Python Data Fundamentals

A collection of reusable Python utilities for data loading, exploratory data analysis (EDA), and data cleaning — built as part of the Google Advanced Data Analytics Professional Certificate.

Project Structure

python-data-fundamentals/
├── src/
│   ├── data_loader.py      # CSV loading, validation, dataset description
│   ├── eda_toolkit.py       # Summary stats, distributions, correlations, outlier detection
│   └── data_cleaning.py     # Deduplication, missing values, type conversion, outlier clipping
├── notebooks/
│   ├── 01_python_basics_demo.ipynb
│   └── 02_pandas_eda_walkthrough.ipynb
├── data/
│   └── c2_epa_air_quality.csv
├── requirements.txt
└── README.md

Key Features

Module	Highlights
data_loader	load_csv() with auto-preview, validate_dataframe() with missing-data thresholds, describe_dataset()
eda_toolkit	Extended summary_statistics() (IQR, skew, kurtosis), distribution/boxplot/correlation plots, IQR-based outlier detection
data_cleaning	Duplicate removal, 5 missing-value strategies (drop/mean/median/mode/ffill), dtype conversion, quantile-based outlier clipping

Dataset

EPA Air Quality Index (AQI) — 1,725 observations of air quality measurements across U.S. states and counties.

Column	Description
state_name	U.S. state
county_name	County within the state
aqi	Air Quality Index value

Getting Started

# Clone the repository
git clone https://github.com/asenabeshiktepeli/python-data-fundamentals.git
cd python-data-fundamentals

# Install dependencies
pip install -r requirements.txt

# Quick usage
python -c "
from src.data_loader import load_csv, validate_dataframe
df = load_csv('data/c2_epa_air_quality.csv')
print(validate_dataframe(df))
"

Notebooks

1. Python Basics Demo — Variables, control flow, functions, and list comprehensions demonstrated with real data
2. Pandas EDA Walkthrough — End-to-end exploratory analysis of the EPA Air Quality dataset using the src/ utilities

Technologies

• Python 3.10+
• pandas, NumPy
• matplotlib, seaborn

License

This project is for educational and portfolio purposes. The EPA Air Quality dataset is publicly available from the U.S. Environmental Protection Agency.