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
Pandas
module. - 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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