multiBivariateCorrelation: Calculation of all the bivariate correlations in a dataframe

In linkspotter: Bivariate Correlations Calculation and Visualization

Description

Computation of a correlation dataframe.

Usage

multiBivariateCorrelation(
  dataset,
  targetVar = NULL,
  corMethods = c("pearson", "spearman", "kendall", "mic", "MaxNMI"),
  maxNbBins = 100,
  showProgress = T
)

Arguments

dataset	the dataframe which variables bivariate correlations are to be analyzed.
targetVar	a vector of character strings corresponding to the names of the target variables. If not NULL, correlation coefficients are computed only with that target variables.
corMethods	a vector of correlation coefficients to compute. The available coefficients are the following : c("pearson","spearman","kendall","mic","distCor","MaxNMI"). It is not case sensitive and still work if only the beginning of the word is put (e.g. pears).
maxNbBins	an integer used if corMethods include 'MaxNMI'. It corresponds to the number of bins limitation (for computation time limitation), maxNbBins=100 by default.
showProgress	a boolean to decide whether to show the progress bar.

Value

a specific dataframe containing correlations values or each specified correlation coefficient.

Examples

# run linkspotter on iris example data
data(iris)
corDF<-multiBivariateCorrelation(iris)
print(corDF)

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