By Mike Allerhand (auth.)
This short offers a roadmap for the R language and programming atmosphere with signposts to extra assets and documentation.
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Additional resources for A Tiny Handbook of R
The quantile function is useful for calculating breaks so that the intervals will contain equal frequencies of values. numeric levels nlevels :, interaction Make a factor from a vector Make an ordered factor from a vector Make a factor by generating (equal sized) levels Make a factor by cutting a vector at given break points Set the first (reference) level of a factor Get a factor’s numeric codes Get the labels of a factor’s levels Get the number of levels of a factor Cross-classify factors Arithmetic operators are not valid for factors.
Any operation involving NA is undecidable and so the only sensible result is NA. Descriptive functions by default will propagate NA values rather than a potentially incorrect summary. na is needed to test for NA. The function returns TRUE where its argument is NA. cases is provided for testing for NA along data frame rows. Other functions provide arguments to accommodate NA. 4 Handling Missing Values Cases with missing values can be dropped altogether: [ dat ¼ dat½complete:casesðdatÞ; # Drop cases ðrowsÞ with any NA It is possible to impute40 values that are missing.
They are not defined for character data. They are defined for logical data by treating logical values as numeric in an arithmetic context as: TRUE=[1 and FALSE=[0. Consequently the sum function counts TRUE in a logical vector, and the mean function calculates the proportion TRUE. This enables descriptive functions to summarise how a vector meets a given condition. For example [ x ¼ cð2; 4; 6; 8; 10Þ [ y ¼ cð"apple"; "apple"; "orange"; "apple"; "orange"Þ [ sumðxÞ [ sumðyÞ # Sum of the elements of x # Error!