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 visualizations: bar plots, scatter plots, histograms, pie charts and learning how to customize 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.
What will you learn?
•How to visualize data using a number of different plots in Python
•The architecture behind Matplotlib and different coding styles
•How to adjust the zoom and axes in a Matplotlib plot
•How to customize plots using stylesheets and axes options
•How to display error bars and confidence intervals on plots
•How to create 3D figures and geographical maps
•How to manipulate images with Matplotlib
•How to use Seaborn to reduce complexity
About the instructor:
•Postdoctoral researcher and lecturer
•PhD in Computer Science focusing on Machine Learning
•10+ years experience in data science and visualization
Visualisation in matplotlib, Seaborn, Plotly & Cufflinks, EDA on Boston Housing, Titanic, IPL, FIFA, Covid-19 Data.
4.7
★★★★★ 4.7/5
26,142 students
