My Python learning journey through hands-on projects, progressing from Python fundamentals to data analysis and visualization.
A simple Python program that calculates a student's average grade and assigns a letter grade.
Concepts practiced:
- Variables and user input
- Arithmetic operations
- Conditional statements
- Comparison operators
- Type conversion
A data analysis project for exploring and summarizing personal expense data using Python.
Concepts practiced:
- Pandas DataFrames
- Data cleaning and manipulation
- Grouping and aggregation
- Basic statistical analysis
- Data visualization with Matplotlib
A climate data analysis project exploring long-term changes in Turkey's annual average surface temperature from 1940 to 2025.
Concepts practiced:
- Real-world data exploration
- Pandas filtering
- Descriptive statistics
- Time-series analysis
- 10-year moving averages
- Linear trend estimation with NumPy
- Data visualization with Matplotlib
Key finding:
The analysis estimates an overall linear temperature trend of approximately +0.28 °C per decade for Turkey over the 1940–2025 period.
An exploratory data analysis project using simulated high-energy physics collision data from the HIGGS dataset.
What I practiced:
- Descriptive statistics
- Signal vs background comparison
- Grouping and aggregation with Pandas
- Pearson correlation analysis
- Scientific data visualization with Matplotlib
Key finding: Among the selected features, missing_energy and m_wwbb showed the strongest positive linear relationship (r ≈ 0.313).
- Python
- Pandas
- NumPy
- Matplotlib
- Jupyter Notebook
- Git & GitHub
This repository documents my progression from Python fundamentals toward data analysis, scientific computing, and real-world problem solving.
Each project focuses on applying newly learned concepts through practical implementation rather than isolated exercises.
python-learning/
│
├── grade_calculator.py
│
├── 02-expense-analyzer/
│ ├── expense_analyzer.py
│ ├── expenses.csv
│ └── README.md
│
├── 03-climate-data-explorer/
│ ├── climate_analysis.py
│ ├── data/
│ ├── visualizations/
│ └── README.md
│
├── 04-particle-collision-eda/
│ ├── analysis.py
│ ├── higgs_train_10k.csv
│ ├── correlation_plot.png
│ ├── requirements.txt
│ └── README.md
│
└── README.md