Pandas - How to reset index in a given DataFrame Last Updated : 25 Aug, 2021 Comments Improve Suggest changes Like Article Like Report 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) Output : Comment More infoAdvertise with us Next Article Pandas - How to reset index in a given DataFrame A ajaynair710 Follow Improve Article Tags : Python Python-pandas Python pandas-dataFrame pandas-dataframe-program Practice Tags : python Similar Reads Reset Index in Pandas Dataframe Let’s discuss how to reset the index in Pandas DataFrame. Often We start with a huge data frame in Pandas and after manipulating/filtering the data frame, we end up with a much smaller data frame. When we look at the smaller data frame, it might still carry the row index of the original data frame. 6 min read Pandas DataFrame.reset_index() In Pandas, reset_index() method is used to reset the index of a DataFrame. By default, it creates a new integer-based index starting from 0, making the DataFrame easier to work with in various scenarios, especially after performing operations like filtering, grouping or multi-level indexing. Example 3 min read How to drop rows in Pandas DataFrame by index labels? Dropping rows in a Pandas DataFrame by index labels is a common operation when you need to remove specific rows based on their index positions. For example, we are working with a DataFrame that contains details of students, including their names, ages, and universities. Initially, the DataFrame has 5 min read How to Reference the Next Row in a Pandas DataFrame To reference the next row in a Pandas DataFrame, you can use the .shift() method. This method shifts the data by a specified number of periods (rows), allowing you to access the previous or next row's values in a given column. It's useful for comparing consecutive rows or calculating differences bet 4 min read How to Reverse Row in Pandas DataFrame? In this article, we will learn how to reverse a row in a pandas data frame using Python. With the help of Pandas, we can perform a reverse operation by using loc(), iloc(), reindex(), slicing, and indexing on a row of a data set. Creating Dataframe Let’s create a simple data frame with a dictionar 3 min read Like