1. Using the xlsx or readxl package or otherwise, read each sheet in the ”assignment1.xlsx” file into R.
2. Generate a data frame for each sheet in the file.
3. The dataset in the first sheet is a random selection from a larger dataset. You will never get access to the full dataset so you should regenerate a new identification number for each subject in the dataset. This should be the row number of each entry in Sheet 1. You do not need to do this for Sheet 2.
4. It is also required to have an additional identifier which is the number you have generated in (3) followed by the first letter of each subjects first name and then followed by the first letter of each subject’s surname. You do not need to do this for Sheet 2.
5. Although the data is not available for most subjects, some data highlighting subjects state of health is available in Sheet 2. You should use the subjects ID number to match it and merge it with the data in Sheet 1.
6. Not every subject has its ID number included in Sheet 2. You should attempt to match the remaining subjects using their first and surnames. This must be done using tidyverse in a robust manner. Your code for doing this should work again in the case of a new sample of data being provided. 7. You should add a column for age range. This should be
Age Range
Category Name
0-17
1
18-35
2
35-54
3
54-74
4
74-
5
8. You should filter the data by each age category. Generate a bar plot using ggplot2 for the criminal record variable.
9. You should generate an appropriate visualisation examining the relationships between height, weight, age and criminal records. Comment on this.
10. Using filters, you should analyse if there are any interesting results in the dataset regarding the relationships between height, weight and criminal record. Use appropriate visualisations.
