This thread is part 1 of 2 which will be focused on calculating different statistical values of a series using different alternative methods for each statistic. Firstly, if you are unfamiliar with series objects or you want to learn more about them, have a look at the following threads:

- Building Pandas series with several datatypes.
- Filtering out values from a series.
- Finding unique elements in two series.
- Assign a series’ index a name.

The following statistical calculations of a series will be covered in this thread:

- Minimum Value
- Maximum Value

However, if you want to learn more series statistics, then have a look at the second part of this thread: Calculating series statistics part 2.

## The minimum value

#### 1. Using 'min()' method:

- The
`min()`

method of a Pandas series returns the minimum value in the series.

#### 2. Using 'nsmallest()' method:

- The
`nsmallest()`

method returns the smallest`n`

values in the series. To find the first minimum value, we can use`n=1`

.

#### 3. Using 'idxmin()' method:

- The
`idxmin()`

method returns the index of the minimum value in the series.

#### 4. Using 'np.min()' method:

- The
`np.min()`

is a NumPy function that is used to find the minimum value from a collection of values.

## The maximum value

#### 1. Using 'max()' method:

- The
`max()`

method of a Pandas series returns the maximum value in the series.

#### 2. Using 'nlargest()' method:

- The
`nlargest()`

method returns the largest`n`

values in the series. To find the first maximum value, we can use`n=1`

.

#### 3. Using 'idxmax()' method:

- The
`idxmax()`

method returns the index of the maximum value in the series.

#### 4. Using 'np.max()' method:

- The
`np.max()`

is a NumPy function that is used to find the maximum value from a collection of values.