Example Datasets for Python Programming and Data Analytics Fundamentals

9.8 MB of structured data files in CSV and XLSX formats accompany a book on Python programming for data analytics. The datasets are designed to illustrate concepts like data manipulation, conditional structures, loops, and visualization using libraries such as Pandas, NumPy, and Matplotlib. Its primary purpose is educational, providing practical examples for learners.

Use Cases

• Practicing data extraction and manipulation from CSV and Excel files
• Implementing conditional structures and loops for data processing tasks
• Creating data visualizations using Matplotlib with structured data
• Learning to use Pandas DataFrames and NumPy for data analysis
• Developing functions for common data analytics workflows

Strengths

• Explicitly linked to a published educational book, providing clear context
• Released under a permissive CC-BY-4.0 license for easy reuse and sharing
• Cross-platform presence on figshare suggests established curation and accessibility

Limitations

• Column names and row counts are not provided, limiting detailed assessment of structure
• The future 'last updated' date of 2026-03 19 suggests metadata may be inaccurate
• Dataset scale is modest at 9.8 MB, which may limit complexity for advanced applications

Provenance

Source

Kingsley Okoye, author of 'Python Programming - Fundamentals for Data Analytics and Real Process Management'

Collection Method

Created as example material for an educational book

Time Range

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Freshness

2026-03-19 19:57:08

Geography

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