Data Visualization with Python and Matplotlib
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More and more people are realising the vast benefits and uses of analysing big data. However, the majority of people lack the skills and the time needed to understand this data in its original form. That is where data visualisation comes in, creating 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.
Python Data Visualisation made Easy
With over 58 lectures and 6 hours of 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 will 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 will then move onto each of the most popular types of graph, covering how to import data from both a CSV and NumPy. You will then move on to more advanced features like customised spines, styles, annotations, averages and indicators, geographical plotting with Basemap and advanced wireframes.
This course has been specially designed for students who want to learn a variety of ways to visually display python data. On completion of this course, you will not only have gained a deep understanding of the options available for visualising data, but you will have the know-how to create well presented, visually appealing graphs too.
Basic understanding of Python.
Students should be comfortable with the basics of the Python 3 programming language
Python 3 should be already installed, and students should already know how open IDLE or their own favorite editor to write programs in.
- Students seeking to learn a variety of ways to visually display data
- Students who seek to gain a deep understanding of options for visualizing data
Self-Paced Learning Outline
- Section 1: Course Introduction
- Section 2: Different types of basic Matplotlib charts
- Section 3: Basic Customization Options
- Section 4: Advanced Customization Option
- Section 5: Geographical Plotting with Basemap
- Section 6: 3D graphing
- Section 7: Course Conclusion
|Learning Style||Self-Paced Learning|
|Course Duration||7 Hours|