How sreejabethu/sales-data-analysis-forecasting works
This is a small, single-script sales-data analysis project. The workflow starts with a user running main.py, which loads the product dataset, cleans and filters it, then produces rating-distribution and category-level visualizations. The README also describes interpreting rating and sales-related trends. The source shows the implemented cleaning and plots; the exact sales-trend analysis described in the README is not evident in the excerpt, so it is represented as a documented capability without an asserted implementation link.
Main entry points: main.py Analysis script · amazon.csv Product data
Components 10
Data preparation
- Analysis script
main.py - Product data
amazon.csv - Clean and filter
main.py
Exploratory analysis
- Rating distribution
main.py - Category metrics
main.py - Sales and ratings trends
README.md
Visualizations
- Rating histogram
main.py - Discount chart
main.py - Rating-count chart
main.py
Other components
- Analyst
Connections 8
- Analyst → Analysis script: runs
README.md - Analysis script → Product data: loads
main.py - Analysis script → Clean and filter: cleans
main.py - Clean and filter → Rating distribution: provides data
main.py - Clean and filter → Category metrics: provides data
main.py - Rating distribution → Rating histogram: plots
main.py - Category metrics → Discount chart: plots discounts
main.py - Category metrics → Rating-count chart: plots counts
main.py