v0.1 - Initial Release

📁 Version 0.1

📂 Current Status

• Data: The repository currently contains 2023 data for all Italian universities in .csv format. The categories mirror those used by AlmaLaurea, and every effort has been made to maintain data integrity, adding some macro-categories over the categories where necessary. The data structure is derived from AlmaLaurea's grouping by disciplinary areas and fields, with student numbers aggregated by university. Users can replicate these results using AlmaLaurea's filters directly on their website, linked in the "Important Notice" section of this README. However, the dataset still requires cleaning.
  • Work in Progress: We are implementing a column to differentiate between absolute numbers and percentages, as well as separating aggregate data from individual records. Category 5 is currently the most impacted by these upcoming updates.
  • Methodological Note: The original data collected by AlmaLaurea used "-" to indicate that no respondents were present in the sample, and "" to signify that five or fewer respondents answered in that sample, excluding it from analysis. To maintain this structure and improve usability, "-" has been replaced with the numeric value 0 and "" with -1 in the dataset. These replacements carry the same meaning as in AlmaLaurea's original methodology. Refer to the "Important Notice" section of this README for links to AlmaLaurea's official pages on data methodologies.

🔜 Future Plans

• Enhanced Usability: Clean and rearrange the dataset further to make it even more user-friendly.
• Historical Data: Include data from previous years, dividing .csv files by year.
• SQL Format: Introduce an SQL database version for improved compatibility and scalability with various HR data analysis tools.
• Dashboard Implementation: Consider adding a dashboard to this project, making the dataset more accessible to a broader audience. While not currently on the roadmap, this would align with the mission of the repository by simplifying data interpretation for more users.

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🛠️ How to Use

1. Download the Italian_University_Dataset_2023.csv file directly from the Assets below.
2. Open the file using your preferred data analysis tool, such as Tableau or Power BI.
3. Start exploring and analyzing the data to meet your needs.