Python Pandas Timestamp.is_quarter_start Attribute

What is Timestamp?

A timestamp is a sequence of characters or encoded information that identifies when a particular event occurred, typically providing the date and time of day, and can be accurate to a fraction of a second.

The timestamp method is used for a variety of synchronization purposes, including assigning a sequence order to a multievent transaction so that the transaction can be canceled if a fault occurs. A timestamp can also be used to record time in reference to a specific starting point in time.

Uses of Timestamp:

Timestamps are used to maintain track of information stored online or on a computer. A timestamp indicates when data was generated, shared, modified, or removed.

Here are some examples of how timestamps can be used:

  • A timestamp in a computer file indicates when the file was last modified.
  • Photographs with digital cameras have timestamps that show the date and time of day they were taken.
  • The date and time of the post are included in social media posts.
  • Timestamps are used in online chat and instant messages to record the date and time that a message was delivered, received, or viewed.
  • Timestamps are used in blockchain blocks to confirm the validity of transactions, such as those involving cryptocurrencies.
  • To secure the integrity and quality of data, data management relies on timestamps.
  • Timestamps are used in digital contracts and digital signatures to signify when a document was signed.

Python Pandas Timestamp.is_quarter_start Attribute:

The Timestamp.is_quarter_start attribute of the Pandas module returns a boolean value. If the date in the given Timestamp object is the start of the quarter, it returns True; otherwise, it returns False.

Syntax:

 Timestamp.is_quarter_start

Parameters: It has no arguments

Return Value:

True: If the date in the given Timestamp object is the quarter-start.

False: If the date in the given Timestamp object is NOT the quarter-start.

NOTE: The quarter start dates are: January 1st, April 1st, July 1st, October 1st.

Pandas Timestamp.is_quarter_start Attribute in Python

Example1

Approach:

  • Import pandas module using the import keyword.
  • Pass some random year, month, day, hour as arguments to the Timestamp() function of the pandas module to get the Timestamp object.
  • Store it in a variable.
  • Print the above-obtained Timestamp object
  • Apply is_quarter_start attribute on the above Timestamp object to check if the date in the given Timestamp object is the quarter start or NOT.
  • The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
  
# Pass some random year, month, day, hour as arguments to the
# Timestamp() function of the pandas module to get the Timestamp object
# Store it in a variable
time_stamp_obj = pd.Timestamp(2020, 4, 1, 10)
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
# Apply is_quarter_start attribute on the above Timestamp object to check 
# if the date in the given Timestamp object is quarter start or NOT
print("Checking if the date in the given Timestamp object is quarter start or NOT:")
time_stamp_obj.is_quarter_start

Output:

The above obtained Timestamp object: 2020-04-01 10:00:00
Checking if the date in the given Timestamp object is quarter start or NOT:
True

Example2

Approach:

  • Import pandas module using the import keyword.
  • Pass some random year, month, day, tz =’Asia/Kolkata’ (Timezone) as the arguments to the Timestamp() function of the pandas module to get the Timestamp object
  • Print the above-obtained Timestamp object.
  • Apply is_quarter_start attribute on the above Timestamp object to check if the date in the given Timestamp object is the quarter start or NOT.
  • The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
  
# Pass some random year, month, day, tz ='Asia/Kolkata'
# (Timezone) as the arguments to the Timestamp() function of the
# pandas module to get the Timestamp object
time_stamp_obj = pd.Timestamp(year = 2015,  month = 5, day = 25, tz = 'Asia/Kolkata')
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
# Apply is_quarter_start attribute on the above Timestamp object to check 
# if the date in the given Timestamp object is quarter start or NOT
print("Checking if the date in the given Timestamp object is quarter start or NOT:")
time_stamp_obj.is_quarter_start

Output:

The above obtained Timestamp object: 2015-05-25 00:00:00+05:30
Checking if the date in the given Timestamp object is quarter start or NOT:
False