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Data Mining Project - SNCB Cool Train

Overview

This repo is our project "SNCB Cool Train" in the course "Data Mining" at Université Libre de Bruxelles (ULB).

Built With

Setup

  1. Here we only use a mini file ar41_for_ulb_mini.csv. You can get the full raw data file ar41_for_ulb.csv (1.9GB) provided by the lecturer.
  2. Go to https://account.mapbox.com/access-tokens/ and create an access token, then put it at mapbox_access_token= in the file app.py.

Usage

  1. Clone the repo
    git clone https://github.com/hieunm44/dm-sncb-cool-train.git
    cd sdm-sncb-cool-train
  2. Install necessary packages
    pip install -r requirements.txt
  3. Get weather data from https://open-meteo.com/ through API calls then integrate to raw data.
    python3 data_integration.py
    Then two files weather_data.csv and merged_data will be created in the folder data.
  4. Check the file preprocess_data.ipynb for data preprocessing and model training. Several data files and model files will be created.
  5. Run the visualization app. Here we only use the file sample_data.csv (a portion of full data), so that the application can run smoothly.
    python3 app.py

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Detecting anomaly from SNCB Train data and dashboard visualization.

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