How can Pygal be used to generate box plots in Python?


Visualizing data is an important step since it helps understand what is going on in the data without actually looking at the complicated working underneath it and performing complicated computations.

Pygal is an open source Python package that helps in the creation of interactive plots, and SVG (Scalar Vector Graphics) images of graphs. SVG refers to dynamically generating animated graphs with the given data. These SVG images of graphs can be used and customized depending on our requirements. The SVG images are highly scalable, hence they can be downloaded in high quality format. These downloaded images can also be embedded to various projects, websites and so on.

These interactive and customized graphs can be created with ease in Pygal. Pygal helps create bar chart, histogram, line plot, and much more.

Box plot can be understood as a statistical graph that helps display numerical data with respect to quartile information. They help understand the outliers present in data.

Pygal package can be installed using the below command on Windows −

pip install Pygal

Let us understand how box plots be created using Pygal −

Example

import pygal
from pygal.style import Style
custom_style = Style(colors=('#E80080', '#404040', '#9BC850', '#E81190'))\

box_chart = pygal.Box(height=400,width = 300,style=custom_style)
box_chart.title = "Box plot"
box_chart.add("label 1", [0.4])
box_chart.add("label 2", [1.2])
box_chart.add("label 3", [1.5])
box_chart.add("label 3", [1.8])

box_chart.render_in_browser()

Output

Explanation

  • The required packages are imported into the environment.

  • The pygal.Box function is called with a few parameters.

  • This is assigned to a variable that is used to add characteristics.

  • The colors for the Box plots are defined.

  • The height and width of the graph is also defined.

  • The title and values for the box plots are defined.

  • The ‘render_in_browser’ function is called to plot the generated box plot in the browser.

Updated on: 19-Jan-2021

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