Python Pandas Timestamp.year Attribute

Python Pandas Timestamp.year Attribute

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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.

Pandas Timestamp.year Attribute:

The Timestamp.year attribute of the Pandas module gives the year in which the date of the specfied Timestamp object falls.

Syntax:

 Timestamp.year

Parameters: It has no arguments.

Return Value:

The year in which the date of the specfied Timestamp object falls is returned by the Timestamp.year attribute.

Pandas Timestamp.year Attribute in Python

Example1

Approach:

  • Import pandas module using the import keyword.
  • Pass some random year, month, day, hour, second, tz = ‘Asia/Kolkata’ (Timezone) as the 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 the year attribute on the above Timestamp object to get the year in which the date of the given timestamp object lies.
  • 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, second, tz = 'Asia/Kolkata'
# (Timezone) as the arguments to the Timestamp() function of the
# pandas module to get the Timestamp object
# Store it in a variable
time_stamp_obj = pd.Timestamp(year = 2015,  month = 8, day = 5, hour = 7, 
                            second = 24, tz = 'Asia/Kolkata')
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
# Apply year attribute on the above Timestamp object to 
# get the year in which the date of the given timestamp object lies
print("The year in which the date of the given timestamp object lies:")
time_stamp_obj.year

Output:

The above obtained Timestamp object: 2015-08-05 07:00:24+05:30
The year in which the date of the given timestamp object lies:
2015

Example2

Approach:

  • Import pandas module using the import keyword.
  • Pass some random year, month, day, hour, second, tz = ‘US/Central’ (Timezone) as the 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 the year attribute on the above Timestamp object to get the year in which the date of the given timestamp object lies.
  • 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, second, tz = 'US/Central'
# (Timezone) as the arguments to the Timestamp() function of the
# pandas module to get the Timestamp object
# Store it in a variable
time_stamp_obj = pd.Timestamp(year = 2020,  month = 1, day = 18, hour = 11, 
                            second = 30, tz = 'US/Central')
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
# Apply year attribute on the above Timestamp object to 
# get the year in which the date of the given timestamp object lies
print("The year in which the date of the given timestamp object lies:")
time_stamp_obj.year

Output:

The above obtained Timestamp object: 2020-01-18 11:00:30-06:00
The year in which the date of the given timestamp object lies:
2020

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