netCoin (version 2.1.0)

dichotomize: Dichotomize.

Description

This converts factor(s) o character(s) column(s) of a data frame into a set of dichotomous columns. Their names will correspond to the labels or text of every category.

Usage

dichotomize(data, variables,
            sep = "", min = 1, length = 0, values = NULL,
            sparse = FALSE, add = TRUE, sort = TRUE, nas = "None")

Value

A data frame composed by the original plus the added dichotmous columns.

Arguments

data

a data frame with a factor or textual column which can be simple (only one value for each scenario) or multiple if components are delinited with a separator.

variables

vector of column names that have to be converted into dichotomous vectors.

sep

vector of characters used to divide columns with multiple events. If this separator is "", every unique cell of every column is converted into a dichotomus data frame's column.

min

convert to dichotomous vectors only label or text that has a frequency less or equal to the value of this parameter. If the value of min is between 0 and 1, its value is interpreted as a percentage

length

maximum number of dichotomous columns generated for every variable

values

vector of labels or texts selected to their conversion to dichotomous columns

sparse

produce a sparse matrix instead of a data.frame

add

add the new columns to the input data.frame

sort

order the new columns by their frequencies

nas

variable name to convert the NA values of the set of variables

Author

Modesto Escobar, Department of Sociology and Communication, University of Salamanca, and Luis Martinez Uribe, Fundacion Juan March. See https://sociocav.usal.es/blog/modesto-escobar/

References

Escobar, M. and Martinez-Uribe, L. (2020) Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93, 1-32. tools:::Rd_expr_doi("10.18637/jss.v093.i11").

Examples

# A character column
frame1 <- data.frame(A = c("Man", "Women", "Man", "Undet."))
dichotomize(frame1, "A", sep = "; ")

# A character column (with separator)
frame2 <- data.frame(A = c("Man; Women", "Women; Women",
                         "Man; Man", "Undet.; Women; Man"))
dichotomize(frame2, "A", sep = "; ")

# A character column and another factor column (same sepatator)
frame3 <- data.frame(A = c("Man; Women", "Women; Women",
                         "Man; Man", "Undet.; Women; Man"),
                     C = factor(c(1:4), labels = c("Paris", "New York",
                         "London; New York", "")))
dichotomize(frame3, c("A", "C"), sep = "; ")

# A set of simple character or factor (same levels) variables. 
# In this case, you must use "C" separator.
frame4 <- data.frame(A = c("Man", "Women","Man", "Undet",NA),
                     B = c("Women","Women","Man","Women",NA),
					 C = c(NA,NA,NA,"Man",NA))
dichotomize(frame4,c("A","B","C"), sep="C")