How to Reset Index of Pandas DataFrame? Examples

Pandas Reset Index of DataFrame

When you concatenate, sort, join or do some rearrangements with your DataFrame, the index gets shuffled or out of order.

To reset the index of a dataframe, you can use pandas.DataFrame.reset_index() method.

In this tutorial, you'll learn how to reset the index of a given DataFrame using DataFrame.reset_index() method.

Syntax of reset_index()

The syntax of DataFrame.reset_index() function is given below.

DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='')

To reset the index, pass the parameters drop=True and inplace=True.

Examples

1. Reset index of DataFrame using reset_index()

In this example, we will concatenate two dataframes and then use reset_index() to re-order the index of the dataframe.

Python Program

import pandas as pd
	
df_1 = pd.DataFrame(
	[['Somu', 68, 84, 78, 96],
	['Kiku', 74, 56, 88, 85],
	['Ajit', 77, 73, 82, 87]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])

df_2 = pd.DataFrame(
	[['Amol', 72, 67, 91, 83],
	['Lini', 78, 69, 87, 92]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])	

#concatenate dataframes
df = pd.concat([df_1, df_2])
#now the index is not in order

# reset index
df.reset_index(drop=True, inplace=True)

#print dataframe
print(df)

Explanation

1. The program imports the pandas library, which is used to work with data in a tabular format.
2. Two DataFrames, df_1 and df_2, are created using the pd.DataFrame() function:
• df_1: Contains data for three students with their scores in 'physics', 'chemistry', 'algebra', and 'calculus'.
• df_2: Contains data for two additional students with similar columns as df_1.
3. The pd.concat() function is used to concatenate the two DataFrames df_1 and df_2 vertically. The rows from both DataFrames are combined into one DataFrame.
4. After concatenation, the index values from both DataFrames are preserved, leading to non-sequential indices in the concatenated DataFrame.
5. To reset the index and have it start from 0, the reset_index() method is called with the argument drop=True, which removes the old index and assigns a new default sequential index.
6. The program then prints the final DataFrame, df, showing all rows with the reset index.

Output

2. Reset index of DataFrame using concat()

You can reset the index using concat() function as well. Pass in the argument ignore_index=True to the concat() function.

Python Program

import pandas as pd
	
df_1 = pd.DataFrame(
	[['Somu', 68, 84, 78, 96],
	['Kiku', 74, 56, 88, 85],
	['Ajit', 77, 73, 82, 87]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])

df_2 = pd.DataFrame(
	[['Amol', 72, 67, 91, 83],
	['Lini', 78, 69, 87, 92]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])	

#reset index while concatenating
df = pd.concat([df_1, df_2], ignore_index=True)

#print dataframe
print(df)

Explanation

1. The program imports the pandas library, which is used for data manipulation and analysis.
2. Two DataFrames, df_1 and df_2, are created using the pd.DataFrame() function:
• df_1: Contains data for three students with their scores in 'physics', 'chemistry', 'algebra', and 'calculus'.
• df_2: Contains data for two additional students with similar columns as df_1.
3. The pd.concat() function is used to concatenate df_1 and df_2 along the rows. The argument ignore_index=True ensures that the indices are reset to a default sequential order, starting from 0, without preserving the original index values.
4. The resulting DataFrame, df, contains all the rows from both df_1 and df_2, with a new index assigned to each row.
5. The final DataFrame, df, is printed to show the combined data with the reset index.

Output

   name  physics  chemistry  algebra  calculus
0  Somu       68         84       78        96
1  Kiku       74         56       88        85
2  Ajit       77         73       82        87
3  Amol       72         67       91        83
4  Lini       78         69       87        92

If you have only one dataframe whose index has to be reset, then just pass that dataframe in the list to the concat() function.

Python Program

import pandas as pd
	
df_1 = pd.DataFrame(
	[['Somu', 68, 84, 78, 96],
	['Kiku', 74, 56, 88, 85],
	['Ajit', 77, 73, 82, 87]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])

df_2 = pd.DataFrame(
	[['Amol', 72, 67, 91, 83],
	['Lini', 78, 69, 87, 92]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])	

#concatenate
df = pd.concat([df_1, df_2])
#now the index is not in order

#reset the index
df = pd.concat([df], ignore_index=True)

#print dataframe
print(df)

Video Tutorial - Reset Index of Pandas DataFrame

Summary

In this Pandas Tutorial, we learned how to resent index of Pandas DataFrame.