Basic R-Language Notes

Notes for Learning R language

Printing Something

• Simply write the string
• use print() function

Comments

• Only single line comment (starts with #)

Variables

• Use <- assignment operator to assign value to any variable Like; x<-"Kushang shah"
• = is also fine but it can be forbidden in some context in R.
• print variable by print(x)

Concatation of variables

• paste() function is being used.
• x <- "Awosome"
• paste("R is ", x)
• Prints 'R is Awosome'
• concatation of variables are also fine paste(var1, var2)
• Yo can add more than 2 parameters in paste() function as well. paste("R is ", x, y) works just fine.
• paste() function always concates as strings (paste(1,2,3) will give '123' as output)
• To add numbers + operator comes in picture. x + y
• x<-y<-z<-'yo' assigns 'yo' to each variables.

Data types

• numeric, integer, complex, character(string), logical
• (10.5), (1L letter "L" declares this as an integer), (9 + 3i, "i" is the imaginary part), ("Yoman"), (TRUE or FALSE)
• We can use class() function to check the data types of each variable.

Numbers in R

• numeric, integer, comples are numbers.

• numeric contains any number with or without decimal; 10, 34.2 etc.

• Integers are numerica data without decimals.

• A complex number is written with an "i" as the imaginary part.

Type conversions in numbers

• as.numeric(), as.integer(), as.complex() is being used.
• Warning message shows up when you try to convert complex to integer or numeric. Viseversa works fine.

Mathamatics in R

• R have many operators for math.

• +, -, *, /, ^, %%, %/%

• (add), (sub), (mul), (div), (exponent), (modulus:Remainder), (integer div)

• Some build in math functions.

• min(), max(), sqrt(), abs(), ceiling(), floor()

R strings

• To add multiline strings...

x <- " Hey man, I am
    Kushang shah.
"

• It will add \n whenever you have break the line.

• If you want to print exactly like this then use cat() function.

• cat(x) will print it accordingly.

• To get the length of string use nchar() function.

• Use grepl() function to check a substring in string. Returns boolean. grepl("H", "Hello")

• paste() function is being used to combine two or more stirngs.

• \ is an escape character.

• However, while printing string \ will also get print. Use cat() function to avoid that.

Booleans in R

• ==, !=, >, <, >=, <= operators returns boolean. They are comparision operators.

• &, &&, |, ||, ! are logical operators.

• (and, or, not)

• Will find the difference after vectors.

• :, %in%, %*% (Miscellaneous operators)

• (creates a series of numbers, seperates all by 1), (Find out if an element belongs to a vector), (matrix multiplication)

if...else

a<-2
b<-3

if (b > a) {
  print("b is greater than a")
} 

• Always use {} to define scope.
• else if is also there.
• &, |, ! is used for logical operations.

Loops in R

• Two loops are there. While and for.

While loops

i <- 1
while (i < 6) {
  print(i)
  i <- i + 1
}

• We can break the loop with break statement.
• With the next statement, we can skip an iteration without terminating the loop.

For loops

for (x in 1:10) {
  print(x)
} 

• With the for loop we can execute a set of statements, once for each item in a vector, array, list, etc.
• The for loop does not require an indexing variable to set beforehand, like with while loops.
• break and next statements works the same as while.

Functions in R

• A function is a block of code which only runs when it is called.

my_function <- function(){ 
  print("Hello World!")
}

• To call a function just simply write their name and paranthesis. See below code.

my_function <- function() {
  print("Hello World!")
}

my_function()

Arguments of functions

• Information can be passed into functions as arguments.
• You can add as many arguments as you want, just separate them with a comma.

my_function <- function(fname) {
  paste(fname, "Griffin")
}

my_function("Peter")
my_function("Lois")
my_function("Stewie") 

• To give the parameter a default value, use my_function(par = 'yo'){} in the function definition.
• When calling the function, number of arguments must be tha same of parameters of function definition.
• To return a value from the function use return() function.

my_function <- function(x) {
  return (5 * x)
}

print(my_function(3))

Write a function within a function

• In R, we can write a new function within another function. Inner function can only be called from inside the function.

Outer_func <- function(x) {
  Inner_func <- function(y) {
    a <- x + y
    return(a)
  }
  return (Inner_func)
}
output <- Outer_func(3) 
output(5) # Prints 8 because 5 + 3 = 8

• Code explanation:

• Here, first we are storing Outer_func(3) function's return value Inner_func in output variable.

• Then now we have Inner_func in output variable, so we call output with the parameter y value.

• During the declaration of output variable, function's x value get initialized. And in later we use it.

• Recursion is also working in R.

Global variables

• Global variables can be used by everyone, both inside of functions and outside.

txt <- "awesome"
my_function <- function() {
  paste("R is", txt)
}

my_function()

• If you create a variable with the same name inside a function, this variable will be local, and can only be used inside the function.
• To create a global variable inside a function, you can use the global assignment operator <<-

my_function <- function() {
txt <<- "fantastic"
  paste("R is", txt)
}

my_function()

print(txt)

• Also, use the global assignment operator if you want to change a global variable inside a function.

