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_period() function return a period object for which the given Timestamp is an observation.
Syntax :Timestamp.to_period()
Parameters :
freq : time series frequencyReturn : period object
Example #1: Use Timestamp.to_period() function to convert the given Timestamp to a period 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_period() function to convert the given Timestamp to period.
# convert to period # we have applied monthly frequency ts.to_period(freq ='M') |
Output :
As we can see in the output, the Timestamp.to_period() function has converted the given Timestamp object into a period object.
Example #2: Use Timestamp.to_period() function to convert the given Timestamp to a period 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_period() function to convert the given Timestamp to period.
# convert to period # we have applied minutely frequency ts.to_period(freq ='T') |
Output :
As we can see in the output, the Timestamp.to_period() function has converted the given Timestamp object into a period object.
