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Darkstore Analysis - Geospatial

Overview

Darkstore Analysis - Geospatial is a project focused on the geospatial study of dark stores (warehouses used for rapid e-commerce fulfillment). Using geographic data, machine learning, and visualization techniques, this project helps businesses optimize their dark store locations for better efficiency and market reach.

Features

  • Geospatial Visualization: Interactive maps displaying dark store locations.
  • Demand Analysis: Identifying high-demand regions using customer order data.
  • Site Selection Optimization: Using clustering and geospatial algorithms to suggest new locations.
  • Competitor Mapping: Understanding market presence and competition.

Technologies Used

  • Python: Data processing, machine learning
  • Geopandas & Shapely: Spatial data manipulation
  • Folium & Plotly: Geospatial visualization
  • Scikit-learn: Clustering and demand forecasting
  • QGIS: Additional spatial analysis

About

Darkstore Analysis - Geospatial** is a project focused on the geospatial study of dark stores (warehouses used for rapid e-commerce fulfillment). Using geographic data, machine learning, and visualization techniques, this project helps businesses optimize their dark store locations for better efficiency and market reach.

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