How to Extract Day from Datetime in pandas | Simple Guide

To extract the day from a datetime column in pandas, use the .dt.day attribute on a datetime Series. This returns the day of the month as an integer for each datetime value.

Syntax

Use Series.dt.day to get the day of the month from a pandas datetime Series.

• Series: A pandas Series with datetime values.
• .dt: Accessor for datetime properties.
• .day: Extracts the day as an integer (1 to 31).

python

df['date_column'].dt.day

Example

This example shows how to create a pandas DataFrame with a datetime column and extract the day from it.

python

import pandas as pd

data = {'date_column': ['2024-06-01', '2024-06-15', '2024-06-30']}
df = pd.DataFrame(data)
df['date_column'] = pd.to_datetime(df['date_column'])
df['day'] = df['date_column'].dt.day
print(df)

Output

  date_column  day
0  2024-06-01    1
1  2024-06-15   15
2  2024-06-30   30

Common Pitfalls

Common mistakes include:

• Trying to use .day on a column that is not converted to datetime type, which causes an error.
• Using .day on a string column without conversion.

Always convert your column to datetime first using pd.to_datetime().

python

import pandas as pd

data = {'date_column': ['2024-06-01', '2024-06-15', '2024-06-30']}
df = pd.DataFrame(data)

# Wrong: trying to extract day from string column
# df['day'] = df['date_column'].dt.day  # This will raise an error

# Right: convert to datetime first
df['date_column'] = pd.to_datetime(df['date_column'])
df['day'] = df['date_column'].dt.day
print(df)

Output

  date_column  day
0  2024-06-01    1
1  2024-06-15   15
2  2024-06-30   30

Quick Reference

Operation	Code Example	Description
Extract day	df['date_column'].dt.day	Gets day of month as integer
Convert to datetime	pd.to_datetime(df['date_column'])	Converts string to datetime type
Extract month	df['date_column'].dt.month	Gets month as integer
Extract year	df['date_column'].dt.year	Gets year as integer

Key Takeaways

Use .dt.day on a datetime Series to get the day of the month.

Always convert your column to datetime type with pd.to_datetime() before extracting date parts.

Trying to use .dt.day on non-datetime columns causes errors.

The day extracted is an integer from 1 to 31 depending on the date.

You can similarly extract month and year using .dt.month and .dt.year.