Over the weekend, I crossed two big learning milestones🥳🎉
✅Completed Web Scraping in Python
✅Completed Introduction to Statistics in Python
Web scraping taught me how to actually collect data from the web, building spiders, navigating pages, extracting structured information, and understanding how raw data is born.
Statistics helped me make sense of that data, from probability distributions to correlation, causation vs spurious relationships, design of experiments and how data behaves in the real world.
To start the week, I moved into:
Introduction to Data Visualization with Matplotlib
Intermediate Importing Data in Python
Now it's about turning data into clear visuals and learning how to bring data in from different sources, files, formats, and real world datasets.
Starting tomorrow, I'll also be adding: Introduction to Importing Data in Python, to complete the pipeline.
This phase feels exciting because everything is finally connecting: Get the data, clean it, analyze it, visualize it and explain it.
Slowly but surely, I'm building the full data workflow, not just learning concepts, but practicing how they fit together.
Onward to more charts, more datasets, and deeper questions
-SP
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