# How to Find the Minimum Value by Group in Pandas

You can use the following methods to find the minimum value by group in a pandas DataFrame:

Method 1: Groupby minimum of one column

```df.groupby('group_column')['values_column'].min()
```

Method 2: Groupby minimum of multiple columns

`df.groupby('group_column')['values_column1', 'values_column2'].min()`

The following examples show how to use each method in practice with the following pandas DataFrame:

```import pandas as pd

#create pandas DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'B', 'C', 'C'],
'points':[24, 23, 27, 11, 14, 8, 13],
'rebounds': [11, 8, 7, 6, 6, 5, 12]})

#display DataFrame
print(df)

team  points  rebounds
0    A      24        11
1    A      23         8
2    B      27         7
3    B      11         6
4    B      14         6
5    C       8         5
6    C      13        12```

## Example 1: Groupby Minimum of One Column

The following code shows how to find the minimum value of the points column, grouped by the team column:

```#find minimum value of points, grouped by team
df.groupby('team')['points'].min()

team
A    23
B    11
C     8
Name: points, dtype: int64
```

From the output we can see:

• The minimum value of points for team A is 23.
• The minimum value of points for team B is 11.
• The minimum value of points for team C is 8.

## Example 2: Groupby Minimum of Multiple Columns

The following code shows how to find the minimum value of the points and rebounds columns, grouped by the team column:

```#find minimum value of points and rebounds, grouped by team
df.groupby('team')[['points', 'rebounds']].min()

points  rebounds
team
A	23	   8
B	11	   6
C	8	   5
```

From the output we can see:

Team A:

• Minimum points: 23
• Minimum rebounds: 8

Team B:

• Minimum points: 11
• Minimum rebounds: 6

Team C:

• Minimum points: 8
• Minimum rebounds: 5

Note: It’s important that you use double brackets when specifying the value columns, otherwise you may receive an error.