An useful guide to a proper deal with missing categorical data, with use cases

In this post, it will be shown how to deal with categorical features with missing values with several examples compared to each other. It will be used the Classified Ads for Cars dataset to predict the price of ADs through a simple model of Linear Regression.

To show the various strategies and relevant pros / cons, we will focus on a particular categorical feature of this dataset, the maker, the name of the brand of cars (Toyota, Kia, Ford, Bmw, …).

Post Steps:

  • Deal with missing values in Categorical Features: we will…

Daniele Salerno

Software Engineer | Python Developer | Data Science Enthusiast |

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