Procedure 2: Extracting a substring from a string, testing logically and presenting for machine learning

In Horizontal Abstraction, it is quite common to have the requirement to inspect a string of data looking for an occurrence (or pattern) and return a logical value that can be used in machine learning.

In this example, a string will be inspected and return a 1 in the event that the string “Richard” is present.

Firstly, create a vector of name strings by typing:

Names <- c("Richard","Robert","Reinhard","Raymond","Richardino","Richardo")

Run the line of script to console:

Use the substr() function to create a vector of the first 7 characters of the value contained in the Names vector, by typing:

NamesSubstr <= substr(Names,1,7)

Write the NamesSubstr vector:

NamesSubstr

Run the line of script to console:

The question being posed is whether the first characters of the name is equal to “Richard”. To perform this evaluation, create a logical vector from the NamesSubstr vector by typing:

NamesSubstrLogical <- NamesSubstr == "Richard"

Notice how a double equals sign is used to eliminate confusion between evaluation and assignment.

Run the line of script to console:

Write the logical vector out to console by typing:

NamesSubstrLogical

Run the line of script to console:

The character notion of TRUE or FALSE cannot be used in machine learning readily (you can’t multiply by text) and it follows that these values should be converted to a numeric value using the as.numeric() function, typing:

NamesSubstrLogicalNumeric <- as.numeric(NamesSubstrLogical)

Run the line of script to console:

Write the newly created vector to console by typing:

Run the line of script to console:

A more concise line of script nesting the functions might be:

NamesSubstrLogicalNumericNested <- as.numeric(substr(Names,1,7) == "Richard")

An alternative approach might be converting the logical vector to a factor as explained elsewhere.