Explore and practice the different types of plots that are instrumental in visualizing your data.

Python Data Analysis and Visualization

Visualization using Matplotlib for Python

# What is `boxplot`?

A `boxplot` is a standardized way of displaying a dataset based on a five-number summary: the minimum, the maximum, the sample median, and the first and third quartiles. In statistics, the `boxplot` is a method for graphically depicting groups of numerical data through their quartiles.

In Matplotlib, `boxplot()` is the core function to create box plot. Below are some of the important parameters of the function:

- `x`: Array or a sequence of vectors. The input data.
- `vert`: Set as True or False. The default value is True, which displays the boxes vertically.
- `labels`: Sets the labels for each dataset. 
- `notch`: Set as True or False. the default value is False. If True, the parameter will produce a notched box plot.
- `widths`: Sets the width of the box.
- `patch_artist`:  Set as True or False. the default value is False. If False, the parameter will produce boxes with the Line2D artist. Otherwise, the boxes will be drawn with Patch artists.

>**Notice**: In the images below, there are some data points outside of the boxes and their whiskers. These data points are outliers. To eliminate the effect of outliers, they need to be displayed separately. Thus, the maximum (or minimum) value of a box plot is not truly the maximum (or minimum) value. Instead, the values are calculated based on quartile.
>
>- IQR: $Q3-Q1$
>- maximum: $Q3+1.5 \times IQR$
>- minimum: $Q1-1.5 \times IQR$
>
>Data outside of these ranges are considered outliers.


In this lesson, we will learn how to display data quartiles by using a box plot.

How to Draw a Box Plot

What is boxplot?

What is `boxplot`?