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getwd()
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gets working dir
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setwd("C:/file/path")
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set working dir
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help.start()
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open help
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install.packages("package")
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install package
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library("package")
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make content available
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detach("package")
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detach package
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x=read.csv(file.choose())
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import data
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ls()
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list the variables
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str(var)
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structure of variable
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rm(var)
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remove variable
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1D = array(1:24)
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1-D array
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2D=array(1:24,dim=c(6,4))
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2-D array
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3D=array(1:24,dim=c(4,3,2))
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3-D array
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matrix(1:12,nrow=4,ncol=3)
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matrix
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rbind/cbind(mat1,mat2)
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row/col bind
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t(mat)
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transpose
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rowMeans(data[])/ colMeans(data[])
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row/ column mean
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rowSums(data[])/ colSums(data[])
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row / column sum
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qplot(data, line=TRUE,...)
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produces quantile-quantile plot
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ggplot(data = NULL, mapping = aes(), ...)
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initializes a ggplot object
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geom_bar()
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bar graph
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coord_flip()
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flip x and y coordinates
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facet_grid()
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lay out panels in a grid
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geom_density/hist/point
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density/histogram/scatter plot
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toString(x)
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produces a single character string
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toupper()/tolower()
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converts to upper/lower case
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substring(chr,n,n)
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retrieves/replaces the substring
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paste (…, sep= " ", collapse=NULL)
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Convert to character + Concatenate
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num = c(1,2,3,4,5,6)
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numeric vector
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chr = c("aaa","bbb")
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character vector
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log = c(TRUE,TRUE,FALSE)
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logical vector
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mean(vec)
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mean
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sd(vec)
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standard deviation
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var(vec)
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variance
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range(vec)
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range
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which.min(vec)/which.max(vec)
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position of the min/max value
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rep(1:5,times=3)
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Replicate elements of vector
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rbinom(n, size, prob)
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Binomial
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rpois(n,size)
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Poisson
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runif(n, min = 0, max = 1)
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Uniform
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rnorm(n,mean,sd)
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Normal
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rexp(n)
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Exponential
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df = data.frame(subjectID=1:5,gender=c("M","F","M","M","F"),score=c(8,3,6,5,5))
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Created data frames in R
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fw = read.csv(file.choose())
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Importing data by choosing a file
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grass = read.csv('C:/Users/Downloads/grass.csv')
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Importing data by specifying paths
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view(df)
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opens editor
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|
rbind(a_data_frame, another_data_frame)
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Bind rows/ columns of frames
|
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merge(frame1, frame2, by = "x")
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Merge 2 data frames
|
|
summary(df)
|
returns descriptive statistics of data
|
|
if (condition){ Do something } else { Do something different }
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ifelse statement
|
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while (condition){ Do something }
|
while loop
|
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for (variable in sequence){ Do something }
|
for loop
|
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t.test(data)
|
1 sample t test
|
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t.test(data1,data2)
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2 sample t test
|
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t.test(pre,post,paired=TRUE)
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paired sample t test
|
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wilcox.test(data)
|
Wilcox test
|
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cor.test(data1,data2)
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correlation test
|
|
chisq.test(data)
|
Chi square test
|
|
shapiro.test(data)
|
Shapiro test
|
|
aov()
|
ANOVA
|
|
summary(lm(y ~ x1 + x2 + x3, data=mydata))
|
multiple regression
|
|
summary(glm(y ~ x1 + x2 + x3, family="", data=mydata))
|
classification
|
|
cluster = kmeans(data)
|
cluster analysis
|
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