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 TimedeltaIndex.floor()
function floor all the values in the given TimedeltaIndex object to the specified frequency.
Syntax : TimedeltaIndex.floor(freq)
Parameters :
freq : freq string/objectReturn : index of same type
Example #1: Use TimedeltaIndex.floor()
function to floor all the values in the given TimedeltaIndex object to daily frequency.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data = [ '3 days 06:05:01.000030' , '1 days 06:05:01.000030' , None , '1 days 02:00:00' , '21 days 06:15:01.000030' ]) # Print the TimedeltaIndex object print (tidx) |
Output :
Now we will use the TimedeltaIndex.floor()
function to floor all the values.
# floor the values to daily frequency tidx.floor(freq = 'D' ) |
Output :
As we can see in the output, the TimedeltaIndex.floor()
function has floored all the values to the daily frequency.
Example #2: Use TimedeltaIndex.floor()
function to floor all the values in the given TimedeltaIndex object to hourly frequency.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data = [ '06:05:01.000030' , '3 days 06:05:01.000030' , '22 day 2 min 3us 10ns' , '+23:59:59.999999' , None , '+12:19:59.999999' ]) # Print the TimedeltaIndex object print (tidx) |
Output :
Now we will use the TimedeltaIndex.floor()
function to floor all the values.
# floor the values to hourly frequency tidx.floor( 'H' ) |
Output :
As we can see in the output, the TimedeltaIndex.floor()
function has floored all the values to the hourly frequency.