How can I combine date and time columns into a single timestamp in Pandas?

Combine Date and Time Columns in Pandas

In data analytics, combining date and time data into a single timestamp is often necessary. Pandas, a powerful data manipulation library in Python, provides multiple ways to achieve this.

One direct method is to use Python's ' ' operator to concatenate the 'Date' and 'Time' columns, as shown below:

new_column = df['Date'] + ' ' + df['Time']

This results in a string column containing the combined date and time information. However, for data operations, it's more convenient to convert the string to a datetime object.

Using pd.to_datetime() with the default settings assumes a specific date-time format. However, in this case, the combined string does not match the default format. Therefore, it is necessary to specify the exact format:

new_column = pd.to_datetime(new_column, format='%m-%d-%Y %H:%M:%S')

Alternatively, one can also use pd.to_datetime() with the error argument set to "coerce" to automatically convert any values that cannot be parsed as a datetime. However, using a more explicit format is generally faster and more reliable.

With this approach, the combined date-time information can now be treated as a datetime column, enabling further manipulation and analysis in Pandas.

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