Basic R Flashcards
Write a function drawing x times with replacement from the standard normal distribution, then taking an average and printing it
myfunction
Load all functions in the R file “functions.R” in the working directory
source(“functions.R”)
Show working directory
getwd()
Show contents of working directory
dir()
Choose working directory
setwd()
Get help for the source() function
?source
Find help for linear regressions
help.search(“linear regression”)
What are the five atomic classes of objects
character, numeric, integer, complex and logical
What is the difference between a list and a regular vector
The list may contain elements of different classes, the elements of a vector all have to be the same class
Assign the integer 1 (not the number) to the object x
x
Find out what class x is
class(x)
Divide 1 by infinity
1/Inf
Give examples of object attributes
Names, dimnames, dimensions, class, length, etc.
Create an empty numeric vector x with 100 elements
x
Input the letters a, b and c as elements in a vector x
x
What happens if you concatenate elements of different classes?
They are all coerced to one class
Make a vector consisteng of the integers 1 to 10 to a character format
x
What happens if you run
x
NAs are introduced by coercion for the first and second elements
Create a matrix x of zeroes with two rows and two columns
x
create two vectors containing the integers 1 to 3. Merge them into a matrix as rows and into a matrix as columns
x
Transform a vector containing the integers 1 to 10 into a matrix with two rows.
x
What are the two types of factors and what distiguishes them?
Unordered (categorical, unranked), ordered (categorical, ranked)
Why is it better to use factors than integer categories
They are self-describing
Make a factor vector containing five yes/no elements. Get a frequency count of each factor level.
x
What is the difference between NA and NaN?
NA missing values
NaN undefined mathematical operations (subset of NA)
Test which elements in the vector x are NAs and which are NANs
is. na(x)
is. nan(x)
Returns logical vectors with corresponding elements TRUE if the element in the original vector is missing
What are data frames used for?
- Tabular data
- The columns do not have to be the same class
- The rows have names
Create a data frame x with a “letters” column consisting of the first four letters of the alphabet and a “numbers” column consisting of the first four integers. Give the rows the names “first”, “second”, etc…
x
Create a vector x with the integers from one to three. Give the elements names.
x
What are the most important arguments in read.table() function?
file, header, sep, colClasses, nrows, skip, stringsAsFactors
How large a dataset can you load with read.table() and read.csv()?
However much RAM you have available
What is the main advantages of dump() or dput() relative to write.table() or write.csv()
They preserve R metadata (like class) and work better with version control applications like Git
Save the dataframe x in a textual format that preserves metadata. Then read it into r again
dput(x, file=”x.R”)
dget(“x.R”)
Save the dataframes x and y in a textual format that preserves metadata. Removet hem and then read them into r again
dump(c(“x”,”y”), file=”data.R”)
source(“data.R”)
What is the main difference between dput() and dump()?
Dump() works on several objects, dput() only works on one. Source() will pull in the objects as they were, dget() requires you to assign them anew
How do you get a website as text loaded into r
y
What are the three subsetting operators and how are they different?
[ object of same type [[ single element, class may differ, allows using calculated values, makes subsetting of a list by c( , ) sequential $ extracts by name, does partial matching by default
Create a vector x with the letters from a to d. Now create the vector y consisting of letters in x after b
x “b”]
Create a vector x with the letters from a to d. Now create the vector y of logicals answering “y>a?” Use y to subset x
x “a”
x[y]
Make a list x consisting of 1) The number from 1 to 3, 2) the letters a and b and 3) TRUE. Name the elements “num”, “let” and “log”.
Extract the first element in the list by its name, then extract as a list, then extract only its contents.
Exctract the third element of the first element
x = list(1:3, c(“a”,”b”), TRUE)
names(x)
Make a vector with three words as elements. Extract the first and third word with one command.
x
Make a 2x2 matrix x containing the numbers 1 to 4. Order numbers first by columns, the by rows. Subset the four, but keep it as a matrix.
x
Create a vector x with numbers and NAs. Subset all non-NAs as a vector y.
x
Create a data frame with two numeric variables with a few NAs. Subset out the data frame y consisting of the complete cases.
x
Draw from a standard normal distribution and assign to object x. Make a logic statement that assigns 1 to y if x is above 0 and 0 to y otherwise.
x
