Matplotlib: Data Visualization with Python & Matplotlib

$99.99 $49.99

This Data Visualization with Python and Matplotlib course has been specially designed for students who want to learn a variety of ways to visually display Python data. Gain a deep understanding of the options available for visualizing data, and get the know-how to create well presented, visually appealing graphs. Get ready to create advanced graphs with the Matplotlib add-on!

Length: 7 hrs

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Description

More and more people are realizing the vast benefits and uses of analyzing big data. However, the majority of people lack the skills and the time needed to understand this data in its original form. That’s where this Data Visualization with Python and Matplotlib training course comes in! Learn how data visualization allows you to create easy to read, simple to understand graphs, charts and other visual representations of data. Python 3 and Matplotlib are the most easily accessible and efficient to use programs to do just this.

Learn Big Data Python

  • Visualize multiple forms of 2D and 3D graphs; line graphs, scatter plots, bar charts, etc.
  • Load and organize data from various sources for visualization
  • Create and customize live graphs
  • Add finesse and style to make your graphs visually appealing

Sample clip

 

 
Python Data Visualization Made Easy

With nearly 7 hours of video content, this course covers almost every major chart that Matplotlib is capable of providing. Intended for students who already have a basic understanding of Python, you’ll take a step-by-step approach to create line graphs, scatter plots, stack plots, pie charts, bar charts, 3D lines, 3D wire frames, 3D bar charts, 3D scatter plots, geographic maps, live updating graphs, and virtually anything else you can think of!

Starting with basic functions like labels, titles, window buttons and legends, you’ll then move onto each of the most popular types of graph, covering how to import data from both a CSV and NumPy. You’ll then move on to more advanced features like customized spines, styles, annotations, averages and indicators, geographical plotting with Basemap and advanced wireframes.

Tools Used:

Python 3: Python is a general purpose programming language which a focus on readability and concise code, making it a great language for new coders to learn. Learning Python gives a solid foundation for learning more advanced coding languages, and allows for a wide variety of applications.

Matplotlib: Matplotlib is a plotting library that works with the Python programming language and its numerical mathematics extension ‘NumPy’. It allows the user to embed plots into applications using various general purpose toolkits (essentially, it’s what turns the data into the graph).

IDLE: IDLE is an Integrated Development Environment for Python; i.e where you turn the data into the graph. Although you can use any other IDE to do so, we recommend the use of IDLE for this particular course.

CHAPTER 1: COURSE INTRODUCTION
Introduction
Getting Matplotlib And Setting Up
 
CHAPTER 2: DIFFERENT TYPES OF BASIC MATPLOTLIB CHARTS
Section Introduction
Basic matplotlib graph
Labels, titles and window buttons
Legends
Bar Charts
Histograms
Scatter Plots
Stack Plots
Pie Chart
Loading data from a CSV
Loading data with NumPy
Section Conclusion
 
CHAPTER 3: BASIC CUSTOMIZATION OPTIONS
Section Introduction
Source for our Data
Parsing stock prices from the internet
Plotting basic stock data
Modifying labels and adding a grid
Converting from unix time and adjusting subplots
Customizing ticks
Fills and Alpha
Add, remove, and customize spines
Candlestick OHLC charts
Styles with Matplotlib
Creating our own Style
Live Graphs
Adding and placing text
Annotating a specific plot
Dynamic annotation of last price
Section Conclusion
 
CHAPTER 4: ADVANCED CUSTOMIZATION OPTIONS
Section Introduction
Basic suplot additions
Subplot2grid 
Incorporating changes to candlestick graph
Creating moving averages with our data
Adding a High minus Low indicator to graph
Customizing the dates that show
Label and Tick customizations
Share X axis
Multi Y axis
Customizing Legends
Section Conclusion
 
CHAPTER 5: GEOGRAPHICAL PLOTTING WITH BASEMAP
Section Introduction
Downloading and installing Basemap
Basic basemap example
Customizing the projection
More customization, like colors, fills, and forms of boundaries
Plotting Coordinates
Connecting Coordinates
Section Conclusion
 
CHAPTER 6: 3D GRAPHING
Section Introduction
Basic 3D graph example using wire_frame
3D scatter plots
3D Bar Charts
More advanced Wireframe example
Section Conclusion
 
CHAPTER 7: COURSE CONCLUSION
Conclusion

Harrison Kinsley is a husband, runner, friend of all dogs, programmer, teacher, and entrepreneur.

Harrison utilized his love for learning and building with technology to start multiple businesses, all of which leverage the Python programming language. Python programming is a major part of his life and work. He believes programming is a super power, and the social impact of making this education easily accessible to anyone is one of the most important things he can do with his life.

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