Objective:
Develop a Python program that reads a dataset, performs basic data analysis, and generates a report summarizing key insights.
Requirements:
Input Handling:
Allow the user to select a CSV file to load as the dataset.
Validate the file to ensure it contains tabular data.
Data Analysis:
Implement functions to calculate the following statistics:
Mean, median, and standard deviation of numerical columns.
Count of unique values for categorical columns.
Identify and report missing values for each column.
Display the top 5 rows of the dataset.
Visualization:
Use Matplotlib or Seaborn to:
Plot a histogram for a selected numerical column.
Generate a bar chart for the frequency of values in a selected categorical column.
User Interaction:
Provide a menu for the user to choose different analysis options.
Include an option to exit the program gracefully.
Report Generation:
Save the results of the analysis and the visualizations in a PDF file using a library like FPDF or ReportLab.
Bonus:
Implement error handling for invalid inputs or file formats.
Add an option for the user to export cleaned data (without missing values) to a new CSV file.
Submission:
Submit the Python script file(s) (.py).
Include a README file explaining how to run your program.
Attach a sample dataset for testing your program.
Evaluation Criteria:
Code functionality and correctness.
Proper use of Python programming principles (functions, loops, etc.).
Code readability and comments.
Creativity in visualization and reporting.
