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getwd()
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gets the working directory
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setwd("C:/file/path")
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sets the working directory
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data = read.csv(file.choose())
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opens file explorer to get data
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ls()
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lists the variables
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str(var)
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structure of the variable
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rm(var)
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removes the variable
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help.start()
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opens help
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install.packages("package name")
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installs the package
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library("package name")
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makes the contents available to use
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detach("package name")
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detaches the package
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toString(x)
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helper function to produce a single character string
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toupper()/tolower()
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converts text to upper/lower case
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substring(chr,n,n)
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retrieve or replaces the substring of the charachter
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paste (…, sep = " ", collapse = NULL)
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Concatenate vectors after converting to character
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1D = array(1:24)
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1 dimensional array
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2D = array(1:24, dim = c(6,4))
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2 dimensional array
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3D = array(1:24, dim = c(4,3,2))
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3 dimensional array
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mat = matrix(1:12, nrow=4, ncol=3)
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matrix
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cbind(mat1,mat2)
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column bind
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rbind(mat1,mat2)
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row bind
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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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df = data.frame(subjectID=1:5,gender=c("M","F","M","M","F"),score=c(8,3,6,5,5))
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dataframe
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view(df)
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opens editor
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head(df)/tail(df)
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displays top/bottom n rows
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summary(df)
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returns descriptive statistics of data
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rowMeans(data[])
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row mean
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rowSums(data[])
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row sum
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colMeans(data[])
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column mean
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colSums(data[])
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column sum
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for (variable in sequence){ Do something }
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for loop
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while (condition){ Do something }
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while loop
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if (condition){ Do something } else { Do something different }
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ifelse statement
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t.test(data)
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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)
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Wilcox test
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cor.test(data1,data2)
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correlation test
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chisq.test(data)
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Chi square test
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shapiro.test(data)
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Shapiro test
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aov()
|
ANOVA
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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
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density plot
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geom_hist
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histogram
|
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geom_point
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scatter plots
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rbinom(n, size, prob)
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Binomial distribution
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rpois(n,size)
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Poisson distribution
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runif(n, min = 0, max = 1)
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Uniform distribution
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rnorm(n,mean,sd)
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Normal distribution
|
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rexp(n)
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Exponential distribution
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summary(lm(y ~ x1 + x2 + x3, data=mydata))
|
multiple regression
|
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summary(glm(y ~ x1 + x2 + x3, family="", data=mydata))
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classification
|
|
cluster = kmeans(data)
|
kmeans cluster analysis
|
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