Why Your Data Code Feels Slow (And What Actually Speeds It Up)
When people say their data code feels slow, they usually mean something a little different. It feels heavy.
Every small change takes too long to try out. Running the script feels like a whole event instead of a quick test.
You pause before hitting run because you already know you are going to be waiting. The computer seems to be struggling with something that looks simple on the surface.
Most of the time, people blame Python. Or pandas. Or the size of the dataset.
That reaction makes sense. But it is usually not the real issue.
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Early on, performance problems in data work are not really about raw CPU speed. They are about friction. They come from making the computer do work it does not need to do.
They come from moving too much data around. They come from how the code is structured.
The biggest improvements usually do not come from fancy tricks or new tools. They come from thinking about the problem differently.
Most slow data code is not wrong. It is just shaped the wrong way.
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