Lab | Data Cleaning Bonus Challenge

The objectives of this lab are:

• Know the Iris Dataset (you will use it tomorrow)
• Review cleaning concepts

Introduction

As you know, data comes with a lot of errors. In this lab we propose you a challenge. We have purposely added some errors to the famous Iris flower dataset. Let's take a look on the data and fix some possible errors as:

• Data is encoded properly.

• Data falls within the expected range, and use domain knowledge whenever possible to define that expected range.

• Deal with missing data in one way or another: replace it if you can or drop it.

Some advices:

• Never tidy your data manually because that is not easily reproducible

• Use code as a record of how you tidied your data

• Plot everything you can about the data at this stage of the analysis so you can visually confirm everything looks correct

Deliverables

• A notebook with the code you used to clean the data.
• The final data in a csv.