Python | Pandas DatetimeIndex.is_quarter_start

DatetimeIndex.is_quarter_start Pandas DatetimeIndex.is_quarter_start is an indicator of whether a date is the first day of a quarter. If the date is the first day of the quarter, True is returned otherwise False .

Syntax: DatetimeIndex.is_quarter_start

Returns: numpy array containing logical values.

Example # 1: Use the DatetimeIndex attribute. is_quarter_start to check if the dates in the DatetimeIndex are the first day of the quarter.

# import pandas as pd import pandas as pd   # Create DatetimeIndex didx = pd.DatetimeIndex ([ ’2014-01-31’ , ’ 2014-04-1’ , ’2015-08-01’ , ’2000-12-02’ ])   # Print DatetimeIndex print (didx)

Output:

Now we want to find out if the dates are contained in this DatetimeIndex object, the first day of the quarter.

# determine if the days are the first day of the quarter. didx.is_quarter_start

Exit:

As we can see in the output, the function returned an empty array containing boolean values ​​for each entry in the DatetimeIndex object.  True values ​​indicate that the corresponding date was the first day of the quarter, and False values ​​indicate that the corresponding date was not the first day of the quarter.

Example # 2: Use the DatetimeIndex.is_quarter_start attribute to check if the dates present in the DatetimeIndex object are the first day of the quarter.

# import pandas as pd import pandas as pd   # Create DatetimeIndex didx = pd.date_range ( ’ 2011-03-30 ’ , periods = 5 )    # Print DatetimeIndex print (didx)

Output:

Now we want to find out if the dates contained in this DatetimeIndex are the first day of the quarter.

# determine if days are the first day of the quarter. didx.is_quarter_start

Output:

As we can see in output, the function returned an empty array containing boolean values ​​for each record of the Da object tetimeIndex.  True values ​​indicate that the corresponding date was the first day of the quarter, and False values ​​indicate that the corresponding date was not the first day of the quarter.