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.
