Creating charts with python

Learn how to create beautiful and insightful charts with Python — the Quick, the Pretty, and the Awesome

A comprehensive code-along guide to visualization with Python, explaining plotting with Pandas, Seaborn, and Plotly. Where we visualize, among others, that money can buy happiness.

In today’s article, we are going to look into three different ways of plotting data with Python. We will do this by utilizing data from the World Happiness Report 2019. I enriched the World Happiness Report data with information from Gapminder and Wikipedia to allow for the exploration of new relationships and visualizations.

The World Happiness Report tries to answer which factors influence happiness throughout the world.

Happiness in the report is defined as the responses to the “Cantril ladder question” asking respondents to value their lives today on a 0 to 10 scale, with the worst possible life as a 0 and the best possible life as a 10.

Throughout this article, I am going to use Life Ladder as a target variable. Whenever we talk about Life Ladder, think Happiness.

Structure of the article

T his article is intended as a code-along guide and a point of reference to revisit whenever you want to look up a specific type of plot. I will, for the sake of space, sometimes combine multiple charts into one image. But rest assured, you can find all the underlying code in this Repo or the corresponding Jupyter Notebook.

Table of contents

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How to Create Modern Charts in Python

In this article we are going to learn How to Create Modern Charts in Python, so for creating Charts in Python we are going to use PySide6 GUI library, PySide6 is Python binding for Qt framework, which allows developers to create graphical user interfaces (GUIs) for desktop applications. PySide6 is set of Python modules that provides access to Qt application framework, enabling developers to create cross platform applications that can run on Windows, Linux and macOS.

PySide6 is community driven project that is designed to be compatible with the latest version of Qt currently Qt 6. PySide6 is released under the LGPL (Lesser General Public License), which allows developers to create commercial applications without the need to release their source code.

PySide6 provides number of features, including support for many of Qt modules, such as QtCore, QtGui, QtWidgets, QtNetwork, QtSvg and many more. PySide6 also includes support for internationalization enabling developers to create applications that can be easily translated into different languages, in PySide6 there a module called QtCharts and that is used for building different types of charts.

So now first of all we need to install PySide6, you can use pip for installation of PySide6.

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