How to Convert Index as Column in Pandas

This tutorial shows how you can convert dataframe index as a column in Python. The basic syntax is to use reset_index() (see below).

df_name.reset_index()

Starting Dataframe for Examples 1 and 2

The following is the sample dataframe that will be used in Examples 1 and 2.

(Note that, Example 3 will use a different dataframe.)

import pandas as pd
d = {'Brand': ['Tesla', 'Ford','Toyota'], 'Count': [3, 4, 5]}
df = pd.DataFrame(data=d)
print(df)

The following the printout of the sample dataframe. 

    Brand  Count
0   Tesla      3
1    Ford      4
2  Toyota      5

Example 1: use reset_index()

You can move the index of a dataframe as a column using reset_index() in Pandas. The following is the example. 

df_changed=df.reset_index()
print(df_changed)

The following is the ouput. 

	index	Brand	Count
0	0	Tesla	3
1	1	Ford	4
2	2	Toyota	5

Example 2: Use inplace in reset_index()

You can add reset_index(inplace=True) to save the index as a new column. The default is inplace=False.

When you set inplace = True, the reset_index method will not create a new dataframe. Instead, it will directly modify and overwrite the original dataframe.

The follwoing is to apply reset_index(inplace=True). 

# Applying inplace=True
df.reset_index(inplace=True)

# print the result
print("After using inplace:\n",df)

The following is the output. As we can see, it has been added a column named “index”. Note that, the true index is without column name in this case. 

After using inplace:
    index   Brand  Count
0      0   Tesla      3
1      1    Ford      4
2      2  Toyota      5

Example 3: Use drop in reset_index()

You can use the drop=True to not save the index as a column. The default is drop=False.

Step 1: Create a dataframe

The following is the sample dataframe. The index is CA, MA, WA. 

# Create a sample data frame
import pandas as pd
d = {'Brand': ['Tesla', 'Ford','Toyota'], 'Count': [3, 4, 5]}
df = pd.DataFrame(data=d,index=['CA','MA','WA'])
print(df)

The following is the original dataframe.

     Brand  Count
CA   Tesla      3
MA    Ford      4
WA  Toyota      5

Step 2: Using drop=True in reset_index()

# add drop=True 
df_new=df.reset_index(drop=True)
print("Using drop=True:\n",df_new)
Using drop=True:
     Brand  Count
0   Tesla      3
1    Ford      4
2  Toyota      5

Further Reading