We frequently hear — “Ohh, there are packages accessible to do every thing! It takes solely 10 minutes to run the fashions utilizing the packages.” Sure, agreed there are packages — however they work solely when you have a clear dataset able to go along with it. And the way lengthy does it take to create, curate, and clear a dataset from a number of sources that’s match for function? Ask an information scientist who’s struggling to create one. All those that needed to spend hours cleansing the info, researching, studying and re-writing codes, failing and re-writing once more will agree with me! This brings us to the purpose:
‘Actual-life information science is 70% information cleansing and 30% precise modeling or evaluation’
Therefore, I assumed, let’s return to fundamentals for a bit and study the right way to clear datasets and make them usable for fixing enterprise issues extra effectively. We are going to begin this sequence with lacking values remedy. Right here is the agenda:
- What are lacking values
- What are the causes of lacking values in a dataset
- Why are lacking values essential
- Method to cope with lacking values