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.
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)
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Output :