 = c(13966089,13966089,13966089,
13966089,13966089,13966089,13966089,13966089),
Action = c("qc", "qc", "qc", "qc", "qc", "qc", "qc", "qc"),
Day = c("Tue", "Tue", "Tue", "Tue", "Wed", "Wed", "Wed", "Wed"),
Date_Time_Char = c("2019-02-12 23:56:44",
"2019-02-12 23:57:43","2019-02-12 23:58:45",
"2019-02-12 23:59:49","2019-02-13 00:00:31","2019-02-13 00:00:31",
"2019-02-13 00:01:09","2019-02-13 00:01:39"),
Date_Time_POSIXct = c("2019-12-02 23:56:44",
"2019-12-02 23:57:43","2019-12-02 23:58:45",
"2019-12-02 23:59:49", NA, NA, NA, NA)
)
sample_df %>%
mutate(new_column = as.POSIXct(Date_Time_Char))
#> ID_1 ID_2 Action Day Date_Time_Char Date_Time_POSIXct
#> 1 500353496 13966089 qc Tue 2019-02-12 23:56:44 2019-12-02 23:56:44
#> 2 500353496 13966089 qc Tue 2019-02-12 23:57:43 2019-12-02 23:57:43
#> 3 500353496 13966089 qc Tue 2019-02-12 23:58:45 2019-12-02 23:58:45
#> 4 500276744 13966089 qc Tue 2019-02-12 23:59:49 2019-12-02 23:59:49
#> 5 500353496 13966089 qc Wed 2019-02-13 00:00:31 <NA>
#> 6 500353496 13966089 qc Wed 2019-02-13 00:00:31 <NA>
#> 7 500271964 13966089 qc Wed 2019-02-13 00:01:09 <NA>
#> 8 500310573 13966089 qc Wed 2019-02-13 00:01:39 <NA>
#> new_column
#> 1 2019-02-12 23:56:44
#> 2 2019-02-12 23:57:43
#> 3 2019-02-12 23:58:45
#> 4 2019-02-12 23:59:49
#> 5 2019-02-13 00:00:31
#> 6 2019-02-13 00:00:31
#> 7 2019-02-13 00:01:09
#> 8 2019-02-13 00:01:39
Created on 2020-10-07 by the reprex package (v0.3.0)
Can you please provide a proper REPRoducible EXample (reprex) illustrating your issue?