Python: Data Analytics and Visualization

Preface

The world generates data at an increasing pace. Consumers, sensors, or scientific experiments emit data points every day. In finance, business, administration and the natural or social sciences, working with data can make up a significant part of the job. Being able to efficiently work with small or large datasets has become a valuable skill. Python started as a general purpose language. Around ten years ago, in 2006, the first version of NumPy was released, which made Python a first class language for numerical computing and laid the foundation for a prospering development, which led to what we today call the PyData ecosystem: A growing set of high-performance libraries to be used in the sciences, finance, business or anywhere else you ...