Python CSV Analysis & Visualization

I have a CSV file with a blend of numerical and categorical columns that I’d like you to explore with Python. Your task is to write clean, well-commented code—preferably in a single, logically organized notebook or script—that walks through data cleaning, imputes missing values using the mean or median as appropriate, and then performs a concise exploratory analysis. Once the data is ready, generate a set of bar charts, line charts, and scatter plots with Matplotlib (seaborn is fine if you prefer) so the insights stand out clearly. Please rely on Pandas for wrangling, NumPy for any numerical work, and Matplotlib for the visuals. Keep the logic straightforward and easy for another developer to follow. Deliverables • Python source code (with comments and logical sections) • Cleaned CSV dataset • Folder or embedded output containing the bar, line, and scatter plots • A short written summary (a few paragraphs or a markdown cell) explaining the cleaning decisions, the handling of missing values, and the key takeaways from the analysis I’ll consider the job complete when the script runs end-to-end on my machine, reproducing the cleaned data and charts exactly as described.