Reset Index of DataFrame in Pandas

Reset Index of DataFrame

To reset the index of a DataFrame to a default one in Pandas, call reset_index() method on this DataFrame.

In this tutorial, we will learn the syntax of DataFrame.reset_index() method and how to use this method to reset the index of this DataFrame to default index.

Syntax

The syntax of pandas DataFrame.reset_index() method is

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

where

Parameter	Value	Description
level	int, str, tuple, or list. default value is None.	Only remove the given levels from the index. Removes all levels by default.
drop	bool. default value is False.	Do not try to insert index into dataframe columns. This resets the index to the default integer index.
inplace	bool. default value is False.	Modify the DataFrame in place (do not create a new object).
col_level	int or str. default value is 0.	If the columns have multiple levels, determines which level the labels are inserted into. By default it is inserted into the first level.
col_fill	object. default value is ‘’.	If the columns have multiple levels, determines how the other levels are named. If None then the index name is repeated.

Return Value

• DataFrame or
• None if inplace=True.

Examples

Reset Index of DataFrame

In the following program, we take a DataFrame with some specific index, and then set the index to default index using reset_index().

Example.py

import pandas as pd

data = {'col_1': [10, 15, 20, 25], 'col_2': [50, 55, 60, 65]}
df = pd.DataFrame(data, index=['a', 'b', 'c', 'd'])

result = df.reset_index()

print('Original DataFrame')
print(df)
print('\nDataFrame with Index Reset')
print(result)

Output

Original DataFrame
   col_1  col_2
a     10     50
b     15     55
c     20     60
d     25     65

DataFrame with Index Reset
  index  col_1  col_2
0     a     10     50
1     b     15     55
2     c     20     60
3     d     25     65

Avoid adding Index as Column to DataFrame

When we reset the index, the old index is added as a column to the resulting DataFrame. We can avoid this happening by passing True for the parameter drop.

Example.py

import pandas as pd

data = {'col_1': [10, 15, 20, 25], 'col_2': [50, 55, 60, 65]}
df = pd.DataFrame(data, index=['a', 'b', 'c', 'd'])

result = df.reset_index(drop=True)

print('Original DataFrame')
print(df)
print('\nDataFrame with Index Reset')
print(result)

Output

Original DataFrame
   col_1  col_2
a     10     50
b     15     55
c     20     60
d     25     65

DataFrame with Index Reset
   col_1  col_2
0     10     50
1     15     55
2     20     60
3     25     65

Reset Index of DataFrame In-place

reset_index() method by default does not modify the original DataFrame. We can tell reset_index() method to modify the DataFrame in-place and not return anything, by passing True to the parameter inplace.

Example.py

import pandas as pd

data = {'col_1': [10, 15, 20, 25], 'col_2': [50, 55, 60, 65]}
df = pd.DataFrame(data, index=['a', 'b', 'c', 'd'])

df.reset_index(inplace=True)

print(df)

Output

  index  col_1  col_2
0     a     10     50
1     b     15     55
2     c     20     60
3     d     25     65

Conclusion

In this Pandas Tutorial, we learned the syntax of reset_index() method and how to reset the index of given DataFrame to a default index using this pandas DataFrame.reset index() method.