This project focuses on reinforcing key Python visualization skills by utilizing the Matplotlib and pyplot libraries. The primary objective is to practice creating various types of plots and charts to present information effectively. By working through the tasks provided, students will gain hands-on experience with web-enabled Jupyter notebooks and lay important foundations for processing language and mining the web.

1. Frequency Distribution of Characters: Create a bar plot to display the frequency distribution of characters in a given text.
2. Visualizing Random Data: Generate random numbers and visualize them using scatter and plot on separate axes.
3. Customizing Scatter and Plot Styles: Repeat the previous task but customize the style and color of both the scatter and the plot.
4. Sorting Algorithm Time Analysis: Plot the time it takes to execute a sorting algorithm on lists of different sizes, showcasing insertion sort and merge sort times on the same axes with a legend.

• Use only the Matplotlib and pyplot libraries.
• Write code in Jupyter Notebook cells, ensuring each cell is executed and displays output.
• Commit and push all changes to the assignment repository.

This repository follows a structured layout to organize the project files effectively:

• Notebooks: Contains Jupyter notebooks for each task, named accordingly.
• HTML: Contains exported HTML files of the notebooks.
• README.md: Provides an overview of the project, instructions, and requirements.
• .gitignore: Specifies files and directories to be ignored by Git.

The questions in this assignment can be found in the provided pyplot.ipynb notebook.