# R code for chapter 44 manipulating variables (columns) in R Commander and R
# Book details:
# Health Science Statistics using R and R Commander
# by Robin Beaumont
# Paperback - ISBN 9781907904318
# http://www.amazon.co.uk/Health-Science-Statistics-using-Commander/dp/190790431X
# or direct from publisher at: 
# http://www.scionpublishing.com/
# book website: http://www.robin-beaumont.co.uk/rbook
###########################################################
# 
var1<- c(2,4,3,5,6,5,6,4,NA,1)
var2<- c(2,5,4,5,6,2,3,4,NA,3)
mydataframe <- data.frame(var1, var2)

# Recoding a variable, changing all 5's to 10's:
# into a new factor
 mydataframe$newvar <- Recode(mydataframe$var1, '5 =10',  as.factor.result=TRUE)
 # into a new variable NOT a factor:
mydataframe$newvar <- Recode(mydataframe$var1, '5 =10',  as.factor.result=FALSE)
# changing the values in a variable to a calculated value
mydataframe$var1_squared <- with(mydataframe, var1^2)

# creating standardised variables:
# a single variable:
mydataframe$Zvar1 <- scale(mydataframe$var1)
# if you have a dataframe with only numeric variables you can allpy the
# scale() function to it en masse otherwise you get an error:
newdata_scaled <- scale(mydataframe)

# 1.4	Converting numeric variable(s) to factors with level values
# converting a variable to a factor:
mydataframe$var1factor <- as.factor(mydataframe$var1)
mydataframe

# 1.5	Converting numeric variable(s) to factors with level names
mydataframe$var1factor2 <- factor(mydataframe$var1,  labels=c('red','yellow','green','blue','brown','black'))

# 1.6	Which of my variables are factors? 
str(mydataframe)

# 1.7	Converting and grouping a numeric variable to a factor with level values: 'binning'
# 1.8	Reorder factor levels 

mydataframe$var1factor_reorder <- factor(mydataframe$var1factor, 
  levels=c('2','1','3','4','6','5'))

mydataframe$var1factor_ordered <- factor(mydataframe$var1factor, 
levels=c('2','1','3','4','6','5'), ordered=TRUE)

# 1.9	Renaming one or more variables
names(mydataframe)[c(4,6)] <- c("squared","factored")

# 1.10	 Deleting one or more variables
mydataframe$var1factor_ordered <- NULL

##### end