toaster (version 0.4.2)

createCentroidPlot: Create plot of cluster centroids.

Description

Visualize centroids produced by clustering function like k-means. Plots available are line plot, bar plot, or heatmap. Parameter format specifies which one to create.

Usage

createCentroidPlot(km, format = "line", groupByCluster = TRUE,
  baseSize = 12, baseFamily = "serif", title = paste("Cluster Centroids",
  format, "Plot"), xlab, ylab = ifelse(format == "heatmap", "cluster",
  ifelse(km$scale, "scaled value", "value")), legendPosition = ifelse(format
  == "bar", "none", "right"), coordFlip = FALSE, ticks = FALSE,
  defaultTheme = theme_tufte(base_size = baseSize, base_family = baseFamily,
  ticks = ticks), themeExtra = NULL)

Arguments

km

an object of class "toakmeans" returned by computeKmeans.

format

type of plot to use: "line", "bar", "bar_dodge", "bar_facet" (same as "bar") or "heatmap".

groupByCluster

logical: indicates if centroids are grouped by clusters or variables. groupByCluster has no effect when format="heatmap".

baseSize

theme base font size.

baseFamily

theme base font family.

title

plot title.

xlab

a label for the x axis, defaults to a description of x.

ylab

a label for the y axis, defaults to a description of y.

legendPosition

the position of legends. ("left", "right", "bottom", "top", or two-element numeric vector). "none" is no legend.

coordFlip

logical flipped cartesian coordinates so that horizontal becomes vertical, and vertical horizontal (see coord_flip).

ticks

logical Show axis ticks using default theme settings (see defaultTheme)?

defaultTheme

plot theme settings with default value theme_tufte. More themes are available here: ggtheme (by http://ggplot2.org/{ggplot2}

themeExtra

any additional theme settings that override default theme.

Value

• ggplot object

Examples

if(interactive()){
# initialize connection to Lahman baseball database in Aster 
conn = odbcDriverConnect(connection="driver={Aster ODBC Driver};
                         server=<dbhost>;port=2406;database=<dbname>;uid=<user>;pwd=<pw>")
                         
km = computeKmeans(conn, "batting", centers=5, iterMax = 25,
                   aggregates = c("COUNT(*) cnt", "AVG(g) avg_g", "AVG(r) avg_r", "AVG(h) avg_h"),
                   id="playerid || '-' || stint || '-' || teamid || '-' || yearid", 
                   include=c('g','r','h'), scaledTableName='kmeans_test_scaled', 
                   centroidTableName='kmeans_test_centroids',
                   where="yearid > 2000")
createCentroidPlot(km)
createCentroidPlot(km, format="bar_dodge")
createCentroidPlot(km, format="heatmap", coordFlip=TRUE)
}