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R Intro Code.R
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R Intro Code.R
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# Introduction to R Workshop Code
# -----------------------------------------
# Creating Values and vectors
a <- 4
b <- 5
x <- c(1:5)
x2 <- c(1,4,7,3,8)
# We can combine these two vectors into a data set using cbind
dat <- cbind(x, x2)
View(dat)
# -----------------------------------------
# Arithmetic Operators
# This code will run fine without using the assign arrow, but because we are not telling R where to put the results, it will just print it
# in the command line. If we specify the name of the object that we want R to creat (ex. Addition), it will store the output as an object
# of that name.
(a + b)
Addition <- (a + b)
Subtraction <- (a - b)
Multiplication <- (a * b)
Division <- (a / b)
Exponentiation <- (a ^ b)
# -----------------------------------------
# Logical Operators
# Logical operators work like questions where you give R a statement and it evaluates if it is True or False
(a < b)
Lesser <- (a < b)
Lesser.Equal <- (a <= b)
Greater <- (a > b)
Greater.Equal <- (a >= b)
(a = b)
Exact.Equal <- (a == b)
Not.Equal <- (a != b)
# -----------------------------------------
# Changing the Working Directory - Example
# -----------------------------------------
# Reading in Data from a raw url file from github
My.Data <- read.csv("https://raw.githubusercontent.com/PrisonRodeo/PLSC504-2018-git/master/Data/Beer.csv", header = TRUE)
# -----------------------------------------
# Renaming or Creating a new dataset
New.Data <- My.Data
# -----------------------------------------
# Checking the names of the variables in your dataset
names(New.Data)
# -----------------------------------------
# Viewing Data
View(New.Data)
#You can also double click the dataset name in the environment
# -----------------------------------------
# Creating a New variable
New.Data$ABV.Per.Dollar <- New.Data$alcohol/New.Data$price
# -----------------------------------------
# Deleting a Variable
New.Data$ABV.Per.Dollar <- NULL
# -----------------------------------------
# Useful R commands - adapted from http://www.sr.bham.ac.uk/~ajrs/R/r-function_list.html
# Math
log() # natural log
exp()
sqrt()
sum()
#general
length(x) # Return no. of elements in vector x
range(x) # Returns the minimum and maximum of x
ls() # List objects in current environment
cbind() # Combine vectors by row/column
abs(x) # The absolute value of "x"
seq(1,10,0.4) # Generate a sequence (1 -> 10, spaced by 0.4)
sign(x) # Returns the signs of the elements of x
sort(x) # Sort the vector x
order(x) # list sorted element numbers of x
options() # Set options to control how R computes & displays results
view(My.Data) # View dataset
# Graphics
help(package=graphics) # List all graphics functions
plot() # Generic function for plotting
barplot() # Produces a bar plot
par() # Set or query graphical parameters
points(x,y) # Add another set of points to an existing graph
abline() # Adds a straight line to an existing graph
lines() # Join specified points with line segments
hist(x) # Plot a histogram of x
# Statistics
help(package=stats) # List all stats functions
cor.test() # Perform correlation test
cumsum(); cumprod(); cummin(); cummax() # Cumuluative functions for vectors
density(x) # Compute kernel density estimates
loess(); lowess() # Scatter plot smoothing
mad() # Calculate median absolute deviation
mean(x); weighted.mean(x); median(x); min(x); max(x); quantile(x)
rnorm(); runif() # Generate random data with Gaussian/uniform distribution
sd() # Calculate standard deviation
summary(x) # Returns a summary of x: mean, min, max etc.
t.test() # Student's t-test
var() # Calculate variance
sample() # Random samples & permutations
qqplot() # quantile-quantile plot
# -----------------------------------------
# Installing Packages
install.packages("Amelia")
# -----------------------------------------
# Looking up function documentation
?mean
# -----------------------------------------
# Looking up vignettes
vignette()
vignette("amelia", package = "Amelia", lib.loc = NULL, all = TRUE)
# -----------------------------------------
# Clearing Out the Environment