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 modulesimport pandas as pdimport numpy as np# creating a DataFrameODI_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 DataFrameprint("Original DataFrame :")print(df)# dropping the 0th and the 1st indexdf = df.drop([0, 1])# displaying the altered DataFrameprint("DataFrame after removing the 0th and 1st row")print(df)# resetting the DataFrame indexdf = df.reset_index()# displaying the DataFrame with new indexprint("Dataframe after resetting the index")print(df) |
Output :
