nah ur not lazy—whats the point of pandas normalization if ur data’s already clean? but here’s the kicker: some models *need* it.
like, k-means clustering uses distances. if one feature’s scale is huge, it’ll warp the whole model. normalization keeps things fair.
for a quick demo, check out this [scikit-learn guide](https://scikit-learn.org/stable/modules/...ssing.html). it’s not just hype.
like, k-means clustering uses distances. if one feature’s scale is huge, it’ll warp the whole model. normalization keeps things fair.
for a quick demo, check out this [scikit-learn guide](https://scikit-learn.org/stable/modules/...ssing.html). it’s not just hype.