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Simulation of a customer behavior in a supermarket with Monte Carlo Markov Chain Modeling.

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Supermarket Markov Chain Simulation

by Statistically Significant Four

MCMC Simulation A Monte Carlo Markov Chain simulation to predict the customers' behavior in a hypothetical supermarket with below layout:

Supermarket layout

Usage

$ python supermarket.py

Repo Structure

1. MCMC Simulation

  • supermarket.py -> the executable script that runs the simulation
  • proba.py -> the calculation of the transition matrix
  • visualization.py -> for an old-fashioned videogame-like visualization of the Monte Carlo Simulation
  • output -> folder with the simulation output data

2. Notebooks

  • EDA.ipynb -> exploratory data analysis on the raw data
  • theory.ipynb -> summary on Markov-Chains theory

3. Data

  • data -> The daily supermarket raw data that form the dataset of this model (in csv format)
  • data/cleaned-up -> crean data created in EDA.ipynb, and ready for calucating the transition matrix

4. Output

  • MCMC_Simulation -> The results of the simulation in .csv file after running supermarket.py
  • dungeon_supermarket map -> buited in visualization.py

Credits

This project was done in collaboration with Francesco Mari, Behzad Azarhoushang & Vlasis Tritakis.

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Simulation of a customer behavior in a supermarket with Monte Carlo Markov Chain Modeling.

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