R Programming: Mathematical Functions In R

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Slide 1 www.r-squared.in/rprogramming
R Programming
Learn the fundamentals of data analysis with R.

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Course Modules
www.r-squared.in/rprogramming
✓ Introduction
✓ Elementary Programming
✓ Working With Data
✓ Selection Statements
✓ Loops
✓ Functions
✓ Debugging
✓ Unit Testing

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Working With Data
✓ Data Types
✓ Data Structures
✓ Data Creation
✓ Data Info
✓ Data Subsetting
✓ Comparing R Objects
✓ Importing Data
✓ Exporting Data
✓ Data Transformation
✓ Numeric Functions
✓ String Functions
✓ Mathematical Functions

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In this unit, we will explore the following mathematical functions:
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Mathematical Functions
● Arithmetic Operators
● Column/ Row Operators
● Cumulative Operators
● Sampling
● Set Operations
● Logarithm

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Arithmetic Operators
Operator Description
+ Addition
- Subtraction
* Multiplication
/ Division
^ Exponential
%% Modulus
%/% Integer division

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Examples
> # example 1
> x <- 5
> y <- 2
> x + y
[1] 7
> x - y
[1] 3
> x * y
[1] 10
> x / y
[1] 2.5

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Examples
> # example 2
> x <- 5
> y <- 2
> x ^ y
[1] 25
> x %% y
[1] 1
> x %/% y
[1] 2

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Column & Row Operations
colSums Sum of column values
rowSums Sum of row values
colMeans Mean of column values
rowMeans Mean of row values

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Column & Row Operations
Examples
> # example 1
> m
[,1] [,2] [,3]
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9
> colSums(m) # sum of columns
[1] 6 15 24
> rowSums(m) # sum of rows
[1] 12 15 18
> colMeans(m) # mean of columns
[1] 2 5 8
> rowMeans(m) # mean of rows
[1] 4 5 6

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Cumulative Operations
cumsum Cumulative sums
cumprod Cumulative products
cummin Cumulative minima
cummax Cumulative maxima

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Cumulative Operations
Examples
> # example 1
> x <- 1:5
> cumsum(x)
[1] 1 3 6 10 15
> cumprod(x)
[1] 1 2 6 24 120
> x <- c(3:1, 2:0, 4:2)
> cummin(x)
[1] 3 2 1 1 1 0 0 0 0
> cummax(x)
[1] 3 3 3 3 3 3 4 4 4

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Miscellaneous Functions
max Maxima
min Minima
pmax Parallel minima
pmin Parallel maxima
sum Sum of the values
prod Product of the values
range Min and Max of the values

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Examples
> # example 1
> x <- c(3, 26, 122, 6)
> min(x)
[1] 3
> max(x)
[1] 122
> prod(x)
[1] 57096
> sum(x)
[1] 157
> range(x)
[1] 3 122

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Examples
> # example 2
> x <- c(3, 26, 122, 6)
> y <- c(43,2,54,8)
> z <- c(9,32,1,9)
> pmin(x, y, z)
[1] 3 2 1 6
> pmax(x, y, z)
[1] 43 32 122 9

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sample()
Description
sample() takes a sample of the specified size from the elements of an object, with or
without replacement.
Syntax
sample(x, size, replace = FALSE, prob = NULL)
Returns
Sample of the specified size.
Documentation
help(sample)

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sample()
Examples
> example 1
> x <- 1:10
> sample(x)
[1] 10 1 4 2 9 7 5 6 8 3
> sample(10)
[1] 7 6 10 8 2 9 1 3 4 5
> sample(x, size = 5)
[1] 1 10 8 9 5

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sample()
Examples
> example 2
> c <- c("Heads", "Tails")
> sample(c, size = 1)
[1] "Heads"
> sample(c, size = 2)
[1] "Tails" "Heads"
> sample(c, size = 10, replace = TRUE)
[1] "Tails" "Tails" "Tails" "Heads" "Heads" "Heads" "Tails" "Heads" "Heads" "Heads"
> table(sample(c, size = 10, replace = TRUE))
Heads Tails
5 5

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Set Operations
Perform set operations on two vectors
Operation Description
union(x, y) Union of x and y
intersect(x, y) Intersect of x and y
setdiff(x, y) Elements in x and not in y
setequal(x, y) Test if x and y are equal

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Set Operations
Examples
> example 1
> x <- 1:10
> y <- 6:15
> union(x, y)
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
> intersect(x, y)
[1] 6 7 8 9 10
> setdiff(x, y)
[1] 1 2 3 4 5
> setdiff(y, x)
[1] 11 12 13 14 15
> setequal(x, y)
[1] FALSE

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Logarithm
Description
log() computes the natural logarithm.
Syntax
log(x, base)
Returns
Logarithm of the specified base or the natural logarithm
Documentation
help(log)
help(exp)

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log()
Examples
> example 1
> log(10, base = 10)
[1] 1
> log(10, base = 2)
[1] 3.321928
> log(2.71828)
[1] 0.9999993
> # natural logarithm
> log(10)
[1] 2.302585
> # base 10
> log10(10)
[1] 1

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log()
Examples
> # base 2
> log2(10)
[1] 3.321928
> # exponential
> exp(3)
[1] 20.08554
> 2.71828 ^ 3
[1] 20.0855

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In the next module, we will explore selection statements in R:
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Next Steps...
● if()
● if else()
● ifelse()
● switch()

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R Programming: Mathematical Functions In R

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R Programming: Mathematical Functions In R