Day 30 of improving my Data Science skills

Source: Dev.to

What I focused on today

Today felt like one of those quiet but powerful learning days—the kind where things don’t just work, but I understand why and how they work.

I spent the day deep in importing data in Python. It started with files—no fancy models, no dashboards—just learning how data enters Python.

Key things I learned

• Read entire text files safely using with open().
• Import Excel files with multiple sheets using pd.read_excel().
• Passing sheet_name=None returns every sheet as a dictionary.
  “Oh… Python just handed me every sheet as a dictionary.” That small win felt big.

Suddenly, Excel wasn’t just a file anymore. It became a structured collection of DataFrames, each accessible by name—simple, clean, yet powerful.

Visualizing the data

Data isn’t meant to stay silent. Using Matplotlib, I began turning numbers into pictures. Visual patterns explained more than raw values ever could.

This sparked curiosity:

• You start asking better questions.
• You notice patterns you didn’t expect.
• You stop guessing and start observing.

Takeaways

• Data doesn’t magically appear; it’s imported intentionally.
• Files aren’t scary—they’re just formats waiting to be read.
• Visualization isn’t decoration; it’s understanding.

Plans for tomorrow

• Explore more data sources.
• Create additional visualizations.
• Tackle exercises that stretch my understanding beyond the basics.

If today was about opening the door to data, tomorrow is about walking confidently through it.

And I’m just getting started.

— SP