DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface List of Figures List of Tables Process . Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Conditional Trees Decision Trees Hierarchical Clustering Kernel Methods K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products Borgelt Data Mining Suite R Rattle Weka Closed Products C4.5 Clementine Enterprise Miner Equbits Foresight GhostMiner InductionEngine ODM Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Numbers

Numbers in R can be integer, double, or complex. The actual type is generally determined by R based on context and defaults. Numbers do tend to be double unless they are in some way restricted to being integers, or you wish to store complex numbers.

> typeof(1) 	    # "double"
> typeof(1.3)       # "double"
> typeof(1:2)       # "integer" - this is a vector of two integers 1 and 2
> typeof((1:2)[1])  # "integer" - this is the first element of the vector
> typeof(2+5i)	    # "complex" - complex numbers have real and imaginary parts

The basic numeric operators include:

	Addition		Subtraction		Multiplication		Division
^	Exponentiation	:	Sequence	%/%	Integer division	%%	Remainder

See the documentation for Arithmetic for details:

> ?Arithmetic

> 1 : 5    # 1 2 3 4 5

Typical numeric functions include:

> round(1234.56)	# 1235
> trunc(1234.56)	# 1234

Brought to you by Togaware.