ExpNumViz: Distributions of numeric variables

In SmartEDA: Summarize and Explore the Data

Distributions of numeric variables

Description

This function automatically scans through each variable and creates density plot, scatter plot and box plot for continuous variable using ggplot2 functions.

Usage

ExpNumViz(
  data,
  target = NULL,
  type = 1,
  nlim = 3,
  fname = NULL,
  col = NULL,
  Page = NULL,
  sample = NULL,
  scatter = FALSE,
  gtitle = NULL,
  theme = "Default"
)

Arguments

data	dataframe or matrix
target	target variable
type	1 (boxplot by category and overall), 2 (boxplot by category only), 3 (boxplot for overall)
nlim	numeric variable unique limit. Default nlim is 3, graph will exclude the numeric variable which is having less than 'nlim' unique value
fname	output file name
col	define the fill color for box plot. Number of color should be equal to number of categories in target variable
Page	output pattern. if Page=c(3,2), It will generate 6 plots with 3 rows and 2 columns
sample	random selection of plots
scatter	option to run scatter plot between all the numerical variables (default scatter=FALSE)
gtitle	chart title
theme	adding extra themes, geoms, and scales for 'ggplot2' (eg: themes options from ggthemes package)

Details

This function automatically scan each variables and generate a graph based on the user inputs. Graphical representation includes scatter plot, box plot and density plots.

All the plots are generated using ggplot2 pacakge function (geom_boxplot, geom_density, geom_point)

The plots are combined using gridExtra pacakge functions

• target is continuous then output is scatter plots

• target is categorical then output is box plot

• target is NULL then density plot for all numeric features

• scatter = TRUE generate multiple scatter plot between all the independent contionuos variables with or without group argument

Value

returns collated graphs in PDF or JPEG format

• Univariate plot density plot for all the numeric data with the value of shape of the distribution (Skewness & Kurtosis)

• Bivariate plot correlatin plot for all the numeric data

• Bivariate plot scatter plot between continuous dependent variable and Independent variables

• Box plot by overall sample

• Box plot by stratified sample

See Also

geom_boxplot ggthemes geom_density geom_point

Examples

## Generate Boxplot by category
ExpNumViz(iris,target = "Species", type = 2, nlim = 2,
           col = c("red", "green", "blue", "pink"), Page = NULL, sample = 2, scatter = FALSE,
           gtitle = "Box plot: ")
## Generate Density plot
ExpNumViz(iris, nlim = 2,
           col = NULL,Page = NULL, sample = 2, scatter = FALSE,
           gtitle = "Density plot: ")
## Generate Scatter plot by Dependent variable
ExpNumViz(iris,target = "Sepal.Length", type = 1, nlim = 2,
           col = "red", Page = NULL, sample = NULL, scatter = FALSE,
           gtitle = "Scatter plot: ", theme = "Default")
## Generate Scatter plot for all the numerical variables
ExpNumViz(iris,target = "Species", type = 1, nlim = 2,
           col = c("red", "green", "blue"), Page = NULL, sample = NULL, scatter = TRUE,
           gtitle = "Scatter plot: ", theme = "Default")

SmartEDA documentation built on Dec. 4, 2022, 1:15 a.m.