In stephlocke/RMSFTDP: R in the Microsoft Data Platform

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R Syntax {.tabset}

Key syntax and operators.

Basic operators

Action | Operator | Example ------------- | ------------- | ------------- Subtract | - | 5 - 4 = r 5 - 4 Add | + | 5 + 4 = r 5 + 4 Multiply | * | 5 * 4 = r 5 * 4 Divide | / | 5 / 4 = r 5 / 4 Raise to the power | ^ | 5 ^ 4 = r 5 ^ 4 Modulus | %% | 9 %% 4 = r 9 %% 4 Integer division | %/% | 9 %/% 4 = r 9 %/% 4 Basic sequence | : | 1:3 = r 1:3

Comparison operators

Action | Operator | Example ------------- | ------------- | ------------- Less than | < | 5 < 5 = r 5 < 5 Less than or equal to | <= | 5 <= 5 = r 5 <= 5 Greater than | > | 5 > 5 = r 5 > 5 Greater than or equal to | >= | 5 >= 5 = r 5 >= 5 Equal | all.equal() | all.equal(0.5 - 0.3,0.3 - 0.1) is r all.equal(0.5 - 0.3,0.3 - 0.1) Exactly equal | == | (0.5 - 0.3) == (0.3 - 0.1) is r (0.5 - 0.3) == (0.3 - 0.1), 2 == 2 is r 2==2 Not equal | != | (0.5 - 0.3) != (0.3 - 0.1) is r (0.5 - 0.3) != (0.3 - 0.1), 2 != 2 is r 2!=2

States

States | Representation
------------- | ------------- True | TRUE 1 False | FALSE 0 Empty | NULL Unknown | NA Not a number e.g. 0/0| NaN Infinite e.g. 1/0 | Inf

Logical operators

Action | Operator | Example ------------- | ------------- | ------------- Not | ! | !TRUE is r !TRUE And | & | TRUE & FALSE is r TRUE & FALSE, c(TRUE,TRUE) & c(FALSE,TRUE) is r c(TRUE,TRUE) & c(FALSE,TRUE) Or | | | TRUE | FALSE is r TRUE | FALSE, c(TRUE,FALSE) | c(FALSE,FALSE) is r c(TRUE,FALSE) | c(FALSE,FALSE) Xor | xor() | xor(TRUE,FALSE) is r xor(TRUE,FALSE) Bitwise And | && | c(TRUE,TRUE) && c(FALSE,TRUE) is r c(TRUE,TRUE) && c(FALSE,TRUE) Bitwise Or | || | c(TRUE,FALSE) || c(FALSE,FALSE) is r c(TRUE,FALSE) || c(FALSE,FALSE) In | %in% | "Red" %in% c("Blue","Red") is r "Red" %in% c("Blue","Red") Not in | !( x %in% y) | !("Red" %in% c("Blue","Red")) = r !("Red" %in% c("Blue","Red"))

Control constructs

Type | Implementation | Example ------------- | ------------- | ------------- If | if(condition) {dosomething} | if(TRUE) { 2 } is r if(TRUE) { 2 } If else | if(condition) {do something} else {do something different} or ifelse(condition, do something, do something else) | if(FALSE) { 2 } else { 3 } is r if(FALSE) { 2 } else { 3 } ifelse(FALSE, 2, 3) is r ifelse(FALSE, 2, 3) For loop | for(i in seq) {dosomething} or foreach(i=1:3) %do% {something} | for(i in 1:3) {print(i)} is r paste0(1:3) While loop | while(condition) {do something } | a<-0 ; while(a<3){a<-a+1} ; a is r a<-0 ; while(a<3){a<-a+1} ; a Switch | switch(value, ...) | switch(2, "a", "b") is r switch(2, "a", "b") Case | memisc::cases(...) | cases("pi<3"=pi<3, "pi=3"=pi==3,"pi>3"=pi>3) is r memisc::cases("pi<3"=pi<3, "pi=3"=pi==3,"pi>3"=pi>3)

NB: If you find yourself using a loop, there's probably a better, faster solution

Assignment operators

Action | Operator | Example ------------- | ------------- | ------------- Create / update a variable | <- | a <- 10

NB: There are others you could use, but this is the best practice

Accessors

Action | Operator | Example ------------- | ------------- | ------------- Use public function from package | :: | memisc::cases() Use private function from package | ::: | optiRum:::pounds_format() Get a component e.g a data.frame column | $ | iris$Sepal.Length Extract a property from a class | @ | Won't be used in this course Refer to positions in a data.frame or vector | [ ] | iris[5:10,1] Refer to item in a list | [[ ]] | list(iris=iris,mtcars=mtcars)[["iris"]]

