# Python Math Min

Groupby minimum in pandas python can be accomplished by groupby() function. Groupby minimum of multiple column and single column in pandas is accomplished by multiple ways some among them are groupby() function and aggregate() function. let’s see how to

- Groupby single column in pandas – groupby minimum
- Groupby multiple columns in pandas – groupby minimum
- Groupby minimum using aggregate() function
- Groupby minimum using pivot() function.
- using reset_index() function for groupby multiple columns and single columns

First let’s create a dataframe

**df1 will be**

- Python min List is one of the List functions used to return the minimum value in a list. In this section, we discuss how to use this Python List minimum function with practical examples.
- To learn more about how mathematical operators work in Python, read our beginner’s guide to Python math operators. The Python += operator performs an addition operator and then assigns the result of the operation to a variable. The += operator is an example of a Python assignment operator.

**Groupby single column – groupby min pandas python:**

groupby() function takes up the column name as argument followed by min() function as shown below

We will groupby min with single column (State), so the result will be

## Python Math Min Function

Description The java.lang.Math.min (int a, int b) returns the smaller of two int values. That is, the result is the value closer to negative infinity. If the arguments have the same value, the result is that same value.

**using reset_index()**

**reset_index() **function resets and provides the new index to the grouped by dataframe and makes them a proper dataframe structure

We will groupby min with “State” column along with the reset_index() will give a proper table structure , so the result will be

**Groupby multiple columns – groupby min pandas python:**

We will groupby min with State and Product columns, so the result will be

**Groupby Min of multiple columns in pandas using reset_index()**

**reset_index() **function resets and provides the new index to the grouped by dataframe and makes them a proper dataframe structure

Photos minerals. We will groupby min with “Product” and “State” columns along with the reset_index() will give a proper table structure , so the result will be

**Using aggregate() function:**

**agg() **function takes ‘min’ as input which performs groupby min, reset_index() assigns the new index to the grouped by dataframe and makes them a proper dataframe structure

We will compute groupby min using agg() function with “Product” and “State” columns along with the reset_index() will give a proper table structure , so the result will be

**using Pivot() function :**

## Python Math Mine

You can use the pivot() functionality to arrange the data in a nice table.

## Python Minimum Of Two Values

groupby() function along with the pivot function() gives a nice table format as shown below