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4/13 Create an id column

1. Introduction

2. Reading file

3. Create factors

4. Create an id column

5. Delete a column

6. Explore the levels of factors in the dataset

7. Change factor levels

8. Load the second CSV

9. Join the two datasets

10. Clean up the data

11. Calculate some statistics

12. Calculate statistics for age groups

13. Congratulations

Okay, we need an ID. The ID will be the first part of a resident’s email address.

Create new columns named id and domain using the email column and @ as a separator. Overwrite the personal_info dataset.

Type:

personal_info <- separate(
  personal_info,
  email,
  sep= "@",
  into = c("id", "domain"))

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Tidyverse

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