Handle your missing data like a pro!

Part 1: Missing Data Series — Deleting missing data

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  1. DROPPING/DELETING THE MISSING ROWS

When to use this method

  • When you have a large data set — When your data set has millions and millions of rows of data, deleting a few rows with blank features will not really make a dent. However, if the data set is small, this is not advisable as that row represents a very important piece of insight.
  • When most of the records are missing — Sometimes, you will have a situation where you have a lot of information missing. For example if you have most entries missing. If that is the case, it is then very difficult to

How Its done

  • To begin with, I have imported some dummy data with some NaN/Null values.
  • The 2nd last row has no data on the age, the city of residence, the weight and diabetes information. This presents once case in which it will make sense to drop that row of data.

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Technical Writer with a knack for explaining hard things in an easy way. All things tech!

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TechNotes by Abby

Technical Writer with a knack for explaining hard things in an easy way. All things tech!