Python | Pandas Timestamp.is_quarter_start

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas Timestamp.is_quarter_start attribute return a boolean value. It return True if the date in the given Timestamp object is start of the quarter else it return False.

Syntax : Timestamp.is_quarter_start Parameters : None Return : boolean

Example #1: Use Timestamp.is_quarter_start attribute to check if the date in the given Timestamp object is start of the quarter or not. Python3

# importing pandas as pd
import pandas as pd

# Create the Timestamp object
ts = pd.Timestamp(2016, 1, 1, 12)

# Print the Timestamp object
print(ts)

Output : Now we will use the Timestamp.is_quarter_start attribute to check if the date in the ts object is start of the quarter or not. Python3

# check if the date is start of the quarter
ts.is_quarter_start

Output : As we can see in the output, the Timestamp.is_quarter_start attribute has returned True indicating the date in the given Timestamp object is start of the quarter.   Example #2: Use Timestamp.is_quarter_start attribute to check if the date in the given Timestamp object is start of the quarter or not. Python3

# importing pandas as pd
import pandas as pd

# Create the Timestamp object
ts = pd.Timestamp(year = 2009, month = 5, day = 31,
                    hour = 4, tz = 'Europe/Berlin')

# Print the Timestamp object
print(ts)

Output : Now we will use the Timestamp.is_quarter_start attribute to check if the date in the ts object is start of the quarter or not. Python3

# check if the date is start of the quarter
ts.is_quarter_start

Output : As we can see in the output, the Timestamp.is_quarter_start attribute has returned False indicating the date in the given Timestamp object is not the start of the quarter.