English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 13m | 264 MB
Master the core functionality of Matplotlib 3 and become an expert in advanced data visualization
You already know the basics of Data Visualization with Matplotlib but this is not enough. You want to be able to create advanced-level Data Visualizations that showcase insights from your datasets.
This course will help you delve into the latest version of Matplotlib, 3, in a step-by-step and engaging manner. Through this course, you will master advanced Matplotlib concepts and will be able to tackle any Data Visualization project with ease and with increasing complexity.
By the end of the course, you will have honed your expertise and mastered data visualization using the full potential of Matplotlib 3.
This course adopts a practical and hands-on approach, with no theory. Since you already know the basics of Data Visualization in Python with Matplotlib, we skip setup issues and go straight to practical ways to visualize data using specific Matplotlib functionalities. All examples use real-world datasets from lots of different domains.
What You Will Learn
- Visualize data using PyPlot, plot functions, create complex subplots, and troubleshoot issues.
- Build interactive plots with Matplotlib 3. Understand and implement event handling and GUI widgets and learn how to turn interactive plots into videos.
- Customize your plots.
- Understand how Matplotlib color customization work, work with layouts, tweak configuration files, and customize style sheets
- Draw on plots, ranging from inserting lines, adding text, and drawing different shapes and annotations.
- Draw special-purpose advanced plots such as non-Cartesian plots, vector fields, violin graphs, and more.
- Learn to visualize both ordinal and tabular data.
- Draw 3D and geospatial plots with Matplotlib 3.
- Create beautiful Data Visualizations with Seaborn
Mastering the Matplotlib Pyplot
1 The Course Overview
2 Creating Plots Using the Plot Function
3 Creating Subplots
4 Subplot Parameters
5 Learn How Pyplot Works
6 Troubleshooting Pyplot
Plot Interactivity with Matplotlib
7 Creating Interactive Plots
8 Event Handling with Plot Callbacks
9 GUI Neutral Widgets
10 Converting Interactive Plots into Videos
11 Customizing Pylab in Style
12 Color Deep Dive
13 Working on Non-Trivial Layouts
14 The Matplotlib Configuration Files
Drawing on Plots
16 Putting Lines in Place
17 Adding Text to Your Plots
18 Playing with Polygons and Shapes
19 Versatile Annotating
Special Purpose Plot
20 Non-Cartesian Plots
21 Plotting Vector Fields
22 Statistics with Boxes and Violins
23 Visualizing Ordinal and Tabular Data
D and Geospatial Plotting
24 Plotting with 3D Axes
25 Looking at Various 3D Plot Types
26 The Basemap Methods
27 Plotting on Map Projections
28 Adding Geography
Data Visualization with Seaborn
29 Visualizing Categorical Data
30 Plotting Distributions
31 Visualizing Data on Multi-Plot Grids
32 Customizing Plots