# Intro # This video is a quick and easy overview of the R programming language. # We'll look at setting up our environment and go through the basic commands. # - R is a programming language and software environment for statistical computing and graphics. # - It is free and open source. It first appeared in 1993 and has gone through number of releases. # - Today R is widely used for data analysis among statisticians and data scientists. # RStudio # RStudio is a free environment for R scripting. You can download RStudio at https://www.rstudio.com/. # RStudio workspace consists of 4 panes: # 1. Source pane for viewing and writing R scripts # 2. Console pane for live coding # 3. Environment/History pane for exploring active variables or viewing older commands # 4. Files/Plots/Packages/Help pane for viewing plots and help and exploring files or packages #Arithmetics x=10 y=2 x+y x-y x*2 x/y x^y #power x**y #power x%%y #remainder from division # Relational operators x=10 y=2 xy x<=y x>=y x==y x!=y # Math functions abs(x) #Takes the absolute value of x log(x,base=y) #Takes the logarithm of x with base y; if base is not specified, returns the natural logarithm exp(x) # Returns the exponential of x sqrt(x) # Returns the square root of x # Help on functions help(log) # Datasets and basic commands iris # We usually work with objects of class data.frame, a table look-alike with columns and rows class(iris) # Dimension dim(iris) # Column names names(iris) # First 6 rows of dataframe head(iris) # Specifying number of first rows head(iris, 10) # Last 6 rows of dataframe tail(iris) # Specifying number of last rows tail(iris, 3) # Descriptive statistics summary(iris) min(iris$Sepal.Length) max(iris$Sepal.Length) range(iris$Sepal.Length) mean(iris$Sepal.Length) median(iris$Sepal.Length) mode(iris$Sepal.Length) sd(iris$Sepal.Length) quantile(iris$Sepal.Length) # Point plot library(ggplot2) ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) + geom_point() # Add colors to groups ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, colour = Species)) + geom_point() # Histogram ggplot(iris, aes(x = Sepal.Length)) + geom_histogram() # Add colors to groups ggplot(iris, aes(x = Sepal.Length, fill = Species)) + geom_histogram() # Boxplot ggplot(iris, aes(x = Species, y = Sepal.Length)) + geom_boxplot() # Saving images ggsave(filename = "my_ggplot.png", path = "C:/temp")