How To Change Date Format In Python Dataframe

Working with dates in Python is a common requirement for data manipulation and analysis. One of the most useful libraries for this purpose is pandas, which provides various functions to manipulate and process data in a structured way, such as DataFrames.

One task you might encounter while working with dates in a pandas DataFrame is the need to change the date format. This tutorial will show you how to change the date format in a Python DataFrame step by step.

Step 1: Importing libraries and creating a sample DataFrame

First, we need to import the necessary libraries – pandas and datetime – and create a simple DataFrame with a date column to demonstrate the process.

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import pandas as pd
import datetime
 
data = {
    'name': ['John', 'Jane', 'Sam', 'Sara'],
    'birth_date': ['1990-01-30', '1992-06-15', '1988-12-25', '1995-10-05']
}
 
df = pd.DataFrame(data)
print(df)

Output:

   name  birth_date
0  John  1990-01-30
1  Jane  1992-06-15
2   Sam  1988-12-25
3  Sara  1995-10-05

In this example, we assume that the date format in the ‘birth_date’ column is ‘YYYY-MM-DD.’

Step 2: Convert ‘birth_date’ column to datetime objects

Next, we will convert the ‘birth_date’ column from string objects to datetime objects. This step is essential because you cannot directly change the date format of a string object. By converting the dates to datetime objects, you can use various datetime functions to manipulate the date format.

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df['birth_date'] = pd.to_datetime(df['birth_date'])
print(df)

Output:

   name birth_date
0  John 1990-01-30
1  Jane 1992-06-15
2   Sam 1988-12-25
3  Sara 1995-10-05

Now, the ‘birth_date’ column contains datetime objects with the default format (‘YYYY-MM-DD’).

Step 3: Change the date format

To change the date format in the ‘birth_date’ column, we will use the apply() and strftime() functions. The apply() function enables you to apply a specific function to the dataframe. Meanwhile, the strftime() function is a method available in datetime objects to format the datetime as a string in a specified format.

Let’s change the date format to ‘DD-MM-YYYY.’

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df['birth_date'] = df['birth_date'].apply(lambda x: x.strftime('%d-%m-%Y'))
print(df)

Output:

   name  birth_date
0  John  30-01-1990
1  Jane  15-06-1992
2   Sam  25-12-1988
3  Sara  05-10-1995

Now the ‘birth_date’ column has the desired date format (‘DD-MM-YYYY’).

Full code

The complete code for changing the date format in a Python DataFrame is shown below:

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import pandas as pd
import datetime
 
data = {
    'name': ['John', 'Jane', 'Sam', 'Sara'],
    'birth_date': ['1990-01-30', '1992-06-15', '1988-12-25', '1995-10-05']
}
 
df = pd.DataFrame(data)
print("Original DataFrame:")
print(df)
print()
 
df['birth_date'] = pd.to_datetime(df['birth_date'])
print("DataFrame after converting 'birth_date' to datetime objects:")
print(df)
print()
 
df['birth_date'] = df['birth_date'].apply(lambda x: x.strftime('%d-%m-%Y'))
print("DataFrame after changing the date format in 'birth_date':")
print(df)

Output:

Original DataFrame:
   name  birth_date
0  John  1990-01-30
1  Jane  1992-06-15
2   Sam  1988-12-25
3  Sara  1995-10-05

DataFrame after converting 'birth_date' to datetime objects:
   name birth_date
0  John 1990-01-30
1  Jane 1992-06-15
2   Sam 1988-12-25
3  Sara 1995-10-05

DataFrame after changing the date format in 'birth_date':
   name  birth_date
0  John  30-01-1990
1  Jane  15-06-1992
2   Sam  25-12-1988
3  Sara  05-10-1995

Conclusion

In this tutorial, you learned how to change the date format in a pandas DataFrame. By using datetime objects and the apply() and strftime() functions, you can quickly and easily change the date format as required. Now you’re ready to perform more advanced date manipulations and analyses in your own data projects!