How to find the minimum value across multiple columns in Pandas?

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You can use the following methods to find the minimum value across multiple columns in a pandas DataFrame:

Method 1: Find Minimum Value Across Multiple Columns

df[['col1', 'col2', 'col3']].min(axis=1)

Method 2: Add New Column Containing Minimum Value Across Multiple Columns

df['new_col'] = df[['col1', 'col2', 'col3']].min(axis=1)

The following examples show how to use each of these methods in practice with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G'],
                   'points': [28, 17, 19, 14, 23, 26, 5],
                   'rebounds': [5, 6, 4, 7, 14, 12, 9],
                   'assists': [10, 13, 7, 8, 4, 5, 8]})

#view DataFrame
print(df)

  player  points  rebounds  assists
0      A      28         5       10
1      B      17         6       13
2      C      19         4        7
3      D      14         7        8
4      E      23        14        4
5      F      26        12        5
6      G       5         9        8

Example 1: Find Minimum Value Across Multiple Columns

The following code shows how to find the minimum value in each row across the points and rebounds columns:

#find minimum value across points and rebounds columns
df[['points', 'rebounds']].min(axis=1)

0     5
1     6
2     4
3     7
4    14
5    12
6     5
dtype: int64

Here’s how to interpret the output:

• The minimum value across the points and rebounds columns for the first row was 5.
• The minimum value across the points and rebounds columns for the second row was 6.
• The minimum value across the points and rebounds columns for the third row was 4.

And so on.

Example 2: Add New Column Containing Minimum Value Across Multiple Columns

The following code shows how to add a new column to the DataFrame that contains the minimum value in each row across the points and rebounds columns:

#add new column that contains min value across points and rebounds columns
df['min_points_rebs'] = df[['points', 'rebounds']].min(axis=1)

#view updated DataFrame
print(df)

  player  points  rebounds  assists  min_points_rebs
0      A      28         5       10                5
1      B      17         6       13                6
2      C      19         4        7                4
3      D      14         7        8                7
4      E      23        14        4               14
5      F      26        12        5               12
6      G       5         9        8                5

The new column titled min_points_rebs now contains the minimum value across the points and rebounds columns for each row in the DataFrame.