Data Structures

• Here we will cover list, vectors, plotting, stats etc.

R Vectors

• A vector is simply a list of items that are of the same type.
• use c() function to make a vector. x<-c('yo', 'man')
• A vector can contain only one type of data. If we add numeric data or logical data along with string then it will treat all values as string.
• 1:10 will return a vector with 1 difference. (1 2 3 ... 10)
• 1.5:5.5 (1.5 2.5 3.5 4.5 5.5)
• 1.5:5.4 (1.5 2.5 3.5 4.5)
• To sort a vector use sort() function.

fruits <- c("banana", "apple", "orange", "mango", "lemon")
numbers <- c(13, 3, 5, 7, 20, 2)

sort(fruits)  # Sort a string
sort(numbers) # Sort numbers 

• To access a value of vector use [index].
• Like; x<-c("Yo", "No", "hey")
• x[1] # prints "Yo"
• In R indexing starts from 1.
• We can also refer to different indexes using c() function.

fruits <- c("banana", "apple", "orange", "mango", "lemon")

# Access the first and third item (banana and orange)
fruits[c(1, 3)] 

• To find out how many items a vector has, use the length() function.
• To add new value in a vector, simply assign value to that index. fruits[4] <- "Kiwi".
• You can also use negative index numbers to access all items except the ones specified. Like fruits[c(-1)]. It ignores 1st value.
• To change an item use fruits[1] <- "kiwi"

Repeat vectors

• Use rep() function.

• To repeat each value; repeat_each <- rep(c(1,2,3), each = 3)

• It will print 111222333

• To repeat sequence; repeat_sequence <- rep(c(1,2,3), times = 3)

• It will print 123123123

• To repeat each value independently; repeat_independent <- rep(c(1,2,3), times = c(4,3,2))

• It will print 111122233

Generating sequenced vectors

• : operator generates sequenced vector with interval of value 1.
• To make bigger or smaller steps in a sequence, use the seq() function:
• numbers <- seq(from = 0, to = 100, by = 20) # prints 0 20 40 60 80 100

Lists

• A list in R can contain many different data types inside it.
• Use list() function to create one.
• Indexing of list also starts with 1.

thislist <- list("apple", "banana", "cherry")

thislist[1] 

• To access the value use []. Same as vectors.
• To change the value, same as vectors.
• Find the length with length() function.
• To find out if a specified item is present in a list, use the %in% operator.

thislist <- list("apple", "banana", "cherry")

"apple" %in% thislist

Add item to the list

• To add an item to the end of the list use append() function.

thislist <- list("apple", "banana", "cherry")

append(thislist, "orange")

• To add an item to the right of a specified index, add "after=index number" in the append() function.

thislist <- list("apple", "banana", "cherry")

append(thislist, "orange", after = 2)

• fruits[-1] will return the list except the index value 1.
• So, with the help of this feature, we can delete index 1 by copying the updated list in new variable.
• You can specify a range of indexes by specifying where to start and where to end the range, by using the : operator.
• Example; fruits[1:4]
• It will start from index 1 to index 4. Both incuded.

Loop through a list and vectors:

• Vectors

fruits <- c("banana", "apple", "orange")

for (x in fruits){
	print(x)
}

• List looping is also same as vector's.

thislist <- list("apple", "banana", "cherry")

for (x in thislist) {
  print(x)
}

Join two lists:

• The most common way to do this is to use the c() function.

list1 <- list("a", "b", "c")
list2 <- list(1,2,3)
list3 <- c(list1,list2)

list3 

R Matrices

• Two dimentional data set.
• Use matrix() function to make one.

# Create a matrix
thismatrix <- matrix(c(1,2,3,4,5,6), nrow = 3, ncol = 2)

# Print the matrix
thismatrix 

• Assignment of c() starts column wise. So, 1,2,3 will be in column1 and 4,5,6 will be in column2.
• Note: c() function is used to concatenate items together.
• To access matrix item, thismtrix[1,2] will be used.
• To access an entire row, use thismatrix[1,]. Entire 1st row will be displayed.
• To access an entire column, use thismatrix[,1]. Entire 1st column will be displayed.
• Access more than one rows, use thismatrix[c(1,2),]. Row 1 and 2 will be displayed.
• Access more than one columns, use thismatrix[,c(1,2)]. Column 1 and 2 will be displayed.

