regression_impact: Create boxplot standardize with IMPACT style

In sharonorengo/visualisationIMPACT: Functions for different type of output (visualisation)

Description

Create boxplot standardize with IMPACT style

Usage

regression_impact(.data, x, y, weight = NULL)

Arguments

.data:	data that contains the statistical result to build boxplots
x:	element of .data that contains the different values of the categorical data
name.y:	name of value calculated
median:	element of .data containing the median values
first_quantile:	element of .data containing lower hinges correspond to the first quartile
third_quantile:	element of .data containing upper hinges correspond to the third quartile
whisker_min:	element of .data containing the value of the lower whisher. Usually calculated as 1.5*IQR smallest value from the hinge
whisker_max:	element of .data containing the value of the upper whisher. Usually calculated as 1.5*IQR largest value from the hinge
outlier_min	(optional): element of .data containing the most extreme value beyond the lower whisper.
outlier_max	(optional): element of .data containing the most extreme value beyond the upper whisper.
sens.boxplot	(optional): if sens.boxplot = "vertical" (default) boxplots are build with vertical cartesian coordinates. If sens.boxplot="horizontal" flip cartesian coordinates so that vertical becomes horizontal

Details

Create a plot with one or multiple boxplot standardize with IMPACT colors, fonts, ... for the same numerical variable

Value

a ggplot object contaning a boxplot

sharonorengo/visualisationIMPACT documentation built on Aug. 12, 2019, 3:34 p.m.