eda: Automated exploratory data analysis
In XanderHorn/lazy: Automated data pre-processing and machine learning

Explores a provided data set and returns a list of plots per feature as well as a summary table.

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eda(data, x = NULL, y = NULL, sample.size = 0.5, theme = 1,
  numeric.plot = "histogram", categorical.plot = "bar",
  pipeline = NULL)

`data`	[required \| data.frame ] Dataset to visualize.
`x`	[optional \| character \| default=NULL] Features to visualize specified as a character vector. If NULL then all features in the dataset will be used except for the target feature.
`y`	[optional \| character \| default=NULL] Target feature to visualize. If NULL a univariate visialization will take place.
`sample.size`	[optional \| numeric \| default=0.5] Sample size to down sample the data for faster exploration.
`theme`	[optional \| numeric \| default=1] Color theme applied to plot, options range from 1 to 4.
`numeric.plot`	[optional \| character \| default="histogram"] The type of plot to be produced. For numeric feature types histogram, density, boxplot and violin are available.
`categorical.plot`	[optional \| character \| default="bar"] The type of plot to be produced. For categorical bar and stackedbar are available.
`pipeline`	[optional \| list \| default=NULL] Pipeline used to pre-process the data for visualization. If NULL then a exploratory pipeline will be produced to pre-process the data.