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R: Data Import

Data Import Exercises

library(tidyverse)

This file can be downloaded here.

Exercise 1

First, check the following files in your text editor (NotePad for Windows users, TextEdit for Apple users).

Next, report the field separator and the function that you will use to import the data. Also think of you need extra arguments in your function to import the data correctly (for example: do you need the locale = argument?). Last, load the datasets in R using the csv, csv2, or tsv import functionality and check if the data is imported correctly.

File 1:

#Your code here for file 1

File 2:

#Your code here for file 2

File3:

#Your code here for file 3

File 4:

#Your code here for file 4

Exercise 2

Download the Heart Disease Health Indicators dataset to your computer. Unzip the file and import the csv data in R.

#Your code here

Exercise 3

Download the Properties of ATC-accepted medicines dataset to your computer. Unzip the file and import the csv data in R.

#Your code here

Exercise 4

Download the Food allergens and allergies dataset to your computer. Unzip the file and import the csv data in R.

#Your code here

Exercise 5

Download the Patients dataset to your computer. Unzip the file and import the csv data in R.

#Your code here

Exercise 6

Use R to create a csv file from the following table:

Protein Name Location Weight (kD) Date submission Source
ORF1 21571..25392 14.3 29-FEB-2020 Published
ORF3a 25401..26228 23.9 29-FEB-2020 Unpublished
ORF4b 26253..26480 161.1 29-FEB-2020 Unpublished
ORF6 27210..27395 35.9 29-FEB-2020 Submitted
ORF7a 27402..27767 24.6 29-FEB-2020 Unpublished 
#Your code here

Use code to prove that the data was written to a csv file (code to read the csv file that you have just created):

#Your code here

Exercise 7

Use the same data from exercise 6 but now write code to create an Excel file. Make sure to include the column headers.

#Your code here

Exercise 8

Use code to open the Excel file from exercise 7.

#Your code here

Exercise 9

The zip file in this link contains 25 small exercises to load data as a tibble in R.
Unpack the zip file and open the Rmd file for instructions.

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