Pandas dt.is_quarter_start attribute returns a boolean value indicating whether the date is the first day of a quarter.
Example:
import pandas as pd
sr = pd.Series(['2012-4-1', '2019-7-18 12:30', '2008-02-2 10:30',
'2010-4-22 09:25', '2019-1-1 00:00'])
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
sr.index = idx
sr = pd.to_datetime(sr)
result = sr.dt.is_quarter_start
print(result)
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Output :
Syntax
Syntax: Series.dt.is_quarter_start
Parameter: None
Returns: Series with boolean values
How to Check if Date is First in it’s Quarter in Pandas Series
To check if a Date is the first date in its respective quarter in the Pandas Series, we use the dt.is_quarter_start attribute of the Pandas Library in Python.
Let us understand it better with an example:
Example
Use the Series.dt.is_quarter_start attribute to check if the dates in the underlying data of the given series object are the first day of the quarter.
# importing pandas as pd import pandas as pd
# Creating the Series sr = pd.Series(pd.date_range('2012-4-1 00:00',
periods = 5, freq = 'W'))
# Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
# set the index sr.index = idx
# Print the series print(sr)
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Output :
Now we will use the dt.is_quarter_start attribute to check if the dates in the given series object is the first day of the quarter or not.
# check if dates are the first # day of the quarter result = sr.dt.is_quarter_start
# print the result print(result)
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Output :
As we can see in the output, the dt.is_quarter_start attribute has successfully accessed and returned boolean values indicating whether the dates are the first day of the quarter.