lessR (version 2.5)

Recode: Recode the Values of an Integer or Factor Variable

Description

Abbreviation: rec

Recodes the values of one or more integer or factor variables in a data frame, by default mydata. The factor variable represents categorical data. The values of the factor are entered as character strings. The values of the original variable may be overwritten with the recoded values, or the recoded values can be designated to be placed in a new variable, indicated by the new.name option. Valid values may be converted to missing, and missing values may be converted to valid values.

There is no provision to recode integer values to character strings because that task is best accomplished with the standard R factor function.

Usage

Recode(old.vars, new.vars=NULL, old, new, dframe=mydata, brief=FALSE)
rec(...)

Arguments

old.vars

One or more variables to be recoded.

new.vars

Name of the new variable or variables that contain the recoded values. If not provided, then the values of the original variable are replaced.

old

The values of the variables that are to be recoded. If the value is "missing" then any existing missing values are replaced by the value specified with new.

new

The recoded values, which match one-to-one with the values in old. If the value is "missing" then instead any values specified in old are converted to missing.

dframe

The name of the data frame that contains the variable with values to be recoded, which is mydata by default.

brief

If TRUE, then less output is provided.

...

Parameter values.

Details

Specify the values to be recoded with the required old parameter, and the corresponding recoded values with the required new parameter. Use new.name to specify the name of the variable that contains the recoded values. If new.name is not present, then the values of the original variable are overwritten with the recoded values.

A set of variables or values can be listed using the colon notation, such as Years:Salary for variables, which specifies the variables from Years to Salary in the data frame, or 0:5 for values, which specifies the integers 0, 1, 2, 3, 4, 5. To specify a list of multiple variables or values, or sets of variables or values, separate each set of variables or values by a comma, then invoke the R combine or c function. For example, if the values in the list of old values is from 0 to 5, and 10, then define the list according to old=c(0:5,10).

Not all of the existing values of the variable to be recoded need be specified. Any value not specified is unchanged in the values of the recoded variable. Unless otherwise specified, missing values are unchanged. To modify missing values, set old="missing" to covert missing data values to the specified value data value given in new. Or, set new="missing" to covert the one or more existing valid data values specified in old to missing data values.

Two diagnostic checks are performed before the recode. First, it is verified that the same number of values exist in the old and new lists of values. Second, it is verified that all of the values specified to be recoded in fact exist in the original data.

See Also

transform, factor.

Examples

# construct data frame
mydata <- read.table(text="Severity Description
1 Mild
4 Moderate
3 Moderate
2 Mild
1 Severe", header=TRUE)

# recode Severity into a new variable called SevereNew
Recode(Severity, new.vars="SevereNew", old=1:4, new=c(10,20,30,40))

# abbreviated form,  replace original with recoded
# another option, the sequence function, to generate list of values
rec(Severity, old=1:4, new=seq(10,40,by=10))

# construct data frame
# recode Description, leave original variable unmodified
Recode(Description, new.vars="DescribeNew",
       old=c("Mild", "Moderate", "Severe"), new=c("M", "O", "S"))

# data in a different data frame than mydata
data(datEmployee)
Recode(Gender, old=c("F","M"), new=c("Female","Male"), dframe=datEmployee)

# reverse score four Likert variables: m01, m02, m03, m10 
data(datMach4)
Recode(c(m01:m03,m10), old=0:5, new=5:0, dframe=datMach4)

# for four Likert variables, convert any 0 or 1 to missing
data(datMach4)
Recode(c(m01:m03,m10), old=0:1, new="missing", dframe=datMach4)

# for four Likert variables, convert any missing value to 99
data(datMach4)
Recode(c(m01:m03,m10), old="missing", new=99, dframe=datMach4)