linkspotterUI: Linkspotter user interface runner

In linkspotter: Bivariate Correlations Calculation and Visualization

Description

Build the Linkspotter user interface

Usage

linkspotterUI(
  dataset,
  corDF,
  variablesClustering = NULL,
  defaultMinCor = 0.3,
  appTitle = "Linkspotter",
  htmlTop = "",
  htmlBottom = "",
  ...
)

Arguments

dataset	the dataframe which variables bivariate correlations are contained in corDF
corDF	a specific dataframe containing correlations values resulting from the function multiBivariateCorrelation()
variablesClustering	a specific dataframe containing the output of the variable clustering resulting from the function clusterVariables()
defaultMinCor	a double between 0 and 1. It is the minimal correlation absolute value to consider for the first graph plot.
appTitle	a character 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.
...	: arguments for 'shiny::shinyApp' function

Value

a 'shiny.appobj' object enable to deploy instantly the user interface for a customizable visualization.

Examples

# calculate a correlation dataframe
data(iris)
corDF=multiBivariateCorrelation(dataset = iris)
corMatrix=corCouplesToMatrix(x1_x2_val = corDF[,c('X1','X2',"MaxNMI")])
corGroups=clusterVariables(corMatrix = corMatrix, nbCluster = 3)
## Not run: 
# launch the UI
linkspotterUI(dataset=iris, corDF=corDF, variablesClustering=corGroups,
defaultMinCor=0.3,cappTitle="Linkspotter on iris data",
options = list(port=8000)
)

## End(Not run)

linkspotter documentation built on July 23, 2020, 5:08 p.m.