How to Select Pandas DataFrame Columns

Suraj Joshi Feb 02, 2024
  1. Select Columns From a Pandas DataFrame Using Indexing Operation
  2. Select Columnns From a Pandas DataFrame Using the DataFrame.drop() Method
  3. Select Columns From a Pandas DataFrame Using the DataFrame.filter() Method
How to Select Pandas DataFrame Columns

This tutorial explains how we can select columns from a Pandas DataFrame by indexing or using the DataFrame.drop() and DataFrame.filter() methods.

We will use the DataFrame df as below to explain how we can select columns from a Pandas DataFrame.

import pandas as pd

df = pd.DataFrame(
    {
        "A": [302, 504, 708, 103, 343, 565],
        "B": [100, 300, 400, 200, 400, 700],
        "C": [300, 400, 350, 100, 1000, 400],
        "D": [10, 15, 5, 0, 2, 7],
        "E": [4, 5, 6, 7, 8, 9],
    }
)

print(df)

Output:

     A    B     C   D  E
0  302  100   300  10  4
1  504  300   400  15  5
2  708  400   350   5  6
3  103  200   100   0  7
4  343  400  1000   2  8
5  565  700   400   7  9

Select Columns From a Pandas DataFrame Using Indexing Operation

import pandas as pd

df = pd.DataFrame(
    {
        "A": [302, 504, 708, 103, 343, 565],
        "B": [100, 300, 400, 200, 400, 700],
        "C": [300, 400, 350, 100, 1000, 400],
        "D": [10, 15, 5, 0, 2, 7],
        "E": [4, 5, 6, 7, 8, 9],
    }
)

derived_df = df[["A", "C", "E"]]

print("The initial DataFrame is:")
print(df, "\n")

print("The DataFrame with A,C and E columns is:")
print(derived_df, "\n")

Output:

The initial DataFrame is:
     A    B     C   D  E
0  302  100   300  10  4
1  504  300   400  15  5
2  708  400   350   5  6
3  103  200   100   0  7
4  343  400  1000   2  8
5  565  700   400   7  9 

The DataFrame with A,C and E columns is:
     A     C  E
0  302   300  4
1  504   400  5
2  708   350  6
3  103   100  7
4  343  1000  8
5  565   400  9 

It selects the columns A, C, and E from the DataFrame df and assigns these columns to the derived_df DataFrame.

Select Columnns From a Pandas DataFrame Using the DataFrame.drop() Method

import pandas as pd

df = pd.DataFrame(
    {
        "A": [302, 504, 708, 103, 343, 565],
        "B": [100, 300, 400, 200, 400, 700],
        "C": [300, 400, 350, 100, 1000, 400],
        "D": [10, 15, 5, 0, 2, 7],
        "E": [4, 5, 6, 7, 8, 9],
    }
)

derived_df = df.drop(["B", "D"], axis=1)

print("The initial DataFrame is:")
print(df, "\n")

print("The DataFrame with A,C and E columns is:")
print(derived_df, "\n")

Output:

The initial DataFrame is:
     A    B     C   D  E
0  302  100   300  10  4
1  504  300   400  15  5
2  708  400   350   5  6
3  103  200   100   0  7
4  343  400  1000   2  8
5  565  700   400   7  9 

The DataFrame with A,C and E columns is:
     A     C  E
0  302   300  4
1  504   400  5
2  708   350  6
3  103   100  7
4  343  1000  8
5  565   400  9 

It drops the columns B and D from the DataFrame df and assigns the remaining columns to the derived_df. Alternatively, it selects all the columns except B and D and assigns them to the derived_df DataFrame.

Select Columns From a Pandas DataFrame Using the DataFrame.filter() Method

import pandas as pd

df = pd.DataFrame(
    {
        "A": [302, 504, 708, 103, 343, 565],
        "B": [100, 300, 400, 200, 400, 700],
        "C": [300, 400, 350, 100, 1000, 400],
        "D": [10, 15, 5, 0, 2, 7],
        "E": [4, 5, 6, 7, 8, 9],
    }
)

derived_df = df.filter(["A", "C", "E"])

print("The initial DataFrame is:")
print(df, "\n")

print("The DataFrame with A,C and E columns is:")
print(derived_df, "\n")

Output:

The initial DataFrame is:
     A    B     C   D  E
0  302  100   300  10  4
1  504  300   400  15  5
2  708  400   350   5  6
3  103  200   100   0  7
4  343  400  1000   2  8
5  565  700   400   7  9 

The DataFrame with A,C and E columns is:
     A     C  E
0  302   300  4
1  504   400  5
2  708   350  6
3  103   100  7
4  343  1000  8
5  565   400  9

It extracts or filters the columns A, C, and E from the DataFrame df and assigns it to the DataFrame derived_df.

Author: Suraj Joshi
Suraj Joshi avatar Suraj Joshi avatar

Suraj Joshi is a backend software engineer at Matrice.ai.

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