Pandas Select Columns by Index

One of the most important aspects of data analysis is to select the required data from the dataset. This helps us to analyze the data in a better way. It is a way to filter out the data we don't need and work with the data we need.

To do this, we need to select the columns that we want to work with. In this tutorial, we will learn how to select columns by index in pandas.

    Table of Contents

  1. Select Single Column by Index
  2. Select Multiple Columns by Index
  3. Select Columns by Index in Range
  4. Conclusion

1. Select Single Column by Index

To select columns by index, we use the iloc() function on the DataFrame object.

The iloc() function takes two parameters, the row index and the column index. If we want to select all the rows, we can pass : as the row index.

Here is an example of selecting a single column by index.

import pandas as pd

# Creating a sample DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Emma'],
        'Age': [25, 30, 35, 40, 45],
        'City': ['NY', 'LA', 'SF', 'NY', 'LA']}

df = pd.DataFrame(data)

# Selecting columns by column index
# Selecting the first column (index = 0)
print(df.iloc[:, 0])

Output:

0      Alice
1        Bob
2    Charlie
3      David
4       Emma
Name: Name, dtype: object

2. Select Multiple Columns by Index

To select multiple columns by index, pass a list of column indexes you want to select to the iloc() function.

If you want to select the second and third columns, pass [1, 2] as the column index.

import pandas as pd

# Creating a sample DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Emma'],
        'Age': [25, 30, 35, 40, 45],
        'City': ['NY', 'LA', 'SF', 'NY', 'LA']}

df = pd.DataFrame(data)

# Selecting columns by column index
# Selecting the second and third column (index = 1, 2)
print(df.iloc[:, [1, 2]])

Output:

   Age City
0   25   NY
1   30   LA
2   35   SF
3   40   NY
4   45   LA

3. Select Columns by Index in Range

Let your dataframe has 10 columns and you want to select columns from 3 to 7. You can do this by passing 3:8 as the column index, i.e. start_index:end_index+1.

Here is an example of selecting columns in range by index.

import pandas as pd

# Creating a sample DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Emma'],
        'Age': [25, 30, 35, 40, 45],
        'City': ['NY', 'LA', 'SF', 'NY', 'LA']}

df = pd.DataFrame(data)

# Selecting columns by column index
# Selecting the columns from index 0 to 2
print(df.iloc[:, 0:3])

Output:

      Name  Age City
0    Alice   25   NY
1      Bob   30   LA
2  Charlie   35   SF
3    David   40   NY
4     Emma   45   LA

Conclusion

You can now select columns by index in pandas with different variations. You can select a single column, multiple columns or columns in range by index.

Learn how to select columns by name in pandas.