Python Pandas - Display the quarter of the date from the PeriodIndex object

To display the quarter of the date from the PeriodIndex object, use the PeriodIndex.quarter property. A quarter represents a three-month period in a year: Q1 (Jan-Mar), Q2 (Apr-Jun), Q3 (Jul-Sep), and Q4 (Oct-Dec).

What is PeriodIndex?

PeriodIndex is an immutable ndarray holding ordinal values indicating regular periods in time. It's useful for time series data analysis with fixed frequencies.

Creating a PeriodIndex Object

First, import pandas and create a PeriodIndex with datetime strings ?

import pandas as pd

# Create a PeriodIndex object with minute frequency
periodIndex = pd.PeriodIndex(['2021-09-25 07:30:35', '2019-10-30 04:15:45',
                             '2021-07-15 02:55:15', '2022-06-25 09:40:55'], freq="T")

print("PeriodIndex...")
print(periodIndex)

PeriodIndex...
PeriodIndex(['2021-09-25 07:30', '2019-10-30 04:15', '2021-07-15 02:55', '2022-06-25 09:40'], dtype='period[T]')

Displaying Quarter Information

Use the quarter property to extract quarter values from the PeriodIndex ?

import pandas as pd

# Create a PeriodIndex object
periodIndex = pd.PeriodIndex(['2021-09-25 07:30:35', '2019-10-30 04:15:45',
                             '2021-07-15 02:55:15', '2022-06-25 09:40:55'], freq="T")

# Display the quarter of each date
print("Quarter of each date:")
print(periodIndex.quarter)

# Display frequency information
print("\nFrequency object:", periodIndex.freq)
print("Frequency as string:", periodIndex.freqstr)

Quarter of each date:
Index([3, 4, 3, 2], dtype='int64')

Frequency object: <Minute>
Frequency as string: T

Understanding the Results

The quarter property returns an Index with integer values representing quarters ?

Conclusion

The PeriodIndex.quarter property efficiently extracts quarter information from datetime periods. This is useful for quarterly financial analysis and seasonal data grouping in pandas time series operations.