Learn to use matplotlib’s gallery to create beautiful plots within Jupyter notebooks using matplotlib and NumPy in this video tutorial by Charles Kelly. These are explained in the context of computer science and data science to technologists and students
- [Teacher] The Beautiful Plots and the Gallery file in…your Exercises file folder is pre-populated with import…statements and source code for four complicated plots.…Before you begin using this notebook,…go to the cell that contains the import statements…and execute this cell by pressing Shift+Enter.…It can be both complicated and time-consuming…to create beautiful plots.…One way to reduce both the time and the complexity…needed to create your own plots…is to review matplotlib's gallery and find plots…that are similar to those that you want to create.…
The gallery is a large collection of well-designed plots…that you can use as starting points for your own plots.…The gallery is organized into categories,…such as line bar charts and markers,…shapes and collections, statistical plots, and more.…Don't worry, this is not cheating.…Most of the authors will be happy…if you replicate their work,…especially if you provide…a citation to their work.…This is definitely a situation where…you want to cut and paste source code.…
- Using Jupyter Notebook
- Creating NumPy arrays from Python structures
- Slicing arrays
- Using Boolean masking and broadcasting techniques
- Plotting in Jupyter notebooks
- Joining and splitting arrays
- Rearranging array elements
- Creating universal functions
- Finding patterns
- Building magic squares and magic cubes with NumPy and Python
Skill Level Intermediate
2. Create NumPy Arrays
3. Index, Slice, and Iterate
4. Plots: Matplotlib and Pyplot
5. Manipulate Arrays
6. Short Examples
7. Extended Examples
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