textual: Text mining

In FactoMineR: Multivariate Exploratory Data Analysis and Data Mining

Text mining

Description

Calculates the number of occurence of each words and a contingence table

Usage

textual(tab, num.text, contingence.by=1:ncol(tab), 
    maj.in.min = TRUE, sep.word=NULL)

Arguments

tab	a data frame with one textual variable
num.text	indice of the textual variable
contingence.by	a list with the indices of the variables for which a contingence table is calculated by default a contingence table is calculated for all the variables (except the textual one). A contingence table can also be calculated for couple of variables. If contingence.by is equal to num.text, then the contingence table is calculated for each row of the data table
maj.in.min	boolean, if TRUE majuscule are transformed in minuscule
sep.word	a string with all the characters which correspond to separator of words

Value

Returns a list including:

cont.table	the contingence table with in rows the categories of the categorical variables (or the couple of categories), and in column the words, and in each cell the number of occurence
nb.words	a data.frame with all the words and for each word, the number of lists in which it is present, and the number of occurence

Author(s)

Francois Husson [e-mail]

See Also

CA, descfreq

Examples

data(poison.text)
res.text <- textual(poison.text, num.text = 3, contingence.by = 1)
descfreq(res.text$cont.table)
## Contingence table for the couple of variable sick-sex
res.text2 <- textual(poison.text, num.text = 3, contingence.by = list(c(1,2)))
descfreq(res.text2$cont.table)
## Contingence table for sex, sick and the couple of variable sick-sex
res.text2 <- textual(poison.text, num.text = 3, contingence.by = list(1,2,c(1,2)))

FactoMineR documentation built on May 29, 2024, 3:36 a.m.