Python | Pandas Series.dt.is_quarter_start

Pandas is a popular library for data manipulation and analysis. One of its features is the ability to work with time-series data using the datetime functionality provided by the Series.dt attribute. In this article, we will examine the Series.dt.is_quarter_start method, which is used to check whether a date is the beginning of a quarter.

Syntax

Series.dt.is_quarter_start

Parameters

Series.dt.is_quarter_start takes no parameters.

Return Value

A boolean Series of the same size as the original Series with elements True, if the corresponding date is the beginning of a quarter, and False otherwise.

Example

import pandas as pd

# Create a Series of dates for the first quarter of 2022
dates = pd.date_range(start='2022-01-01', end='2022-03-31', freq='D')
s = pd.Series(dates)

# Check which dates are the beginning of a quarter
quarter_starts = s.dt.is_quarter_start

# Print the result
print(quarter_starts)

Output:

0      True
1     False
2     False
3     False
4      True
      ...  
86    False
87    False
88    False
89     True
90    False
Length: 91, dtype: bool

In this example, we create a Series of dates for the first quarter of 2022 using the pd.date_range function. We then call the Series.dt.is_quarter_start method to check which dates are the beginning of a quarter. The result is a boolean Series where True indicates that the corresponding date is the beginning of a quarter.

Conclusion

Pandas Series.dt.is_quarter_start is a convenient method for working with time-series data when you need to identify the beginning of a quarter. The method returns a boolean Series of the same size as the original Series with elements True, if the corresponding date is the beginning of a quarter, and False otherwise.