Pandas DataFrame: Reset index in a given DataFrame

Last update on May 01 2025 12:54:39 (UTC/GMT +8 hours)

37. Reset DataFrame Index

Write a Pandas program to reset index in a given DataFrame.

Sample data:
Original DataFrame
attempts name qualify score
0 1 Anastasia yes 12.5
1 3 Dima no 9.0
2 2 Katherine yes 16.5
3 3 James no NaN
4 2 Emily no 9.0
5 3 Michael yes 20.0
6 1 Matthew yes 14.5
7 1 Laura no NaN
8 2 Kevin no 8.0
9 1 Jonas yes 19.0
After removing first and second rows
attempts name qualify score
2 2 Katherine yes 16.5
3 3 James no NaN
4 2 Emily no 9.0
5 3 Michael yes 20.0
6 1 Matthew yes 14.5
7 1 Laura no NaN
8 2 Kevin no 8.0
9 1 Jonas yes 19.0
Reset the Index:
index attempts name qualify score
0 2 2 Katherine yes 16.5
1 3 3 James no NaN
2 4 2 Emily no 9.0
3 5 3 Michael yes 20.0
4 6 1 Matthew yes 14.5
5 7 1 Laura no NaN
6 8 2 Kevin no 8.0
7 9 1 Jonas yes 19.0

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
df = pd.DataFrame(exam_data)
print("Original DataFrame")
print(df)
print("\nAfter removing first and second rows")
df = df.drop([0, 1])
print(df)
print("\nReset the Index:")
df = df.reset_index()
print(df)

Sample Output:

  Original DataFrame
   attempts       name qualify  score
0         1  Anastasia     yes   12.5
1         3       Dima      no    9.0
2         2  Katherine     yes   16.5
3         3      James      no    NaN
4         2      Emily      no    9.0
5         3    Michael     yes   20.0
6         1    Matthew     yes   14.5
7         1      Laura      no    NaN
8         2      Kevin      no    8.0
9         1      Jonas     yes   19.0

After removing first and second rows
   attempts       name qualify  score
2         2  Katherine     yes   16.5
3         3      James      no    NaN
4         2      Emily      no    9.0
5         3    Michael     yes   20.0
6         1    Matthew     yes   14.5
7         1      Laura      no    NaN
8         2      Kevin      no    8.0
9         1      Jonas     yes   19.0

Reset the Index:
   index  attempts       name qualify  score
0      2         2  Katherine     yes   16.5
1      3         3      James      no    NaN
2      4         2      Emily      no    9.0
3      5         3    Michael     yes   20.0
4      6         1    Matthew     yes   14.5
5      7         1      Laura      no    NaN
6      8         2      Kevin      no    8.0
7      9         1      Jonas     yes   19.0

Explanation:

The said code first creates a Pandas DataFrame df from the dictionary ‘exam_data’. The DataFrame contains information about students' names, scores, number of attempts and whether they qualify or not.

df = df.drop([0, 1]): This code drops the rows with index 0 and 1 from the DataFrame using the drop() method.

df = df.reset_index(): This code resets the index using the reset_index() method, which creates a new column called "index" with the index values before resetting.

Finally, it prints the resulting DataFrame with the dropped rows and the new index.

For more Practice: Solve these Related Problems:

Write a Pandas program to reset the index of a DataFrame after dropping some rows and then add the old index as a new column.
Write a Pandas program to reset the index of a DataFrame in place and then sort the DataFrame by the new index.
Write a Pandas program to reset the index of a DataFrame with a custom starting index and then verify the output.
Write a Pandas program to reset a DataFrame index after filtering rows and then format the new index as strings.

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