For this assignment you are going to inspect a “dirty” dataset, and identify the pitfalls the dataset suffers from.

The dataset was gathered from the website of the World Nuclear Association, and contains data on nuclear power plants worldwide. But the data was altered to mimic common pitfalls in data.

You can download the file with the link below.

reactors.xlsx

Expected outcome

In the submissions below, list all the issues you can find in the dataset. Optionally, you can list the techniques and strategies you could use to avoid the pitfalls and remediate the issues with the data.

After submitting the assignment, you can continue the course with the suggested next module Pitfalls in dataviz: scales and proportions, or you can pick another module from the

Submissions

<aside> 🆘 In case you are not familiar with writing and adding images on Notion, watch the video linked below before submitting.

</aside>

Notion 101: Write and edit text

Submission from Elisabet Salas

• Column A: the URLs are too long and without hyperlink that would help to find the information of each reactor in one click.
• Column B: The encoding of the reactors’ names are not standarized, in some of the names there are some characters “( )” and abbreviations that create confusion.
• Column C: the countries should be encoded with ISO 3166  country code.
• Column D: the units are not the same and there are two strings per cell (number and text). The header of the columns should show the units and the values should be all converted to the same unit (MWe or GWe). Moreover some values are missing or appear as “OPERABLE”.
• Column F: The status values are not standarized. This makes impossible to perform any analysis or comparison among all the reactors.