Understanding the working of 'interpolation'

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'Interpolation' is a technique that is used to predict a null/empty value by studying its neighbouring points.

Interpolation doesn't take into consideration the entire dataset when predicting the missing value of a column. It only considers the values of the column that is being interpolated.

What I have tried:

So, how does this technique identify the null value's closest neighbours? How does a value that doesn't exist be considered for anything? What is its reference point?

Posted 8-Nov-23 6:40am

Apoorva666

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Gerry Schmitz · Accepted Answer · 2023-11-08T07:09:00

Solution 1

To interpolate, you need the "relative position" of the missing point, relative to the "two" points on "either side" of the missing value.

In other words, you can't interpolate unless you have at least 2 points to start with, and you know "about" where the missing value should be.

e.g. If the two points are 6 and 12, a missing "middle value" would be 6 + ((12-6) * .5) = 9.

Posted 8-Nov-23 7:09am

Gerry Schmitz

Comments

CPallini 9-Nov-23 5:52am

5.

Andre Oosthuizen 9-Nov-23 13:55pm

And my 5!