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: