Data cleaning and EDA are indispensable components of data science. Before we begin analyzing our data, it is important to understand some basic properties of what we have input. The dataset we are using comprises standardized images with regular shapes and normalized pixel values. The features are simple, thin lines. Our goal is straightforward as well, to recognize digits from images. Yet, in many cases of real-world practice, the problems can be more complicated; the data we collect is going to be raw and often much more heterogeneous. Before tackling the problem, it is usually worth the time to sample a small amount of input data for inspection. Imagine training a model to recognize Ramen just to get you drooling ;). You will probably take a look at some images to decide what features make a good input sample to exemplify the presence of the bowl. Besides the initial preparatory phase, during model building taking out some of the mislabeled...
Matplotlib for Python Developers - Second Edition
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Matplotlib for Python Developers - Second Edition
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Overview of this book
Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library.
Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples.
By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Free Chapter
Introduction to Matplotlib
Getting Started with Matplotlib
Decorating Graphs with Plot Styles and Types
Advanced Matplotlib
Embedding Matplotlib in GTK+3
Embedding Matplotlib in Qt 5
Embedding Matplotlib in wxWidgets Using wxPython
Integrating Matplotlib with Web Applications
Matplotlib in the Real World
Integrating Data Visualization into the Workflow
Index
Customer Reviews