I have a dataset that compares several life-cycle-assessment (LCA) categories, and I want the story behind those numbers to pop. Using Python’s Matplotlib (plus pandas or seaborn if they speed things up), I need a small suite of clear, publication-ready graphics that highlight differences among the categories. The core goal is category comparison, so I’m after a mix of chart styles rather than a single plot: a radar chart to show the full LCA profile at a glance, a pie chart to spotlight contribution shares, and at least one classic bar/stacked-bar view for straightforward side-by-side reading. Consistent color palettes and legible annotations are important because the figures will end up in a report. Deliverables • A well-commented .py script that ingests my CSV/XLSX data and generates the radar, pie, and bar-style charts. • High-resolution PNG (or vector PDF) exports of each figure. • A brief README explaining any required libraries and how to swap in new data. Acceptance criteria Charts load without errors, labels are readable at 100 % zoom, and the visuals clearly distinguish each LCA category so trends and outliers are instantly recognizable.