Data Visualization With Matplotlib 3.x and Python
Data Visualization With Matplotlib 3.x and Python
Getting started with data science visualization using Matplotlib, Seaborn, Bokeh and Cartopy in 2020
This course is about creating graphs using Matplotlib and Python. With over 50 lectures we take a deep dive into the Matplotlib API and show you how to create impressive figures. We go through a number of different visualisations: barplots, scatter plots, histograms, pie charts and learning how to customise them all as well. This course will teach you everything that you need to know to get started creating impressive visualizations in Python. We will also look at some additional libraries such as Seaborn, Bokeh and Cartopy that can be used to create impressive interactive and geographical data plots.
The course has been specially designed for students who want to learn how to visually display python data. On completion of the course, you will not only have gained a deep insight into the range of plots that you can create using Matplotlib, you will also be able to customize the plots to make them your own and ensure that they are visually appealing as well. You will also be able to draw attention to interesting parts of your figure using text and arrow annotations on the plot.
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What you’ll learn
- How to draw graphs in Python with Matplotlib 3.x
- Visualize geographical data on maps
- Customize their Matplolib plots using different colours, fonts and lines
- Create both 2D and 3D data using a range of graphs
- How to create Scatter plots, Density plots, Histograms, Boxplots and much more
- Create interactive graphs that can be deployed on webpages using Bokeh
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