R Notebook

library(dplyr)

filter()

Data = iris
Data_mean = mean(Data$Sepal.Length)
Report = filter(.data = Data, Species == "versicolor", Sepal.Length > Data_mean)
head(Report)

arrange()

Data = iris
Report = arrange(.data = Data, desc(Sepal.Length), Sepal.Width)
head(Report)

select()

Select columns by name

data = iris
Report = select(data, Sepal.Length,Petal.Width)
head(Report)

Select all columns between Columns (inclusive)

data = iris
Report = select(data, -(Sepal.Length:Petal.Width))
head(Report)

Select all columns except

data = iris
Report = select(data, -(Sepal.Length:Petal.Width))
head(Report)

Select with Renaming Columns

data = iris
Report = select(data, Species = Species)
head(Report)

Helper Functions

• starts_with()
  • ends_with()
  • matches()
  • contains()

data = iris
Report = select(data, starts_with("Petal"))
head(Report)

summarize()

Data = iris
Report = summarize(.data = Data, "Sepal Width Mean" = mean(Sepal.Width), "Sepal Length Mean" = mean(Sepal.Width))
head(Report)

mutate()

Data = iris
m = mean(Data$Sepal.Length)
s = sd(Data$Sepal.Length)
Report = mutate(.data= Data, Normalize = (Sepal.Length-m)/s)
head(Report)

NA

transmute()

Data = iris
m = mean(Data$Sepal.Length)
s = sd(Data$Sepal.Length)
Report = transmute(.data= Data, Normalize = (Sepal.Length-m)/s)
head(Report)

groupby()

Data = iris
Grouping = group_by(.data = Data,Species)
Summary = summarise(Grouping, count = n(),"Mean"= mean(Sepal.Length),"Standard Deviation"=sd(Sepal.Length) )
Summary