Add and remove from Matrices

• To add Row use rbind() function.

thismatrix <- matrix(c("apple", "banana", "cherry", "orange","grape", "pineapple", "pear", "melon", "fig"), nrow = 3, ncol = 3)

newmatrix <- cbind(thismatrix, c("strawberry", "blueberry", "raspberry"))

# Print the new matrix
newmatrix 

• To add Column use cbind() function.

thismatrix <- matrix(c("apple", "banana", "cherry", "orange","grape", "pineapple", "pear", "melon", "fig"), nrow = 3, ncol = 3)

newmatrix <- rbind(thismatrix, c("strawberry", "blueberry", "raspberry"))

# Print the new matrix
newmatrix 

• Remember one thing that always try to maintain the dimention. Otherwise it will pop an error.
• To remove things from matrix use thismatrix[-c(index1), -c(index2)].
• thismatrix[-c(1),] will remove first row.
• thismatrix[,-c(1)] will remove first column.
• thismatrix[-c(1),-c(1)] will remove first row and first column.
• To check whether an element exists in the matrix use %in% operator.
• Use the dim() function to find the amout of rows and columns in a matrix.
• Use length() function to find the dimention of any matrix.

Combine two matrices

• We can use rbind() and cbind() functions to combine two matrices.
• Make sure both have same rows count or columns count accordingly.

Arrays in R

• Arrays can have more than 2 dimentions.
• Use array() function to make and dim parameter to specify the dimention.

arr <- array(c(1:24), dim = c(4, 3, 2))
arr

• In dim = c(4, 3, 2), 4 is number of rows, 3 is number of columns, 2 is how much dimention we wants.

• Arrays can only have one data type.

• To access any array item arr[2, 1, 2] use this.

• array[row position, column position, matrix level]

• To access the entire 1st row use arr[c(1),,1]

• To access the entire 2nd column use arr[,c(1), 1]

• To check if an item exists in an array use %in% operator. 'yo' %in% arr.

• To get the amout of rows available in an array use dim() function.

• To get the dimention of an array use length() function.

• Loop in an array is simple.

thisarray <- c(1:24)
multiarray <- array(thisarray, dim = c(4, 3, 2))

for(x in multiarray){
  print(x)
} 

Data Frames in R

• Data Frames are data displayed in a format as a table.
• Can have different types of data but the data type of one column must be same.
• data.frame() function is used for DF creation.

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

# Print the data frame
Data_Frame 

• In the above example, Training, Pulse, Duration is a columns and their values have respective column values.
• Use summary() function to summarizes the data.
• Use [], [[]] or $ to access items in DF.
• Data_Frame[1], Data_Frame[["Training"]], Data_Frame[[1]], Data_Frame$Training will all load 1st column.
• Data_Frame[1] loads value as data.frame type while Data_Frame[[1]] returns a vector. So, generally for computation purpose use [[index]].
• Use rbind() and cbind() function to add rows and columns respectively.
• New_row_DF <- rbind(Data_Frame, c("Strength", 110, 110))
• New_col_DF <- cbind(Data_Frame, Values = c('val1', 'val2', 'val3'))

Operations on DataFrame

• To remove a row use c() function.
• n <- df[-c(1),] Removes first row.
• n <- df[,-c(1)] Removes first column.
• n <- df[-c(1), -c(1)] removes first row and column.
• Use dim() function to find the amount of rows and columns.
• Use length() function to get the columns count in df.
• ncols() and nrows() also returns counts for columns and rows respectively.
• We can also use rbind() function to combine two dfs rows (vertical combination).

Data_Frame1 <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

Data_Frame2 <- data.frame (
  Training = c("Stamina", "Stamina", "Strength"),
  Pulse = c(140, 150, 160),
  Duration = c(30, 30, 20)
)

New_Data_Frame <- rbind(Data_Frame1, Data_Frame2)
New_Data_Frame 

• We can use cbind() function to combine two dfs columns (Horizontally).

Data_Frame3 <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

Data_Frame4 <- data.frame (
  Steps = c(3000, 6000, 2000),
  Calories = c(300, 400, 300)
)

New_Data_Frame1 <- cbind(Data_Frame3, Data_Frame4)
New_Data_Frame1

R Factors

• Used to catagorize the data.
• Gender: male, female etc.
• In order to make a factor, use factor() function.

# Create a factor
music_genre <- factor(c("Jazz", "Rock", "Classic", "Classic", "Pop", "Jazz", "Rock", "Jazz"))

# Print the factor
music_genre 

• To print only levels use level(music_genre).
• We can also specify level argument inside the function.
• x <- factor(c("Classic", "Opera"), levels = c("Classic")).
• Use the length() function to get the length of all the c() values of factor.
• To access the factor items use [].
• music_genre[3] # Gets third value of factor's vector.

Change values in factor

• To change the value in a factor, do this. fac[2] <- "Yoman"

music_genre <- factor(c("Jazz", "Rock", "Classic", "Classic", "Pop", "Jazz", "Rock", "Jazz"))

music_genre[3] <- "Pop"

music_genre[3] 

• But note one thing here, that we cannot change the value of vector if the value is not in the levels.
• But if we have already specified that new value in the levels already then we can do this.

music_genre <- factor(c("Jazz", "Rock", "Classic", "Classic", "Pop", "Jazz", "Rock", "Jazz"), levels = c("Classic", "Jazz", "Pop", "Rock", "Opera"))

music_genre[3] <- "Opera"

music_genre[3]