Analyze Data Like A Python Pro

Author(s): Katlego Thobye

Originally published on Towards AI.

Create a Cheat Sheet and Stop Googling the Docs

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I remember drowning in online searches for the first few months of my data science journey. Every task, no matter how small, required an endless cycle of searching Stack Overflow, poring over Pandas documentation, and frantically flipping between Matplotlib examples. My code was a Frankensteinian monster of copy-pasted snippets, barely held together with duct tape and hope. I spent more time debugging syntax errors and wrestling with data types than ‘analyzing’ anything. From struggling to determine the difference between df.loc() and df. iloc(), and the vast assortment of filling methods (method=‘ffill’) — these commands swam before my eyes, a jumbled mess of possibilities I could never quite grasp.

One particularly frustrating day, I spent hours trying to create a simple scatter plot with different colors based on a categorical variable. I jumped between Matplotlib’s documentation, Seaborn tutorials, and countless blog posts, each offering a slightly different (and often conflicting) approach. That's when it hit me: I needed a consolidated resource—my own data science cheat sheet that captured the essential Pandas, NumPy, and Matplotlib commands I used most frequently, along with clear examples and explanations.

I started… Read the full blog for free on Medium.

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Published via Towards AI