Need to rename convert string or datetime to quarter in Pandas?

If so, you may use the following syntax to extract quarter info from your DataFrame:


The picture below demonstrate it:


To begin, let's create a simple DataFrame with a datetime column:

import pandas as pd
dates = ['2021-01-01', '2021-05-02', '2021-08-03']
df = pd.DataFrame({'StartDate': dates})

df['StartDate'] = pd.to_datetime(df['StartDate'])


Step 1: Extract Quarter as YYYYMM from DataTime Column in Pandas

Let's say that you want to extract the quarter info in the next format: YYYYMM. Pandas offers a built-in method for this purpose .dt.to_period('Q'):

df['quarter'] = df['StartDate'].dt.to_period('Q')

the result would be:

0    2021Q1
1    2021Q2
2    2021Q3

Step 2: Extract Quarter(custom format) from DataTime Column in Pandas

What if you like to get a custom format instead of the default one? In this case you can use method: dt.strftime('q%q %y\'') to change the format like:

df['quarter_custom'] = df['StartDate'].dt.to_period('Q').dt.strftime('q%q %y\'')

This will output:

0    q1 21'
1    q2 21'
2    q3 21'

Another option for custom formatting might be separated extraction of the information as:

df['StartDate'].dt.year.astype(str) + '-' + df['StartDate'].dt.quarter.astype(str)

Step 3: Extract Quarters without the year

If you need to analyse the quarter info without the year information you can get it by: