Not All Missing Data Is Equal: A Data Scientist’s Guide to Smarter Handling of Missing Values
You’ve seen it before.You’ve been there. You import a fresh dataset, your mind buzzing with machine learning possibilities. You run a .info() or .describe(), and your heart sinks. You see it: NaN. Null. Empty cells. Missing data. It’s the silent killer of model accuracy and the source of countless data science headaches. Missing data is […]