Python | Pandas Timestamp.to_datetime64

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. Python3

# 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. Python3

# 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. Python3

# 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. Python3

# 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.