Tutorials References Menu

Python Tutorial

Python HOME Python Intro Python Get Started Python Syntax Python Comments Python Variables Python Data Types Python Numbers Python Casting Python Strings Python Booleans Python Operators Python Lists Python Tuples Python Sets Python Dictionaries Python If...Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Scope Python Modules Python Dates Python Math Python JSON Python RegEx Python PIP Python Try...Except Python User Input Python String Formatting

File Handling

Python File Handling Python Read Files Python Write/Create Files Python Delete Files

Python Modules

NumPy Tutorial Pandas Tutorial SciPy Tutorial

Python Matplotlib

Matplotlib Intro Matplotlib Get Started Matplotlib Pyplot Matplotlib Plotting Matplotlib Markers Matplotlib Line Matplotlib Labels Matplotlib Grid Matplotlib Subplots Matplotlib Scatter Matplotlib Bars Matplotlib Histograms Matplotlib Pie Charts

Machine Learning

Getting Started Mean Median Mode Standard Deviation Percentile Data Distribution Normal Data Distribution Scatter Plot Linear Regression Polynomial Regression Multiple Regression Scale Train/Test Decision Tree

Python MySQL

MySQL Get Started MySQL Create Database MySQL Create Table MySQL Insert MySQL Select MySQL Where MySQL Order By MySQL Delete MySQL Drop Table MySQL Update MySQL Limit MySQL Join

Python MongoDB

MongoDB Get Started MongoDB Create Database MongoDB Create Collection MongoDB Insert MongoDB Find MongoDB Query MongoDB Sort MongoDB Delete MongoDB Drop Collection MongoDB Update MongoDB Limit

Python Reference

Python Overview Python Built-in Functions Python String Methods Python List Methods Python Dictionary Methods Python Tuple Methods Python Set Methods Python File Methods Python Keywords Python Exceptions Python Glossary

Module Reference

Random Module Requests Module Statistics Module Math Module cMath Module

Python How To

Remove List Duplicates Reverse a String Add Two Numbers

Python Examples

Python Examples Python Compiler

Python statistics.median_grouped() Method

❮ Statistic Methods


Example

Calculate the median of grouped continuous data:

# Import statistics Library
import statistics

# Calculate the median of grouped continuous data
print(statistics.median_grouped([1, 2, 3, 4]))
print(statistics.median_grouped([1, 2, 3, 4, 5]))
print(statistics.median_grouped([1, 2, 3, 4], 2))
print(statistics.median_grouped([1, 2, 3, 4], 3))
print(statistics.median_grouped([1, 2, 3, 4], 5))
Try it Yourself »

Definition and Usage

The statistics.median_grouped() method calculates the median of grouped continuous data, calculated as the 50th percentile.

This method treats the data points as continuous data and calculates the 50% percentile median by first finding the median range using specified interval width (default is 1), and then interpolating within that range using the position of the values from the data set that fall in that range.

Tip: The mathematical formula for Grouped Median is: GMedian = L + interval * (N / 2 - CF) / F.

  • L = The lower limit of the median interval
  • interval = The interval width
  • N = The total number of data points
  • CF = The number of data points below the median interval
  • F = The number of data points in the median interval

Syntax

statistics.median_grouped(data, interval)

Parameter Values

Parameter Description
data Required. The data values to be used (can be any sequence, list or iterator)
interval Optional. The class interval. Default value is 1

Note: If data is empty, it returns a StatisticsError.

Technical Details

Return Value: A float value, representing the median of grouped continuous data, calculated as the 50th percentile
Python Version: 3.4

❮ Statistic Methods