Python | Pandas DataFrame.reset_index()

Difficulty Level : Easy
Last Updated : 17 Sep, 2018

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas reset_index() is a method to reset index of a Data Frame. reset_index() method sets a list of integer ranging from 0 to length of data as index.

Syntax:
DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill=”)
Parameters:
level: int, string or a list to select and remove passed column from index.
drop: Boolean value, Adds the replaced index column to the data if False.
inplace: Boolean value, make changes in the original data frame itself if True.
col_level: Select in which column level to insert the labels.
col_fill: Object, to determine how the other levels are named.
Return type: DataFrame

To download the CSV file used, Click Here.

Example #1: Resetting index
In this example, to reset index, First name column have been set as index column first and then using reset index a new index have been generated.

# importing pandas package
import pandas as pd
   
# making data frame from csv file
data = pd.read_csv("employees.csv")
   
# setting first name as index column
data.set_index(["First Name"], inplace = True,
                    append = True, drop = True)
   
# resetting index
data.reset_index(inplace = True)
   
# display
data.head()

Output:
As show in the output images, A new index label named level_0 has been generated.

Before reset –

After reset –

Example #2: Operation on Multi level Index
In this example, 2 columns(First name and Gender) are added to the index column and later one level is removed by using reset_index() method.

# importing pandas package
import pandas as pd
   
# making data frame from csv file
data = pd.read_csv("employees.csv")
   
# setting first name as index column
data.set_index(["First Name", "Gender"], inplace = True,
                             append = True, drop = True)
   
# resetting index
data.reset_index(level = 2, inplace = True, col_level = 1)
   
# display
data.head()

Output:
As shown in the output image, The gender column in the index column was replaced as it’s level was 2.

Before reset –

After reset –

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Python | Pandas DataFrame.reset_index()