To extract the quarter from a datetime column in pandas, you can access the “quarter” property. The “quarter” property returns a 64-bit integer.

import pandas as pd

df = pd.DataFrame({
    "date": ["2021-09-30", "2021-12-31", "2022-03-31", "2022-06-30", "2022-09-30", "2022-12-31"],
    "sales": [100,30,50,60,10,80]
})

df["date"] = pd.to_datetime(df["date"])

df["quarter"] = df["date"].dt.quarter

print(df)

#Output:
        date  sales  quarter
0 2021-09-30    100        3
1 2021-12-31     30        4
2 2022-03-31     50        1
3 2022-06-30     60        2
4 2022-09-30     10        3
5 2022-12-31     80        4

When working with data which contains information over time, the ability to extract certain pieces of information from our data easily is valuable.

One such piece of information is getting the quarter from a date when using pandas in Python.

To get the quarter from a datetime column in pandas, you can access the pandas datetime “quarter” property. The “quarter” property returns a 64-bit integer.

For example, if you have a date which is in the month of January, quarter will return 1 because it is the first quarter.

Below is a simple example which shows you how to get the quarter from a datetime variables in a pandas DataFrame.

import pandas as pd

df = pd.DataFrame({
    "date": ["2021-09-30", "2021-12-31", "2022-03-31", "2022-06-30", "2022-09-30", "2022-12-31"],
    "sales": [100,30,50,60,10,80]
})

df["date"] = pd.to_datetime(df["date"])

df["quarter"] = df["date"].dt.quarter

print(df)

#Output:
        date  sales  quarter
0 2021-09-30    100        3
1 2021-12-31     30        4
2 2022-03-31     50        1
3 2022-06-30     60        2
4 2022-09-30     10        3
5 2022-12-31     80        4

Hopefully this article has been useful for you to learn how to get the quarter from a datetime variable in a pandas DataFrame in Python.

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Last Update: March 1, 2024