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.

**Additional Resources**

The following tutorials explain how to perform other common tasks in pandas:

Pandas: How to Move Column to Front of DataFrame

Pandas: How to Check if Column Contains String

Pandas: How to Add Empty Column to DataFrame