Matplotlib Tutorial
Matplotlib is a Python plotting library that makes it easy for users to visualize data 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 this tool 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 graphical animations.
Before learning this tutorial, you need to know
Before starting the Matplotlib tutorial, you need basic Python knowledge. If you are not yet familiar with Python, 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, and is 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 transforms, signal processing 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