Links to a carefully curated collection of Youtube videos provide a host of additional sourcs for you to develop your ability to use R software in an engaging and accessible manner.
Video 4.1: ‘R tutorial: the basic data types in R’
Question 1: What are the different basic data types in R?
Answer: Logical, numeric, integer (form of numeric), and characters
Question 2: How can you check the data type of a variable in R?
Answer: You can use the class() function, but also you can use the is._() function.
Question 3: How can you coerce one variable type to another type in R?
Answer: You can use the as._() function.
Video 4.2: ‘R tutorial: using the data frame in R’
Question 1: What are the rows and columns in a data frame in R?
Answer: Rows are the observations and columns are the variables.
Question 2: How do we create our own data frame in R?
Answer: You combine your variables using the data.frame() function, where all variables need to be the same length.
Video 4.3: ‘Importing data into R – how to import csv and text files into R’
Question 1: How do we read-in csv files into R?
Answer: You can use the read.csv() function or the read.table() function (but need to specify more arguments).
Question 2: What does the read.csv2() function do?
Answer: It is for csv files that use commas instead of decimals in numbers; which is more common in Europe.
Video 4.4: ‘How to subset data in R with square brackets and logical statements’
Question 1: What is the difference between using = and == in R?
Answer: = can be used to assign values to objects, while == means ‘equal to’ in a mathematical sense.
Question 2: Why is ‘female’ and ‘male’ but in quotes in the R code?
Answer: Because those are the character values for the factor variable ‘gender’ in the dataset.
Question 3: How do we keep all the columns when subsetting the dataset?
Answer: You leave a blank space after the comma in the square brackets.
Video 4.5: ‘How to export data out of R (into .csv, .txt, and other formats)’
Question 1: Why would we want to export data out of R?
Answer: In order to save data that we have manipulated from an existing dataset, we can export as some file format.
Question 2: What happens when we save a file with the same name as an existing file?
Answer: The file is saved, but it automatically overwrites the existing file.
Question 3: What is the quicker way of saving files as csv in R?
Answer: Use the write.csv() function instead of the more generic write.table() function.
Video 4.6: ‘Changing a numeric variable to categorical variable in R’
Question 1: What is the R function used to create the categorical variable?
Answer: The cut() function
Question 2: What is the default for how the categorical intervals are created?
Answer: In the cut() function, the default is for intervals to be left open and right closed.
