| Title: | Counting Codes in a Text and Preparing Data for Analysis |
| Version: | 0.0.4.8 |
| Description: | Data analysis often requires coding, especially when data are collected through interviews, observations, or questionnaires. As a result, code counting and data preparation are essential steps in the analysis process. Analysts may need to count the codes in a text (Tokenization, counting of pre-established codes, computing the co-occurrence matrix by line) and prepare the data (e.g., min-max normalization, Z-score, robust scaling, Box-Cox transformation, and non-parametric bootstrap). For the Box-Cox transformation (Box & Cox, 1964, https://www.jstor.org/stable/2984418), the optimal Lambda is determined using the log-likelihood method. Non-parametric bootstrap involves randomly sampling data with replacement. Two random number generators are also integrated: a Lehmer congruential generator for uniform distribution and a Box-Muller generator for normal distribution. Package for educational purposes. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Imports: | stats |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2025-03-01 13:03:52 UTC; Cohard |
| Author: | Philippe Cohard [aut, cre] |
| Maintainer: | Philippe Cohard <p.cohard@laposte.net> |
| Repository: | CRAN |
| Date/Publication: | 2025-03-01 16:10:02 UTC |
BoxAndCox
Description
BoxAndCox
Usage
BoxAndCox(rawVect, minLambda)
Arguments
rawVect |
a vector |
minLambda |
a number |
Value
a list
Examples
vec=rlnorm(100, log(3), log(3))
BandC=BoxAndCox(vec, -3)
BandC
BAC=unlist(BandC$par)
BAC
rawVectBCFinal=unlist(subCalcBoxAndCox(vec, BandC$par))
BoxMullerGen
Description
BoxMullerGen
Usage
BoxMullerGen(r, s)
Arguments
r |
a number |
s |
a number |
Value
a vector
Examples
#with runif
v=BoxMullerGen(runif(1), runif(1))
print(v)
#with congruGen
seed = 123456789
X=c()
for(i in 1: 2) {
Z=congruGen(seed)
seed=Z$seedUpdate
X=append(X, Z$aleaNum)
}
#print(X)
N=BoxMullerGen(X[1], X[2])
print(N[1])
print(N[2])
analysCodesList
Description
analysCodesList
Usage
analysCodesList(dataS, codesLis)
Arguments
dataS |
a character |
codesLis |
a character |
Value
a list
Examples
codes=list("@essai@","@test@")
data = "this is an example @essai@, a bit long @essai@ text"
Result=analysCodesList(data,codes)
Result
bootStrap
Description
bootStrap
Usage
bootStrap(nameDframe, grpSize)
Arguments
nameDframe |
a data.frame |
grpSize |
a number |
Value
a matrix
Examples
j=c(10,14,56,30,58,78,99,1)
k=c(10,12,14,16,18,20,22,24)
x=data.frame(j,k)
res=bootStrap(x,5)
res
codeCount
Description
codeCount
Usage
codeCount(dataSet, code)
Arguments
dataSet |
a character |
code |
a character |
Value
a number
Examples
data = "this is an example @essai@"
codeCount(data, "@essai@") #number of lines containing the chain
congruGen
Description
congruGen
Usage
congruGen(seed, a)
Arguments
seed |
a number |
a |
a number |
Value
a list
Examples
seed = 123456789
for(i in 1: 10) {
Z=congruGen(seed)
seed=Z$seedUpdate
num=Z$aleaNum
print(num)
}
cooc
Description
cooc
Usage
cooc(lines, code1, code2)
Arguments
lines |
character |
code1 |
character |
code2 |
character |
Value
an integer
Examples
lines ="Companies can boost responsiveness @performance@ by digital @digital@."
code1 = "@performance@"
code2 = "@digital@"
res=cooc(lines, code1, code2)
print(res)
loadCodes
Description
loadCodes
Usage
loadCodes(txtFile)
Arguments
txtFile |
a character |
Value
a list
Examples
theFile =system.file("codesList.txt", package = "codecountR")
data=loadCodes(theFile)
normMinMax
Description
normMinMax
Usage
normMinMax(nameDframe)
Arguments
nameDframe |
a data.frame |
Value
a data.frame
Examples
j=c(10,14,56,30,58,78,99,1)
k=c(10,12,14,16,18,20,22,24)
x=data.frame(j,k)
xMinMax=normMinMax(x)
xMinMax
robustScal
Description
robustScal
Usage
robustScal(nameDframe)
Arguments
nameDframe |
a data.frame |
Value
a data.frame
Examples
j=c(10,14,56,30,58,78,99,1)
k=c(10,12,14,16,18,20,22,24)
x=data.frame(j,k)
xRsc=robustScal(x)
xRsc
subCalcBoxAndCox
Description
subCalcBoxAndCox
Usage
subCalcBoxAndCox(sortedVect, actualLambda)
Arguments
sortedVect |
a vector |
actualLambda |
a number |
Value
a vector
Examples
vec=rlnorm(100, log(3), log(3))
BandC=subCalcBoxAndCox(vec, -3)
testPairs
Description
testPairs
Usage
testPairs(listCodes, lines)
Arguments
listCodes |
character |
lines |
character |
Value
a list
Examples
#Co-occurrences computed line by line in the file. Structure the file accordingly.
#Multiple identical pairs on one line count as one unit.
lines =c("Companies can boost responsiveness @performance@ by digital @digital@.",
"softwares @digital@ may reduce response time @performance@ improving @satisfaction@.")
listCodes=c("@satisfaction@", "@digital@", "@performance@")
coocurences = testPairs(listCodes, lines)
print(coocurences$matrix)
#save to file
#nameFile = paste("CooccurrenceMatrix_",format(Sys.time(),"%d_%m_%Y-%Hh%Mm%Ss"),".csv",sep = "")
#write.csv(coocurences$matrix, nameFile, row.names = TRUE)
tokenization
Description
tokenization
Usage
tokenization(txtFile)
Arguments
txtFile |
a character |
Value
a list
Examples
theFile =system.file("ExText.txt", package = "codecountR")
data=tokenization(theFile)
verify
Description
verify
Usage
verify(lines, code1, code2)
Arguments
lines |
character |
code1 |
character |
code2 |
character |
Examples
lines ="Companies can boost responsiveness @performance@ by digital @digital@."
code1 = "@performance@"
code2 = "@digital@"
verify(lines,code1,code2)
zScore
Description
zScore
Usage
zScore(nameDframe)
Arguments
nameDframe |
a data.frame |
Value
a data.frame
Examples
j=c(10,14,56,30,58,78,99,1)
k=c(10,12,14,16,18,20,22,24)
x=data.frame(j,k)
xZsc=zScore(x)
xZsc