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Python | Pandas Timestamp.to_datetime64

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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.to_datetime64() function return a numpy.datetime64 object with ‘ns’ precision for the given Timestamp object.

Syntax :Timestamp.to_datetime64()

Parameters : None

Return : numpy.datetime64 object

Example #1: Use Timestamp.to_datetime64() function to return a numpy.datetime64 object for the given Timestamp object.




# importing pandas as pd
import pandas as pd
  
# Create the Timestamp object
ts = pd.Timestamp(year = 2011,  month = 11, day = 21
                  hour = 10, second = 49, tz = 'US/Central'
  
# Print the Timestamp object
print(ts)


Output :

Now we will use the Timestamp.to_datetime64() function to return a numpy.datetime64 object for the given Timestamp.




# return numpy.datetime64 object
ts.to_datetime64()


Output :

As we can see in the output, the Timestamp.to_datetime64() function has returned a numpy.datetime64 object for the given Timestamp object with ‘ns’ precision.
 
Example #2: Use Timestamp.to_datetime64() function to return a numpy.datetime64 object for the given Timestamp object.




# importing pandas as pd
import pandas as pd
  
# Create the Timestamp object
ts = pd.Timestamp(year = 2009, month = 5, day = 31
                  hour = 4, second = 49, tz = 'Europe/Berlin')
  
# Print the Timestamp object
print(ts)


Output :

Now we will use the Timestamp.to_datetime64() function to return a numpy.datetime64 object for the given Timestamp.




# return numpy.datetime64 object
ts.to_datetime64()


Output :

As we can see in the output, the Timestamp.to_datetime64() function has returned a numpy.datetime64 object for the given Timestamp object with ‘ns’ precision.



Last Updated : 17 Jan, 2019
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