Project Description
The culmination of the Python Path! Build an end-to-end data analytics tool that ingests raw dataset files, performs statistical transformations, applies custom filter rules, computes descriptive statistics, and generates multi-format markdown & HTML analytical reports.
Learning Objectives
- Architect a modular object-oriented DataProcessor and ReportGenerator class system.
- Implement statistical algorithms without external heavy dependencies (mean, median, variance, std dev).
- Build dynamic dataset filtering pipeline using higher-order functions.
- Export formatted HTML/Markdown analytical dashboards containing statistical highlights.
Technical Requirements & Specifications
### Capstone Overview
This final portfolio capstone brings together everything you have learned in the Python Mastery Path. You will engineer a standalone Data Analytics & Report Engine.
### Technical Architecture
1. **Dataset Ingestor**: Load structured tabular records from CSV or JSON.
2. **Data Sanitizer**: Handle missing values (`None`, `""`), convert data types, and normalize text fields.
3. **Statistical Engine**:
- Metrics: Count, Sum, Mean, Median, Min, Max, Variance, Standard Deviation.
- Grouping: Calculate metrics grouped by categorical columns (e.g. Sales by Region).
4. **Report Generator**:
- Export standalone `report.md` and `report.html` with styling.
