Remove Elements From A Pandas Series Using Drop() And Truncate() Methods

Overview:

  • From a pandas Series a set of elements can be removed using the index, index labels through the methods drop() and truncate().
  • The drop() method removes a set of elements at specific index locations. The locations are specified by index or index labels.
  • The truncate() method truncates the series at two locations: at the before-1 location and after+1 location. It returns the resultant new series.
  • In the similar way, if the data is from a 2-dimensional container like pandas DataFrame, the drop() and truncate() methods of the DataFrame class can be used.

Example – Remove elements at specific index locations using drop():

# Python example program to remove a set of elements

# specified by a set of indexes

import pandas as pds

 

alphabets   = ["a","b","c","d","e","f","g","h","i","j"];

series      = pds.Series(alphabets);

 

# List of indices at which the elements need to be removed

newSeries   = series.drop([0, 2, 4, 6, 8]);

 

print("Original Series:");

print(series);

 

print("New Series returned after removing elements at every alternate index:");

print(newSeries);

 

Output:

Original Series:

0    a

1    b

2    c

3    d

4    e

5    f

6    g

7    h

8    i

9    j

dtype: object

New Series returned after removing elements at every alternate index:

1    b

3    d

5    f

7    h

9    j

dtype: object

 

Example - Remove elements at specific index locations using truncate():

# Example Python program to truncate a pandas Series

# at specific index locations

import pandas as pds

 

# Create a pandas Series

series      = pds.Series([10, 20, 30, 40, 50, 60, 70, 80, 90, 100]);

print("Original Series:");

print(series);

 

# Truncate the Series to get a new Series

newSeries   = series.truncate(4, 8, copy = False);

print("New series obtained after truncation:");

print(newSeries);

 

Output:

Original Series:

0     10

1     20

2     30

3     40

4     50

5     60

6     70

7     80

8     90

9    100

dtype: int64

New series obtained after truncation:

4    50

5    60

6    70

7    80

8    90

dtype: int64


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