This application was created for a thorough statistical analysis on data gathered from my thesis titled "In-Depth Study of No-Code & Low-Code Game Creation Techniques", for the Department of Informatics in Ionian University.
You may view a short presentation of the application by using the following link: https://youtu.be/gszuoDm5GXA
Use the sidebar to select filters like type of platform, techniques and the analysis models. Visualizations will automatically update based on your selections. Hover over any graph to view exact values and data labels. Navigate through the tabs to access different types of insights.
Pandas: For efficient data wrangling and manipulation. NumPy: To support numerical operations and optimize performance. Matplotlib & Seaborn: For building intuitive, beautiful visualizations. Scikit-learn: Used in correlation calculations and analytical modeling. Streamlit: For building this fast, interactive, browser-based UI.
Data is sourced from questionnaires answered by seasoned game developers. All responses are cleaned, standardized, and structured for analysis. Key operations include string normalization, handling nulls, and transforming categorical values. Aggregation and correlation calculations help expose meaningful patterns.
Correlation Heatmaps: Reveal relationships (positive/negative) between tools, communication, and development success. Bar Charts & Histograms: Show frequency of usage and preferences across platforms or tools. Categorical Visuals: Compare data grouped by experience level or development environment. Interactive Filters: Allow real-time comparison of multiple variables.
Emphasis on correlation over causation ensures a data-driven yet cautious interpretation. Insights are experience-weighted, as all participants are active or former professionals. Visuals are tailored to surface practical conclusions about what works and what doesn't.
Developers: Learn which workflows and environments lead to efficient results. Researchers: Explore a validated dataset to fuel further study. Managers/Teams: Make informed decisions on technology stacks and team structures.
This app is not just about data — it's about discovering patterns, relationships, and best practices in game development, through a scientific and visually engaging lens.
Feel free to explore, analyze, and draw your own conclusions from the wealth of experience encapsulated in this tool.
The data from the questionnaire are limited to a small amount, hence why we created the synthetic data sheet. Ideally, we would like to gather more types of data at a bigger amount for a better understanding of the real world dynamics between them, such as team size, experience in years, developer frequency or anything else that could affect the time, cost and challenge of a game's development and analyze again for more accurate results.