The real world is messy, and so too is its data. So messy, that a recent survey reported data scientists spend 60% of their time cleaning data. Unfortunately, 57% of them also find it to be the least enjoyable aspect of their job.

Cleaning data may be time-consuming, but lots of tools have cropped up to make this crucial duty a little more bearable. The Python community offers a host of libraries for making data orderly and legible—from styling DataFrames to anonymizing datasets.

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