Python | Pandas DatetimeIndex.round()
Last Updated :
24 Dec, 2018
Improve
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
Python3
Output :
Now we want to convert the second based frequency of the DatetimeIndex object to minute based frequency
Python3
Output :
As we can see in the output, the function has rounded off the values to the desired frequency.
Example #2: Use
Python3
Output :
Now we want to convert the minute based frequency of the DatetimeIndex object to hour based frequency
Python3
Output :
As we can see in the output, the function has rounded off the values to the desired frequency.
DatetimeIndex.round()
function localize tz-naive DatetimeIndex to tz-aware DatetimeIndex. This method takes a time zone (tz) naive DatetimeIndex object and makes this time zone aware. It does not move the time to another time zone. Time zone localization helps to switch from time zone aware to time zone unaware objects.
Syntax: DatetimeIndex.round(freq, *args, **kwargs) Parameters : freq : The frequency level to round the index to. Must be a fixed frequency like ‘S’ (second) not ‘ME’ (month end) Return : Index of the same type for a DatetimeIndex or TimedeltaIndex, or a Series with the same index for a Series.Example #1: Use
DatetimeIndex.round()
function to round the data of the DatetimeIndex object to the specified frequency.
# importing pandas as pd
import pandas as pd
# Create the DatetimeIndex
# Here 'S' represents secondly frequency
didx = pd.DatetimeIndex(start ='2000-01-15 08:00',
freq ='S', periods = 4)
# Print the DatetimeIndex
print(didx)

# convert to the passed frequency
# 'T' represents minute based frequency
didx.round(freq ='T')

DatetimeIndex.round()
function to round the data of the DatetimeIndex object to the specified frequency.
# importing pandas as pd
import pandas as pd
# Create the DatetimeIndex
# Here 'T' represents minutely frequency
didx = pd.DatetimeIndex(start ='2000-01-15 08:00',
freq ='T', periods = 4)
# Print the DatetimeIndex
print(didx)

# convert to the passed frequency
# Convert minute based frequency to hour based frequency
didx.round(freq ='H')
