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How to rename a DataFrame index in Pandas?

 1 year ago
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In this article, we will discuss multiple ways to rename a DataFrame index in pandas.

Table of Contents

Preparing DataSet

To quickly get started, let’s create a sample dataframe to experiment. We’ll use the pandas library with some random data.

import pandas as pd
# List of Tuples
employees= [('Shubham', 'India', 'Tech', 5, 4),
('Riti', 'India', 'Design' , 7, 7),
('Shanky', 'India', 'PMO' , 2, 2),
('Shreya', 'India', 'Design' , 2, 0),
('Aadi', 'US', 'PMO', 11, 5),
('Sim', 'US', 'Tech', 4, 4)]
# Create a DataFrame object from list of tuples
df = pd.DataFrame(employees,
columns=['Name', 'Location', 'Team', 'Experience', 'RelevantExperience'],
index = ['A', 'B', 'C', 'D', 'E', 'F'])
print(df)
import pandas as pd

# List of Tuples
employees= [('Shubham', 'India', 'Tech',   5, 4),
            ('Riti', 'India', 'Design' ,   7, 7),
            ('Shanky', 'India', 'PMO' ,   2, 2),
            ('Shreya', 'India', 'Design' ,   2, 0),
            ('Aadi', 'US', 'PMO', 11, 5),
            ('Sim', 'US', 'Tech', 4, 4)]

# Create a DataFrame object from list of tuples
df = pd.DataFrame(employees,
                  columns=['Name', 'Location', 'Team', 'Experience', 'RelevantExperience'],
                  index = ['A', 'B', 'C', 'D', 'E', 'F'])
print(df)

Contents of the created dataframe are,

Name Location Team Experience RelevantExperience
A Shubham India Tech 5 4
B Riti India Design 7 7
C Shanky India PMO 2 2
D Shreya India Design 2 0
E Aadi US PMO 11 5
F Sim US Tech 4 4
      Name Location    Team  Experience  RelevantExperience
A  Shubham    India    Tech           5                   4
B     Riti    India  Design           7                   7
C   Shanky    India     PMO           2                   2
D   Shreya    India  Design           2                   0
E     Aadi       US     PMO          11                   5
F      Sim       US    Tech           4                   4

Rename specific index(s) in Pandas DataFrame

In this section, we will look at renaming a specific index using the DataFrame.rename() function. Let’s understand with an example, say, we need to rename the index “A” as “New_A”.

# rename index "A" to "New_A"
print(df.rename(index = {'A':'New_A'}))
# rename index "A" to "New_A"
print(df.rename(index = {'A':'New_A'}))

Output

Name Location Team Experience RelevantExperience
New_A Shubham India Tech 5 4
B Riti India Design 7 7
C Shanky India PMO 2 2
D Shreya India Design 2 0
E Aadi US PMO 11 5
F Sim US Tech 4 4
          Name Location    Team  Experience  RelevantExperience
New_A  Shubham    India    Tech           5                   4
B         Riti    India  Design           7                   7
C       Shanky    India     PMO           2                   2
D       Shreya    India  Design           2                   0
E         Aadi       US     PMO          11                   5
F          Sim       US    Tech           4                   4

As observed, the first row index which was earlier named as “A” has now changed to “New_A”. In case, we need to rename multiple indexes at once, we can do it as follows.

# rename multiple indexes
print(df.rename(index = {'A':'New_A', 'B':'New_B'}))
# rename multiple indexes
print(df.rename(index = {'A':'New_A', 'B':'New_B'}))

Output

Name Location Team Experience RelevantExperience
New_A Shubham India Tech 5 4
New_B Riti India Design 7 7
C Shanky India PMO 2 2
D Shreya India Design 2 0
E Aadi US PMO 11 5
F Sim US Tech 4 4
          Name Location    Team  Experience  RelevantExperience
New_A  Shubham    India    Tech           5                   4
New_B     Riti    India  Design           7                   7
C       Shanky    India     PMO           2                   2
D       Shreya    India  Design           2                   0
E         Aadi       US     PMO          11                   5
F          Sim       US    Tech           4                   4

Rename all indexes in Pandas DataFrame

In this section, we will discuss the method to rename all the indexes at once in pandas DataFrame. We are going to use the set_axis() function from pandas, where we need to provide the list of new names and axis (index or columns) value. Let’s rename all the indexes in the above DataFrame.

# rename all indexes
print (df.set_axis(["New_A", "New_B", "New_C", "New_D", "New_E", "New_F"], axis='index'))
# rename all indexes
print (df.set_axis(["New_A", "New_B", "New_C", "New_D", "New_E", "New_F"], axis='index'))

Output

Name Location Team Experience RelevantExperience
New_A Shubham India Tech 5 4
New_B Riti India Design 7 7
New_C Shanky India PMO 2 2
New_D Shreya India Design 2 0
New_E Aadi US PMO 11 5
New_F Sim US Tech 4 4
          Name Location    Team  Experience  RelevantExperience
New_A  Shubham    India    Tech           5                   4
New_B     Riti    India  Design           7                   7
New_C   Shanky    India     PMO           2                   2
New_D   Shreya    India  Design           2                   0
New_E     Aadi       US     PMO          11                   5
New_F      Sim       US    Tech           4                   4

As observed, all the indexes in the DataFrame are now renamed.

Adding a prefix or suffix to Index Names in Pandas DataFrame

In case, we just need to add a prefix or suffix in the index name of the DataFrame, we can again use the rename function. Let’s add the prefix “New_” in the above DataFrame.

# rename by adding prefix
print (df.rename(index = lambda x: "New_"+x))
# rename by adding prefix
print (df.rename(index = lambda x: "New_"+x))

Output

Name Location Team Experience RelevantExperience
New_A Shubham India Tech 5 4
New_B Riti India Design 7 7
New_C Shanky India PMO 2 2
New_D Shreya India Design 2 0
New_E Aadi US PMO 11 5
New_F Sim US Tech 4 4
          Name Location    Team  Experience  RelevantExperience
New_A  Shubham    India    Tech           5                   4
New_B     Riti    India  Design           7                   7
New_C   Shanky    India     PMO           2                   2
New_D   Shreya    India  Design           2                   0
New_E     Aadi       US     PMO          11                   5
New_F      Sim       US    Tech           4                   4

As observed, we have got a similar output as the above method.

Summary

In this article, we have discussed how to rename DataFrame index in Pandas. Thanks.

Pandas Tutorials -Learn Data Analysis with Python

 

 

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