
Install and configure your working environment for Matplotlib. Ensure Python is present, install Matplotlib and Jupyter Notebook, then import matplotlib.pyplot as plt and plot a simple graph.
Learn to add a title, x and y axis labels, and a legend to a Matplotlib plot using an OOP approach, with linear, quadratic, and cubic curves.
Adjust plot() parameters to customize matplotlib visuals with color, line style, and alpha. Use color names or hex codes, control linewidth, and choose solid or dotted lines.
Learn to create and customize scatter plots in Matplotlib by plotting data with subplots, adjusting marker size and color, and adding legends for multiple data series.
Learn to add annotations in a matplotlib plot by marking a local max with text and an arrow, customize the arrow props, and adjust axis limits.
Create and customize bar diagrams in Matplotlib, including vertical and horizontal bars, groupings by category and gender, labeling, error bars, and on-bar value annotations.
Explore basic image manipulation in Matplotlib by loading images, inspecting color values (rgb) and alpha, applying color maps and color bars, and annotating with rectangles using patches.
This is a course on the matplotlib library of python which is one of the most popular tools for data visualization in python . The course aims to teach all the necessary tools required to start working with the matplotlib library. It starts off with the installation and configuring of the environment and basic plotting. We then move on to study the anatomy of the matplotlib figure. We learn about the building blocks of a matplotlib figure. We will learn to add and manipulate titles, x and y labels, ticks, markers, annotations, various styling to the layout, styling of the plots inside the axes and many more. We will be using numpy for creating our input datas for visualization. We will also learn to configure the reconfiguration file to add custom layout and styling to our figure and axes. The course also aims to teach various plots, and diagrams such as line plots, scatter plots, bar diagrams, pie charts, histograms and so on. We will also learn to plot from the external files with the help of the pandas library and as well as save our plotted figure. It also touches on the topics of image manipulation and 3d plotting with matplotlib.