How to change the datetime format in Python pandas?

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To change the datetime format in Python pandas, you can use the strftime method or the dt.strftime accessor to format the datetime values in a DataFrame column. Here’s an example:

import pandas as pd

# Sample data
data = {'Date': ['2023-01-01', '2023-02-01', '2023-03-01', '2023-04-01'],
        'Value': [10, 15, 8, 12]}

df = pd.DataFrame(data)

# Convert 'Date' column to datetime
df['Date'] = pd.to_datetime(df['Date'])

# Set the desired date format
date_format = "%b %d, %Y"

# Format the 'Date' column
df['Formatted Date'] = df['Date'].dt.strftime(date_format)


In this example, we have a DataFrame df with a ‘Date’ column and a ‘Value’ column. We first convert the ‘Date’ column to a datetime format using pd.to_datetime().

Then, we set the desired date format using the date_format variable. The %b represents the abbreviated month name, %d represents the day of the month with a leading zero, and %Y represents the four-digit year.

To format the ‘Date’ column, we use df['Date'].dt.strftime(date_format) to apply the formatting to each datetime value in the column. This returns a new Series with formatted date strings.

In the example, we create a new column ‘Formatted Date’ to store the formatted datetime values. You can assign the formatted values to an existing column or create a new column as per your requirements.

After running the code, you will see the DataFrame df with the original ‘Date’ column and a new ‘Formatted Date’ column containing the datetime values in the desired format.

You can modify the date_format variable to match your desired format. Refer to the Python documentation on strftime for more formatting options:

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