Extract columns from the raw text

This is the main extractor for the Endoscopy and Histology report. This relies on the user creating a list of words representing the subheadings. The list is then fed to the Extractor so that it acts as the beginning and the end of the regex used to split the text. Whatever has been specified in the list is used as a column header. Column headers don't tolerate special characters like : or ? and / and don't allow numbers as the start character so these have to be dealt with in the text before processing

Usage

Extractor(inputString, delim)

Arguments

inputString

the column to extract from

delim

the vector of words that will be used as the boundaries to extract against

See also

Other NLP - Text Cleaning and Extraction: ColumnCleanUp(), DictionaryInPlaceReplace(), NegativeRemoveWrapper(), NegativeRemove(), textPrep()

Examples

# As column names cant start with a number, one of the dividing
# words has to be converted
# A list of dividing words (which will also act as column names)
# is then constructed
mywords<-c("Hospital Number","Patient Name:","DOB:","General Practitioner:",
"Date received:","Clinical Details:","Macroscopic description:",
"Histology:","Diagnosis:")
Mypath2<-Extractor(PathDataFrameFinal$PathReportWhole,mywords)