This book follows a cookbook style approach that puts orthogonal and non-redundant recipes in your hands. Rather than rehashing the user manual, the explanations expose the underlying logic behind Matplotlib.
If you are an engineer or scientist who wants to create great visualizations with Python, rather than yet another...
Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.
Key Features
Get up and running with the Jupyter ecosystem and some example datasets
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...
We are visual animals. But before we can see the world in its true splendor, our brains, just like our computers, have to sort and organize raw data, and then transform that data to produce new images of the world. Beginning Python Visualization: Crafting Visual Transformation Scripts, Second Edition discusses turning many types of...
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas,...
IPython provides a rich architecture for interactive computing, and as a Python developer you can take advantage of this practical hands-on guide to make yourself an expert. Covers numerical computing, data analysis, and more.
Overview
A practical step-by-step tutorial which will help you to replace the...
We, NumPy users, live in exciting times. New NumPy-related developments seem to come
to our attention every week or maybe even daily. When this book was being written, NumPy
Foundation of Open Code for Usable Science was created. The Numba project—NumPy-aware,
dynamic Python compiler using LLVM—was announced. Also,...
Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you...
