To give an example, I was exploring data provided by the NFL (data here) to see if I could discover any insights regarding variables that increase the likelihood of injury. And if you don’t know what you don’t know, then how are you supposed to know whether your insights make sense or not? You won’t. However, many EDA techniques can remedy some common problems that are present in every dataset. I’m not saying that EDA can magically make any dataset clean - that is not true. With EDA, it’s more like, “garbage in, perform EDA, possibly garbage out.”īy conducting EDA, you can turn an almost useable dataset into a completely useable dataset. Have you heard of the phrase, “garbage in, garbage out”?
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