Pandas Series dt.is_month_start | Check if Date is First Day of Month

The dt.is_month_start attribute returns a boolean value indicating whether the date is the first day of the month.

Example

 import pandas as pd
sr = pd.Series(['2012-1-1', '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_month_start
print(result)

Output:

Syntax

Syntax: Series.dt.is_month_start 

Parameter: None 

Returns: Series of boolean values

How to Check if Date is First Day in Month in Pandas Series

To check for the dates that are first in their respective months in the Pandas Series we use the dt.is_month_start attribute of the Pandas library in Python.

Let us understand it better with an example:

Example:

Use the Series.dt.is_month_start attribute to check if the dates in the underlying data of the given series object are the start of the month or not.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series(pd.date_range('2012-3-1 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)

Output :

Now we will use the Series.dt.is_month_start attribute to check if the dates in the given series object are the start of the month or not.

# check if dates are the start
# of the month or not
result = sr.dt.is_month_start

# print the result
print(result)

Output :

As we can see in the output, the Series.dt.is_month_start attribute has successfully accessed and returned boolean values indicating whether the dates are the start of the month or not.