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Python | Pandas Series.truncate()

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  • Last Updated : 05 Feb, 2019

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas Series.truncate() function is used to truncate a Series or DataFrame before and after some index value. This is a useful shorthand for boolean indexing based on index values above or below certain thresholds.

Syntax: Series.truncate(before=None, after=None, axis=None, copy=True)

Parameter :
before : Truncate all rows before this index value.
after : Truncate all rows after this index value.
axis : Axis to truncate. Truncates the index (rows) by default.
copy : Return a copy of the truncated section.

Returns : truncated Series or DataFrame.

Example #1: Use Series.truncate() function to truncate some data from the series prior to a given date.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio', 'Moscow'])
  
# Create the Datetime Index
didx = pd.DatetimeIndex(start ='2014-08-01 10:00', freq ='W'
                     periods = 6, tz = 'Europe/Berlin'
  
# set the index
sr.index = didx
  
# Print the series
print(sr)


Output :

Now we will use Series.truncate() function to truncate data which are prior to ‘2014-08-17 10:00:00+02:00’ in the given Series object.




# truncate data prior to the given date
sr.truncate(before = '2014-08-17 10:00:00 + 02:00')


Output :

As we can see in the output, the Series.truncate() function has successfully truncated all data prior to the mentioned date.

Example #2: Use Series.truncate() function to truncate some data from the series prior to a given index label and after a given index label.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([19.5, 16.8, 22.78, 20.124, 18.1002])
  
# Print the series
print(sr)


Output :

Now we will use Series.truncate() function to truncate data which are prior to the 1st index label and after the 3rd index label in the given Series object.




# truncate data outside the given range
sr.truncate(before = 1, after = 3)


Output :

As we can see in the output, the Series.truncate() function has successfully truncated all data prior to the mentioned index label and after the mentioned index label.


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