# Statistical Functions in Python | Set 1 (Averages and Measure of Central Location)

Python has the ability to manipulate some statistical data and calculate results of various statistical operations using the file “statistics“, useful in domain of mathematics.

Important Average and measure of central location functions :

1. mean() :- This function returns the mean or average of the data passed in its arguments. If passed argument is empty, StatisticsError is raised.

2. mode() :- This function returns the number with maximum number of occurrences. If passed argument is empty, StatisticsError is raised.

 `# Python code to demonstrate the working of ` `# mean() and mode() ` ` `  `# importing statistics to handle statistical operations ` `import` `statistics ` ` `  `# initializing list ` `li ``=` `[``1``, ``2``, ``3``, ``3``, ``2``, ``2``, ``2``, ``1``] ` ` `  `# using mean() to calculate average of list elements ` `print` `(``"The average of list values is : "``,end``=``"") ` `print` `(statistics.mean(li)) ` ` `  `# using mode() to print maximum occurring of list elements ` `print` `(``"The maximum occurring element is  : "``,end``=``"") ` `print` `(statistics.mode(li)) `

Output:

```The average of list values is : 2.0
The maximum occurring element is  : 2
```

3. median() :- This function is used to calculate the median, i.e middle element of data. If passed argument is empty, StatisticsError is raised.

4. median_low() :- This function returns the median of data in case of odd number of elements, but in case of even number of elements, returns the lower of two middle elements. If passed argument is empty, StatisticsError is raised.

5. median_high() :- This function returns the median of data in case of odd number of elements, but in case of even number of elements, returns the higher of two middle elements. If passed argument is empty, StatisticsError is raised.

 `# Python code to demonstrate the working of ` `# median(), median_low() and median_high() ` ` `  `# importing statistics to handle statistical operations ` `import` `statistics ` ` `  `# initializing list ` `li ``=` `[``1``, ``2``, ``2``, ``3``, ``3``, ``3``] ` ` `  `# using median() to print median of list elements ` `print` `(``"The median of list element is : "``,end``=``"") ` `print` `(statistics.median(li)) ` ` `  `# using median_low() to print low median of list elements ` `print` `(``"The lower median of list element is : "``,end``=``"") ` `print` `(statistics.median_low(li)) ` ` `  `# using median_high() to print high median of list elements ` `print` `(``"The higher median of list element is : "``,end``=``"") ` `print` `(statistics.median_high(li)) `

Output:

```The median of list element is : 2.5
The lower median of list element is : 2
The higher median of list element is : 3
```

6. median_grouped() :- This function is used to compute group median, i.e 50th percentile of the data. If passed argument is empty, StatisticsError is raised.

 `# Python code to demonstrate the working of ` `# median_grouped() ` ` `  `# importing statistics to handle statistical operations ` `import` `statistics ` ` `  `# initializing list ` `li ``=` `[``1``, ``2``, ``2``, ``3``, ``3``, ``3``] ` ` `  `# using median_grouped() to calculate 50th percentile ` `print` `(``"The 50th percentile of data is : "``,end``=``"") ` `print` `(statistics.median_grouped(li)) `

Output:

```The 50th percentile of data is : 2.5
```

Statistical Functions in Python | Set 2 ( Measure of Spread)

This article is contributed by Manjeet Singh. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

My Personal Notes arrow_drop_up

Improved By : Akanksha_Rai

Article Tags :

3

Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.