Explore the world of amazing and efficient graphs with Matplotlib 2.x to make your data more presentable and informative
About This Video
- Create and customize appealing and live graphs, by adding style, colors, and fonts.
- Learn to represent data in the right way to engage readers
- Explore the power of Python packages to design excellent graphs
- A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits.
- Create timestamp data visualizations on 2D and 3D graphs in the form of plots, histogram, bar charts, scatter plots, and more.
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.By the end of this video, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This video will help you prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Table of Contents
- Chapter 1 : Hello Plotting World!
- Chapter 2 : Figure Aesthetics
- Chapter 3 : Figure Layout and Annotations
Chapter 4 : Visualizing Online Data
- Typical API Data Formats 00:03:17
- Introducing Pandas 00:07:08
- Visualizing the Trend of Data 00:04:41
- Visualizing Univariate Distribution 00:06:45
- Visualizing a Bivariate Distribution 00:07:05
- Visualizing Categorical Data 00:06:02
- Controlling SeabornFigure Aesthetics 00:06:18
- More About Colors 00:04:37
- Chapter 5 : Visualizing Multivariate Data
- Chapter 6 : Adding Interactivity and Animating Plots
- Chapter 7 : A Practical Guide to Scientific Plotting
- Chapter 8 : Exploratory Data Analysis Analytics and Infographics
- Title: Python Data Visualization with Matplotlib 2.x
- Release date: October 2017
- Publisher(s): Packt Publishing
- ISBN: 9781788839754