How to Switch the Index Column In Pandas?

7 minutes read

To switch the index column in Pandas, you can make use of the set_index() function and reset_index() function.


To set a different column as the index, you can use the set_index() function by specifying the column name as an argument. This will replace the existing index with the specified column.


Here's an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
import pandas as pd

# Create a dataframe
df = pd.DataFrame({'Name': ['John', 'Alice', 'Bob'],
                   'Age': [25, 30, 35],
                   'City': ['New York', 'London', 'Paris']})

# Set 'Name' column as the index
df.set_index('Name', inplace=True)

print(df)


Output:

1
2
3
4
5
        Age      City
Name                 
John     25  New York
Alice    30    London
Bob      35     Paris


To reset the index column to its default numerical index, you can use the reset_index() function. It will remove the current index and set the default index.


Here's an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
import pandas as pd

# Create a dataframe
df = pd.DataFrame({'Name': ['John', 'Alice', 'Bob'],
                   'Age': [25, 30, 35],
                   'City': ['New York', 'London', 'Paris']})

# Set 'Name' column as the index
df.set_index('Name', inplace=True)

# Reset the index
df.reset_index(inplace=True)

print(df)


Output:

1
2
3
4
   Name  Age      City
0  John   25  New York
1 Alice   30    London
2   Bob   35     Paris


By using these methods, you can easily switch the index column in Pandas as per your requirements.

Best Python Books of March 2024

1
Learning Python, 5th Edition

Rating is 5 out of 5

Learning Python, 5th Edition

2
Head First Python: A Brain-Friendly Guide

Rating is 4.9 out of 5

Head First Python: A Brain-Friendly Guide

3
Python for Beginners: 2 Books in 1: Python Programming for Beginners, Python Workbook

Rating is 4.8 out of 5

Python for Beginners: 2 Books in 1: Python Programming for Beginners, Python Workbook

4
Python All-in-One For Dummies (For Dummies (Computer/Tech))

Rating is 4.7 out of 5

Python All-in-One For Dummies (For Dummies (Computer/Tech))

5
Python for Everybody: Exploring Data in Python 3

Rating is 4.6 out of 5

Python for Everybody: Exploring Data in Python 3

6
Learn Python Programming: The no-nonsense, beginner's guide to programming, data science, and web development with Python 3.7, 2nd Edition

Rating is 4.5 out of 5

Learn Python Programming: The no-nonsense, beginner's guide to programming, data science, and web development with Python 3.7, 2nd Edition

7
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

Rating is 4.4 out of 5

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition


How to change the index column to a categorical data type in Pandas?

To change the index column to a categorical data type in Pandas, you can use the pd.Categorical() function along with the set_index() method.


Here is an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
import pandas as pd

# Create a sample DataFrame
data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)

# Convert the index column to categorical
df.index = pd.Categorical(df.index)

print(df)


Output:

1
2
3
4
        A  B
0  1  4
1  2  5
2  3  6


In this example, we first import the necessary libraries and create a sample DataFrame. Then, we convert the index column to a categorical data type using the pd.Categorical() function. Finally, we assign the categorical index back to the DataFrame using the set_index() method.


How to change the order of the index column in Pandas?

To change the order of the index column in pandas, you can use the reindex function. Here's an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
import pandas as pd

# Create a sample dataframe
data = {'Name': ['John', 'Alice', 'Bob'],
        'Age': [25, 30, 35],
        'City': ['New York', 'London', 'Paris']}
df = pd.DataFrame(data)

# Set 'Name' column as index
df.set_index('Name', inplace=True)

# Change the order of index column
new_order = ['Bob', 'Alice', 'John']
df = df.reindex(new_order)

# Print the dataframe
print(df)


Output:

1
2
3
4
5
       Age      City
Name                
Bob     35     Paris
Alice   30    London
John    25  New York


In this example, we first set the 'Name' column as the index using the set_index function. Then, we define the new order of the index column as a list ['Bob', 'Alice', 'John']. Finally, we use the reindex function to change the order of the index column based on the new order list.


What is the purpose of the index_col parameter in the read_csv function in Pandas?

The index_col parameter in the read_csv function in Pandas is used to specify which column(s) should be used as the index of the resulting DataFrame. By default, Pandas assigns a numeric range index (0, 1, 2, ...) to the DataFrame. However, by specifying an index_col, you can use one or more columns from the CSV file as the unique identifier(s) for each row of data.

Facebook Twitter LinkedIn Telegram Whatsapp Pocket

Related Posts:

To describe a column in Pandas Python, you can utilize the describe() method which provides a summary of statistical information about the column. This descriptive statistics summary helps you gain a better understanding of the data distribution in that specif...
To convert a column with JSON data into a dataframe column in Pandas, you can use the json_normalize function. Here are the steps you can follow:Import the necessary libraries: import pandas as pd import json Read the JSON data into a Pandas dataframe: df = pd...
To create a column based on a condition in Pandas, you can use the syntax of DataFrame.loc or DataFrame.apply functions. Here is a text-based description of the process:Import the Pandas library: Begin by importing the Pandas library using the line import pand...