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 :
- Import the
Pandasmodule. - Create a DataFrame.
- Drop some rows from the DataFrame using the
drop()method. - Reset the index of the DataFrame using the
reset_index()method. - Display the DataFrame after each step.
# 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 DatFrame index df = df.reset_index() # displaying the DataFrame with new index print("Dataframe after resetting the index") print(df) |
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Output :
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