How akanksha238/logistics-analysis works
Logistics Analyzer is a Python analytics project for simulated shipment operations. Its main workflow generates shipment records, analyzes SLA, cost and satisfaction patterns, then produces charts. The repository also contains separate predictive-modeling and mode-allocation optimization scripts, plus cleaning, forecasting and clustering modules. The README describes the core pipeline; links to less-documented subsystems are omitted where sampled source does not establish their runtime wiring.
Main entry points: logistics_dataset.csv Shipment dataset · run_pipeline.py Pipeline runner · eda.py Exploratory analysis · visualize.py Chart generation
Components 13
Core pipeline
- Pipeline runner
run_pipeline.py - Shipment simulator
simulate_data.py - Shipment dataset
logistics_dataset.csv
Operational insights
- Exploratory analysis
eda.py - EDA summary
eda_summary.txt - Chart generation
visualize.py
Decision support
- Delivery prediction
logistics_analyzer.py - Model visualizations
week4_03_viz_modeling.py - Mode allocation
week4_02_optimization.py
Additional analysis
- Data cleaning
data_cleaning.py - Demand forecasting
demand_forecasting.py - Zone clustering
zone_clustering.py
Other components
- Analyst
Connections 12
- Analyst → Pipeline runner: runs
- Pipeline runner → Shipment simulator: calls
- Pipeline runner → Exploratory analysis: calls
- Pipeline runner → Chart generation: calls
- Shipment simulator → Shipment dataset: writes
- Exploratory analysis → Shipment dataset: reads
- Exploratory analysis → EDA summary: writes
- Chart generation → Shipment dataset: reads
- Chart generation → Exploratory analysis: loads data via
- Delivery prediction → Shipment dataset: reads
- Model visualizations → Delivery prediction: uses model results
- Mode allocation → Shipment dataset: reads