I built a full automated analytics workflow for a Delivery Logistics dataset using Python. What I...I built a full automated analytics workflow for a Delivery Logistics dataset using Python. What I...
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Nte Samuel
• Dec 1
I built a full automated analytics workflow for a Delivery Logistics dataset using Python.
What I did:
Downloaded the dataset directly via the Kaggle API
Cleaned and prepared key features (distance, delivery times, cost, ratings, partner performance)
Ran a full Exploratory Data Analysis on courier performance, delivery speed, regional patterns, and weather impacts
Generated automated visualizations on: • On-time vs delayed deliveries • Delivery cost drivers • Vehicle performance differences • Distance vs Delivery Time trends • Partner-level efficiency
Automated the workflow so the script update
Why it matters (Transportation/Logistics Insight): This workflow helps operations teams quickly spot delivery bottlenecks, identify high-performing regions/partners, forecast delays, and optimize cost per km — all without manual reporting
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