Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

Overview of this book

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.
Table of Contents (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Exporting data to JSON, CSV, and Excel


While as producers of data visualization, we are mostly using other people's data, importing and reading data are our major activities. We do need to write or export data that we produced or processed, whether it is for our or others' current or future use.

We will demonstrate how to use the previously mentioned Python modules to import, export, and write data to various formats such as JSON, CSV, and XLSX.

For demonstration purposes, we are using the pregenerated dataset from the Importing data from fixed-width data files recipe.

Getting ready

For the Excel writing part, we will need to install the xlwt module (inside our virtual environment) by executing the following command:

$ pip install xlwt

How to do it...

We will present one code sample that contains all the formats that we want to demonstrate: CSV, JSON, and XLSX. The main part of the program accepts the input and calls appropriate functions to transform data. We will walk through separate sections...