Python Pandas Timestamp.fromordinal() Function

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.fromordinal() Function:

When an ordinal is provided to the Timestamp.fromordinal() function of the pandas module, it returns a Timestamp object after translating and converting it to a ts object. There can’t be any tz information(tzinfo) on the ordinal itself, by definition.

Syntax:

 Timestamp.fromordinal()

Parameters:

ordinal: It is the date corresponding to a proleptic Gregorian ordinal

freq: This is optional. It is the offset that a Timestamp has.

tz: This is the timezone given as input.

Return Value:

The Timestamp object is returned by the Timestamp.fromordinal() function of the pandas module.

Pandas Timestamp.fromordinal() Function in Python

Example1

Here, the function returns a new Timestamp object based on the given ordinal value.

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
Print the above-obtained Timestamp object
Pass some random ordinal value as an argument to the fromordinal() function and apply it on the above Timestamp object to convert the above-given Timestamp object according to the ordinal(numerical) value.
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
time_stamp_obj = pd.Timestamp(year = 2019,  month = 5, day = 16, hour = 11, 
                            second = 25, tz = 'Asia/Kolkata')
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
print()
# Pass some random ordinal value as an argument to the fromordinal() function 
# and apply it on the above Timestamp object to convert the 
# above given Timestamp object according the ordinal(numerical) value.
print("The given Timestamp object according to the ordinal value:")
time_stamp_obj.fromordinal(ordinal = 723826)

Output:

The above obtained Timestamp object: 2019-05-16 11:00:25+05:30

The given Timestamp object according to the ordinal value:
Timestamp('1982-10-08 00:00:00')

Example2

Here, it converts the Timestamp object according to the ordinal(numerical) value and sets the given timezone for the Timestamp.

Approach:

Import pandas module using the import keyword.
Pass some random year, month, day, hour, second, tz = ‘US/Eastern’ (Timezone) as the arguments to the Timestamp() function of the pandas module to get the Timestamp object.
Print the above-obtained Timestamp object
Pass some random ordinal value, tz as the arguments to the fromordinal() function and apply it on the above Timestamp object to convert the above-given Timestamp object according to the ordinal(numerical) value and set the given timezone for the Timestamp.
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/Eastern'
# (Timezone) as the arguments to the Timestamp() function of the
# pandas module to get the Timestamp object
time_stamp_obj = pd.Timestamp(year = 2020,  month = 3, day = 12, hour = 13, 
                            second = 30, tz = 'US/Eastern')
  
# Print the above obtained Timestamp object
print("The above obtained Timestamp object:", time_stamp_obj)
print()
# Pass some random ordinal value, tz as the arguments to the fromordinal() function 
# and apply it on the above Timestamp object to convert the above given Timestamp 
# object according to the ordinal(numerical) value and set the given timezone for the Timestamp
print("The Timestamp object according to the ordinal and timezone Values:")
time_stamp_obj.fromordinal(ordinal = 693745, tz= 'Asia/Kolkata')

Output:

The above obtained Timestamp object: 2020-03-12 13:00:30-04:00

The Timestamp object according to the ordinal and timezone Values:
Timestamp('1900-05-30 00:00:00+0553', tz='Asia/Kolkata')

Pandas Timestamp.fromordinal() Function in Python

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