Back to List
Python
Data
Data Analysis with Python
26.12.2025
A comprehensive data science project conducted using socio-economic data (Education, Income, Unemployment, Crime Rate) from across Turkey.
Project Process and Techniques:
Data Manipulation: Cleaning raw data and preparing it for analysis using the Pandas and NumPy libraries.
Correlation Analysis: Visualizing relationships between variables (e.g., the link between education level and income) using a Heatmap.
Regression and Forecasting: Predicting average values and trends for future years (forecasting) using machine learning algorithms (regression) based on historical data.
This study uncovered hidden patterns in the data and tested their statistical significance.
Project Process and Techniques:
Data Manipulation: Cleaning raw data and preparing it for analysis using the Pandas and NumPy libraries.
Correlation Analysis: Visualizing relationships between variables (e.g., the link between education level and income) using a Heatmap.
Regression and Forecasting: Predicting average values and trends for future years (forecasting) using machine learning algorithms (regression) based on historical data.
This study uncovered hidden patterns in the data and tested their statistical significance.