README.md

ECS272 Final Project

• By Shaokang Xie, Jiazhi Sun

• This folder contains scripts for downloading and processing the Steam games dataset.

Instructions

0. Install the required python libraries:

python -m pip install -r data_processing/requirements.txt

1. Download the raw dataset (saves to data_processing/raw/):

python data_processing/download_py.py

2. Preprocess the raw CSV into cleaned outputs:

python data_processing/preprocess.py \
  --input data_processing/raw/games.csv \
  --json_reviews data_processing/raw/games.json \
  --out data_processing/steam_project_ready.csv \
  --agg_out /tmp/steam_project_agg.csv \
  --sample_out /tmp/steam_project_sample.csv

3. Generate a slimmed JSON for the frontend:

python data_processing/make_slim_json.py

4. Plot the analysis figures

python data_processing/steam_analysis_slide_figure.py

Output files

• data_processing/raw/games.csv and data_processing/raw/games.json (raw dataset from kaggle)
• data_processing/steam_project_ready.csv (cleaned dataset for slide figures)
• frontend/public/games_slim.json (frontend-ready slim JSON)
• data_processing/images/genre_value_bar.png (analysis figure used in slides)
• data_processing/images/peak_ccu_by_price_band.png (analysis figure used in slides)
• data_processing/images/price_trend_composite.png (analysis figure used in slides)
• data_processing/images/price_vs_popularity.png (analysis figure used in slides)
• data_processing/images/spiral_plot.png (analysis figure used in slides)

Run the React Frontend

1. cd frontend
2. npm install
3. npm start