How to change the datetime format in Python pandas?

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)

print(df)

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: https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes