Matplotlib is a Multiplatform visualization library for data that is built on NumPy Arrays. This Library is designed to work with the broader SciPy stack, which includes different modules of Python used for machine learning and data science.
Matplotlib is the default(sort of) Python Data Visualization Package and is being used extensively in the market for creating plots, charts, graphs for datasets for better data analysis and visualization.
In this tutorial of Matplotlib, we will start with the basics of Matplotlib and will cover all the different types of Plots available in Matplotlib.
Matplotlib Basics
General Concepts in Matplotlib
Matplotlib in Jupyter Notebook
Matplotlib Object Oriented Interface
Matplotlib Multiplots with subplots() Function
Matplotlib subplots() Function
Matplotlib subplot2grid() function
Formatting the Axes in Matplotlib
Setting Limits for Axis in Matplotlib
Setting Ticks and Tick Labels in Matplotlib
MATPLOTLIB PLOTS
Matplotlib Bar Plot – bar() Function
Matplotlib Histrograms – hist() Function
Matplotlib Pie Chart – pie() Function
Matplotlib Scatter Plot – scatter() Function
Matplotlib Contour Plot – contour() Function
Matplotlib Quiver Plot – quiver() Function
Matplotlib Box Plot – boxplot() Function
Matplotlib Violin Plot – violinplot() Function
MATPLOTLIB 3D
Matplotlib 3D Plotting – Line and Scatter Plot
Matplotlib 3D Contour Plot – contour3d() Function
Matplotlib 3D WireFrame Plot – plot_wireframe() Function
Matplotlib 3D Surface Plot – plot_surface() Function
Miscellaneous
Working with Text in Matplotlib
Mathematical expressions in matplotlib
Working with Images in Matplotlib
