Splitting Timestamp Column into Separate Date and Time Columns

Splitting unrecognized timestamp column into separate date and time columns

Looks like you can just pass the format:

pd.to_datetime(df['TimeDate'], format='%H:%M:%S (%m/%d/%Y)').dt.date

Output:

0    2018-01-01
1    2018-01-01
2    2018-01-01
Name: TimeDate, dtype: object

Split date-time column into Date and time variables

df$Date <- as.Date(df$Start) # already got this one from the answers above
df$Time <- format(as.POSIXct(df$Start), format = "%H:%M:%S") 

Use as.Date to convert 'Start' to a variables of class Date. For the time variable, we first convert 'Start' to POSIXct. Then use format to extract the time component as a string.

Splitting datetime in csv to separate date and time columns

When reading, use pd.read_csv with parse_dates and infer_datetime_format as True.

Data = pd.read_csv('csv_date.csv', parse_dates=['Time_Stamp'], infer_datetime_format=True)

Next, you can just extract the date & time:

Data['Date'] = Data.Time_Stamp.dt.date
Data['Time'] = Data.Time_Stamp.dt.time

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