How to Use dt.year in pandas to Extract Year from Dates

Use dt.year on a pandas Series with datetime values to extract the year as an integer. This works only if the Series is of datetime type, such as datetime64[ns].

Syntax

The syntax to extract the year from a pandas datetime Series is:

series.dt.year

Here, series is a pandas Series with datetime values. The dt accessor allows datetime properties to be accessed, and year returns the year part as an integer.

python

series.dt.year

Example

This example shows how to create a pandas DataFrame with a datetime column and extract the year using dt.year.

python

import pandas as pd

data = {'date': ['2023-01-15', '2022-07-30', '2021-12-05']}
df = pd.DataFrame(data)
df['date'] = pd.to_datetime(df['date'])
df['year'] = df['date'].dt.year
print(df)

Output

        date  year
0 2023-01-15  2023
1 2022-07-30  2022
2 2021-12-05  2021

Common Pitfalls

Common mistakes when using dt.year include:

• Trying to use dt.year on a column that is not datetime type, which causes an error.
• Forgetting to convert strings to datetime using pd.to_datetime().

Example of wrong and right usage:

python

import pandas as pd

data = {'date': ['2023-01-15', '2022-07-30']}
df = pd.DataFrame(data)

# Wrong: 'date' is string, dt.year will raise error
try:
    df['year'] = df['date'].dt.year
except AttributeError as e:
    print(f'Error: {e}')

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

Output

Error: Can only use .dt accessor with datetimelike values
        date  year
0 2023-01-15  2023
1 2022-07-30  2022

Quick Reference

Operation	Description	Example
Extract year	Get year from datetime Series	series.dt.year
Convert to datetime	Convert string to datetime	pd.to_datetime(series)
Error if not datetime	dt.year fails if Series not datetime	Use pd.to_datetime() first

Key Takeaways

Use dt.year on a pandas datetime Series to get the year as an integer.

Always convert string dates to datetime with pd.to_datetime() before using dt.year.

dt.year raises an error if used on non-datetime Series.

The dt accessor provides many datetime properties like year, month, day.

Extracting year helps in time-based analysis and grouping.