Tutorial: 2.2. Create Plots

The main feature of the package is to create different kinds of plots. These can roughly be devided into four groups:

• Measure plots
• List plots
• Parameter plots
• Tuning plots

Following list gives an overview about all implemented plots and their corresponding group.

Measure Plot	List Plot	Parameter Plot	Tuning Plot
Box Plot	Box Plot	Box Plot
Scatter Plot	Scatter Plot	Scatter Plot
Density Plot	Density Plot	Density Plot
Dual Measure Plot	Dual Measure Plot	Dual Plot
Measure Matrix Plot	Measure Matrix Plot	Measure Matrix Plot
Density Rank Plot	Density Rank Plot
Rank Matrix Bar Plot	Rank Matrix Bar Plot
	Line Plot		Line Plot
Summary Plot
Parallel Coordinates Plot
Radar Plot
Rank Plot
Bar Plot

There is no guarantee that the list provided above is up to date. To see a full list with all possible charts use the method:

listPlots()

If you just want to get a list with the plots that are usable with your input data table use:

getValidPlots(data.table)

Create Plot

The creation of a benchmark visualization is pretty simple. Examples:

createBarPlot(table, "measure")
createListLinePlot(table, "list", "min", TRUE)

The result can look like:

Plot parameters

If you don't know the needed arguments of a specific plot, take a look into the package documentation. As most of the plots are created with plotly you can interactivly change the visualization.

To get more information about the components of your data table execute following commands:

getMeasures(data.table)
getLists(data.table)
getMainColumns(data.table)
getParameterColumns(data.table)
getParameters(data.table, parameter.column)
getTunings(data.table)

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