# How to use Python's statistics functions

Understanding and applying Python's statistics functions.

In this tutorial, we'll explore several useful statistics functions available in the Python Standard Library, specifically within the `statistics`

module. These functions are commonly employed in statistical analysis:

**mean**: Calculates the average value.**median**: Determines the middle value in a dataset.**mode**: Identifies the most frequently occurring value.**standard deviation**: Measures the spread of values in a dataset.

## How to import statistics functions in Python

To utilize these functions, you must first import them from the `statistics`

module as follows:

```
from statistics import mean, median, mode, stdev
```

Once imported, you can call `mean()`

, `median()`

, `mode()`

, and `stdev()`

directly. Since the `statistics`

module is included in the Python Standard Library, no additional package installations are necessary.

## How to define a dataset in Python

Consider a dataset comprising five test scores: 60, 83, 83, 91, and 100. In Python, this data can be stored in a list, which is defined using square brackets `[]`

and separates elements with commas:

```
test_scores = [60, 83, 83, 91, 100]
```

## How to calculate the mean

To compute the mean or average of our test scores, apply the `mean()`

function from the statistics module:

```
average_score = mean(test_scores)
```

The result, `average_score`

, will be `83.4`

.

## How to calculate the median

The median, or middle value of the dataset, is obtained using the `median()`

function. For an odd number of values, it returns the middle value; for an even number, it returns the average of the two middle values:

```
median_score = median(test_scores)
```

Here, `median_score`

will be `83`

.

## How to calculate the mode

The mode, or most frequently occurring value, is calculated using the `mode()`

function. Note that if more than one value is equally common, the function raises a `StatisticsError`

:

```
most_common_score = mode(test_scores)
```

In this case, `most_common_score`

is `83`

.

## How to calculate the standard deviation

Standard deviation, indicating the spread of the data, is calculated with the `stdev()`

function. A larger standard deviation suggests more spread out data, while a smaller one indicates data clustered closely together:

```
score_spread = stdev(test_scores)
```

The `score_spread`

will be approximately `14.84`

.

## Alternative: Importing the entire statistics module

Alternatively, you can import the entire `statistics`

module:

```
import statistics
```

Then, use the functions with their full names, like `statistics.mean(test_scores)`

.

## Summary

The `statistics`

module in Python provides handy functions for basic statistical calculations. You can import specific functions or the entire module depending on your needs. This module offers functions like `mean()`

, `median()`

, `mode()`

, and `stdev()`

, facilitating the computation of average, middle value, most common value, and data spread, respectively, in a given dataset.