How to combine date and time columns into a single datetime column in Pandas?

Combining Date and Time Columns in Pandas

Problem:

You have a Pandas dataframe with separate columns for date and time. You want to combine these columns to create a new column containing the combined datetime values.

Solution:

There are two common approaches to combine date and time columns in Pandas:

1. Using Concatenation with pd.to_datetime():

   a. Concatenate the 'Date' and 'Time' columns with a space as a separator.
   b. Convert the concatenated string to a datetime object using pd.to_datetime().

   df['Combined_DateTime'] = pd.to_datetime(df['Date'] + ' ' + df['Time'])

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2. Using pd.to_datetime() with a Format String:

   a. Convert the 'Date' and 'Time' columns to datetime objects separately using pd.to_datetime().
   b. Set the format parameter to specify the format of the datetime string.

   df['Date'] = pd.to_datetime(df['Date'], format='%m-%d-%Y')
   df['Time'] = pd.to_datetime(df['Time'], format='%H:%M:%S')
   df['Combined_DateTime'] = pd.to_datetime(df['Date'] + ' ' + df['Time'])

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Tips:

• You can use %%timeit to benchmark the performance of the different approaches.
• If the 'Date' and 'Time' columns contain NaNs or invalid values, consider using the errors parameter in pd.to_datetime() to handle such cases.

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