Description Usage Arguments Value Examples
View source: R/linkspotterOnFile.R
This function imports an external dataset, computes its correlation matrices, variable clustering and the customizable user interface to visualize them using a graph.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 | linkspotterOnFile(
  file,
  corMethods = c("pearson", "spearman", "kendall", "mic", "MaxNMI"),
  defaultMinCor = 0.3,
  defaultCorMethod = corMethods[length(corMethods)],
  clusteringCorMethod = corMethods[length(corMethods)],
  nbCluster = 1:9,
  printInfo = T,
  appTitle = "Linkspotter",
  htmlTop = "",
  htmlBottom = "",
  ...
)
 | 
| file | the file containing a structured dataset which the bivariate correlations are to be analyzed. | 
| corMethods | a vector of correlation coefficients to compute. The available coefficients
are the following :  | 
| defaultMinCor | a double between 0 and 1. It is the minimal correlation absolute value to consider for the first graph plot. | 
| defaultCorMethod | a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the first graph plot. | 
| clusteringCorMethod | a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the variables clustering. | 
| nbCluster | an integer. It is the number of clusters to compute. | 
| printInfo | a boolean indicating whether to print on the console some information about the dataset and the estimated computation time. | 
| appTitle | a string taken as the title of the user interface. | 
| htmlTop | a character string that enable to customize your shiny app by adding an HTML code in the HEAD tag. | 
| htmlBottom | a character string that enable to customize your shiny app by adding an HTML code at the end of the BODY tag. | 
| ... | Further arguments to be passed to the used read.csv function. | 
a list containing all the material enabling to analyze correlations:
computationTime: a string
run_it: a shiny.appobj object enable to deploy instantly the user interface
for a customizable visualization.
dataset: the initial dataset
corDF: a the correlation data.frame including values for all coefficients
corMatrices: a list of correlation matrices
corGroups: data.frame a data.frame list
clusteringCorMethod: a character
defaultMinCor: a numeric
defaultCorMethod: a string
corMethods: vector of strings
| 1 2 3 4 5 6 7 8 9 10 11 | # run linkspotter on iris example data
data(iris)
tmpCSV<-tempfile(fileext = '.csv')
write.csv(iris, tmpCSV, row.names = FALSE)
lsOutputIrisFromFile<-linkspotterOnFile(file=tmpCSV)
summary(lsOutputIrisFromFile)
## Not run: 
# launch the UI
lsOutputIrisFromFile$launchShiny(options=list(port=8000))
## End(Not run)
 | 
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