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Pandas – How to reset index in a given DataFrame

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  • Last Updated : 25 Aug, 2021

Let us see how to reset the index of a DataFrame after dropping some of the rows from the DataFrame.
Approach : 

  1. Import the Pandas module.
  2. Create a DataFrame.
  3. Drop some rows from the DataFrame using the drop() method.
  4. Reset the index of the DataFrame using the reset_index() method.
  5. Display the DataFrame after each step. 

Python3




# importing the modules
import pandas as pd
import numpy as np
 
# creating a DataFrame
ODI_runs = {'name': ['Tendulkar', 'Sangakkara', 'Ponting',
                      'Jayasurya', 'Jayawardene', 'Kohli',
                      'Haq', 'Kallis', 'Ganguly', 'Dravid'],
            'runs': [18426, 14234, 13704, 13430, 12650,
                     11867, 11739, 11579, 11363, 10889]}
df = pd.DataFrame(ODI_runs)
 
# displaying the original DataFrame
print("Original DataFrame :")
print(df)
 
# dropping the 0th and the 1st index
df = df.drop([0, 1])
 
# displaying the altered DataFrame
print("DataFrame after removing the 0th and 1st row")
print(df)
 
# resetting the DataFrame index
df = df.reset_index()
 
# displaying the DataFrame with new index
print("Dataframe after resetting the index")
print(df)

Output : 
 

 

 

 

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