Pandas – How to reset index in a given DataFrame

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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