Matplotlib Tutorial
Matplotlib is a plotting library for Python. It allows users to easily visualize data graphically and provides a variety of output formats.
Matplotlib can be used to draw various static, dynamic, and interactive charts.
Matplotlib is a very powerful Python plotting tool. We can use it to present a lot of data more intuitively in the form of charts.
Matplotlib can draw line plots, scatter plots, contour plots, bar charts, column charts, 3D graphics, and even graph animations, and more.
What you need to know before learning this tutorial
Before starting to learn the Matplotlib tutorial, we need to have a basic foundation in Python. If you don't know Python yet, you can read our tutorial:
Matplotlib Applications
Matplotlib is usually used together with NumPy and SciPy (Scientific Python). This combination is widely used as a replacement for MatLab, providing a powerful scientific computing environment that helps us learn data science or machine learning through Python.
SciPy is an open-source Python algorithm library and mathematical toolkit.
SciPy includes modules for optimization, linear algebra, integration, interpolation, special functions, fast Fourier transform, signal and image processing, ordinary differential equation solving, and other computations commonly used in science and engineering.
Related Links
- NumPy Official Websitehttp://www.numpy.org/
- NumPy source code:https://github.com/numpy/numpy
- SciPy Official Website:https://www.scipy.org/
- SciPy source code:https://github.com/scipy/scipy
- Matplotlib Official Website:https://matplotlib.org/
- Matplotlib source code:https://github.com/matplotlib/matplotlib
- pandas visualization official documentation:https://pandas.pydata.org/docs/user_guide/visualization.html