SQL + Python: Chicago Database Analysis (SQLite)

This repository demonstrates SQL + Python skills by:

• loading 3 real-world CSV datasets into a SQLite database
• running analysis queries (filters, joins, grouping, ordering)
• pulling results into pandas for inspection

Project structure

sql-python-chicago-crime-analysis/
  README.md
  requirements.txt
  .gitignore
  data/
    ChicagoCensusData.csv
    ChicagoCrimeData.csv
    ChicagoPublicSchools.csv
  scripts/
    build_sqlite_db.py
  sql/
    queries.sql
  notebooks/
    01_sql_python_chicago.ipynb
  outputs/
    (generated locally; ignored by git)

Key skills demonstrated

• SQLite database creation from CSVs (pandas.to_sql)
• SQL: JOIN, GROUP BY, ORDER BY, LIMIT, LIKE, COUNT, AVG, CAST
• Handling messy / non-standard column names (e.g., "Elementary, Middle, or High School")

Quick start (local)

1. Create a virtual environment (optional) and install dependencies:

   pip install -r requirements.txt

2. Build the database:

   python scripts/build_sqlite_db.py

   This creates outputs/Final.db.

3. Run the notebook:

   jupyter notebook

   Open: notebooks/01_sql_python_chicago.ipynb

Notes for GitHub

• outputs/ and *.db are ignored so your repo stays clean.
• The CSVs in data/ are small enough to commit; if you ever add larger datasets, keep them out of git and document how to obtain them.