Meta-operators

Action | Operator | Example ------------- | ------------- | ------------- Comment | # | # This is my comment Help | ? | ?data.table Identifier | ` | `1`<-2

Exercises

1. Create a variable called Scores that holds the numbers 1 to 10
2. Return whether each number in Scores is an even number
3. Get the help text for the function mean
4. Perform a test to see if R variable names are case sensitive

Answers

#1
Scores<-1:10
#2
(Scores %% 2) ==0
#3
#?mean
#4
scores

R Data types & structures {.tabset}

A brief introduction to data structures and types

Data types

These are the core data types. There are additonal ones like dates with timestamps(POSIXct and POSIXlt) and ordered factors

Data type | Example ------------- | ------------- Integer | 1 Logical | TRUE Numeric | 1.1 String / character | "Red" Factor (enumerated string) | "Amber" or 2 in c("Red","Amber","Green") Complex | i Date | "r Sys.Date()"

Data structures

These are the out of the box data structures. There are other data structure that use these as the basis like data.table or a time-series object.

Data type | Info | Construction example(s) ------------- | ------------- | ------------- Vector | A 1D set of values of the same data type | c(1,"a") , 1:3 , LETTERS Matrix | A 2D set of values of the same data type | matrix(LETTERS,nrow=13, ncol=2) , rbind(1:5,2:6) Array | An nD set of values of the same data type | array(LETTERS, c(13,2)) Data.frame | A 2D set of values of different data types | data.frame(a=1:26, b=LETTERS) List | A collection of objects of various data types | list(vector=c(1,"a"), df=data.frame(a=1:6)) Classes | A class is like a formalised list and can also contain functions i.e. methods | Won't be covered in this class

Exercises

1. Make a variable called ID containing the numbers 1 to 52
2. Make a variable called category holding 52 randomly selected letters (using sample)
3. Make a variable called records that is a data.frame containing ID and category

Answers

#1
ID<-1:52
#2
category<-sample(LETTERS,52, replace=TRUE)
#3
records<-data.frame(ID,category)
head(records)

R Functions {.tabset}

Using functions

• Use an argument's position for well known functions e.g. sum(iris$Sepal.Width)
• Use argument names for less well known functions (or less common arguments) e.g. seq(from=1, to=5, by=1)
• Use argument names to call arguments out of order e.g.seq(by=1, from=1, to=5 )
• Get help for a function that's in a loaded package with ? e.g. ?mean
• Get help for a function that's not loaded with ?? e.g. ??adist
• Search for text or a function in the help with help.search() e.g. help.search("concat")
• Get the definition of a function by calling it without brackets e.g. Sys.Date

Functions can ...

• have named arguments e.g. ifelse(test, yes, no)
• take any number of arguments e.g. mean(...)
• take a combination of named and unlimited arguments e.g. seq.int(from, to, by, length.out, along.with, ...)
• act as operators e.g. +,%%,%>%
• work as you'd would normally expect e.g. mean(iris$Sepal.Width)
• return functions e.g. scales::gradient_n_pal
• have side-effects like making a plot and also returning some data

Basic function writing

• Functions are created with the syntax function(args){code}
• Functions do not need to be stored to be used
• Store a function with myfunc<-function(args){code}
• Functions will usually output whatever object was last called but not stored f<-function(){1}; f()
• Use the return() function to output something specific f<-function(){return(1)}; f()
• Make an argument optional by providing it with a default value or NULL

myfunc<-function(arg1, arg2=NULL){
print(arg1)
if(!is.null(arg2)) return(arg2)
}

Exercises

1. Use the function cut() to produce split floor(rnorm(n = 100, mean=50,sd=20)) into 5 bins with numbers representing the bins they were allocated
2. Write a function that says "Hello world" or says hello to any string or number passed in (use paste)

Answers

#1
nums<-floor(rnorm(n = 100, mean=50,sd=20))
bins<-cut(nums, breaks=5, labels=FALSE)

#2
hello<-function(x=NULL){
  if(is.null(x)) x<-"world"
  res<-paste0("Hello ", x, "!")
  return(res)
}
hello()
hello("Dave")
hello(c("Dave","Jane", "7"))

stephlocke/RMSFTDP documentation built on May 30, 2019, 3:36 p.m.