Matplotlib Tutorial
Matplotlib is a plotting library for Python that allows users to easily visualize data and provides a variety of output formats.
Matplotlib can be used to create various static, dynamic, and interactive charts.
Matplotlib is a powerful Python drawing tool, enabling us to present a lot of data in a more intuitive form through charts.
Matplotlib can draw line plots, scatter plots, contour plots, bar charts, histograms, 3D graphics, and even graphical animations.
What You Need to Know Before Learning This Tutorial
Before starting the Matplotlib tutorial, you should have a basic understanding of Python. If you are not familiar with Python, you can read our tutorials:
Applications of Matplotlib
Matplotlib is commonly used with NumPy and SciPy (Scientific Python). This combination is widely used as a replacement for MatLab and is a powerful scientific computing environment, aiding us in learning 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 solvers, and other commonly used calculations in science and engineering.
Related Links
- NumPy Official Website: http://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