It’s one of those “depends” things. If you’re just doing EDA or simple stats, nah, don’t sweat it. But if you’re building models, it’s pretty much a must.
Whats the point of pandas normalization? Mostly to avoid bias in your models. Like, imagine predicting house prices—sq footage vs. # of bedrooms would skew things if not scaled.
I usually use `(df - df.min()) / (df.max() - df.min())` for quick normalization. Easy peasy.
Whats the point of pandas normalization? Mostly to avoid bias in your models. Like, imagine predicting house prices—sq footage vs. # of bedrooms would skew things if not scaled.
I usually use `(df - df.min()) / (df.max() - df.min())` for quick normalization. Easy peasy.