Python Pandas Timestamp.normalize() Function

Pandas normalize – Python Pandas Timestamp.normalize() Function

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What is Timestamp?

Pandas normalize: 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.normalize() Function:

The Timestamp.normalize() function of the Pandas module normalized timestamp to midnight. This operation is carried out by the function while keeping the tz information unchanged.

Syntax:

Timestamp.normalize()

Parameters: This function doesn’t have any arguments

Return Value:

A normalized new Timestamp is returned by the Timestamp.normalize() function of the Pandas module.

Pandas Timestamp.normalize() Function in Python

Example1

Approach:

  • Import pandas module using the import keyword.
  • Pass some random year, month, day, hour, minute, second, microsecond 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 normalize() Function on the above Timestamp object to normalize the given timestamp object to midnight.
  • 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, minute, second, microsecond 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(2015, 2, 3, 11, 22, 13, 18)
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
# Apply normalize() Function on the above Timestamp object to 
# normalize the given timestamp object to midnight.
print("Normalizing the given timestamp object to midnight:")
time_stamp_obj.normalize()

Output:

The above obtained Timestamp object: 2015-02-03 11:22:13.000018
Normalizing the given timestamp object to midnight:
Timestamp('2015-02-03 00:00:00')

Example2

Approach:

  • Import pandas module using the import keyword.
  • Pass some random year, month, day, hour, microsecond , 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 normalize() Function on the above Timestamp object to normalize the given timestamp object to midnight.
  • 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, microsecond, 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 = 6, day = 26, hour = 7, 
                            microsecond = 35, tz = 'Asia/Kolkata')
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
# Apply normalize() Function on the above Timestamp object to 
# normalize the given timestamp object to midnight.
print("Normalizing the given timestamp object to midnight:")
time_stamp_obj.normalize()

Output:

The above obtained Timestamp object: 2015-06-26 07:00:00.000035+05:30
Normalizing the given timestamp object to midnight:
Timestamp('2015-06-26 00:00:00+0530', tz='Asia/Kolkata')