Create Datetime Column from Two Columns using Python

Introduction

In data analysis, it is not uncommon to come across datasets that have split date and time values. In such a situation, it becomes necessary to merge these values into a single datetime column. Python provides several ways to achieve this, but the most straightforward method involves using the datetime module.

The datetime module is part of the Python Standard Library and provides classes for working with dates and times. In this tutorial, we will create a datetime column from two separate columns representing date and time values.

Importing Libraries

Before we begin, we need to import the necessary libraries. We will be using the pandas library to read the data and datetime to create the datetime column.

import pandas as pd
from datetime import datetime

Reading Data

We will start by reading our data into a pandas dataframe. For this tutorial, we will use a sample dataset that contains two columns, Date and Time.

df = pd.read_csv('sample_data.csv')

Creating Datetime Column

Once we have our data in a pandas dataframe, we can create a new column that combines the Date and Time columns into a datetime column.

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

In the above code, we used the pd.to_datetime() function to convert the concatenated Date and Time strings into a datetime object. The resulting datetime values are then stored in a new column called Datetime.

Conclusion

In this tutorial, we learned how to create a datetime column from two separate columns using Python's datetime module and pandas library. This is a common data wrangling task that is essential in data analysis.