scatterPlot: generates a ggplot object of a scatterplot
In BenBruyneel/BBPersonalR: BBPersonalR

scatterPlot

R Documentation

generates a ggplot object of a scatterplot

Description

generates a ggplot object of a scatterplot

Usage

scatterPlot(
  data,
  xColumn = 1,
  yColumn = 2,
  xTransform = NA,
  yTransform = NA,
  removeNA = FALSE,
  xLabel = ifelse(is.character(xColumn), xColumn, colnames(data)[xColumn]),
  yLabel = ifelse(is.character(yColumn), yColumn, colnames(data)[yColumn]),
  pointAlpha = 0.75,
  pointColor = "black",
  pointFill = "red",
  pointShape = 21,
  pointSize = 2,
  smoothLine = FALSE,
  smoothLineType = "solid",
  smoothLineColor = "black",
  smoothAlpha = 0.1,
  smoothFill = "lightblue",
  smoothWidth = 0.5,
  smoothOrientation = "x",
  smoothConfidence = FALSE,
  smoothMethod = NULL,
  smoothFormula = NULL,
  title = paste(c(yLabel, " vs ", xLabel), collapse = ""),
  vertical = FALSE,
  xAxis = TRUE,
  xDefault = TRUE,
  xLimits = c(0, NA),
  xLog = FALSE,
  xSymmetric = FALSE,
  xSymmetricExpand = 0.05,
  xCentered = TRUE,
  xMedian = FALSE,
  xDeviations = 4,
  yAxis = TRUE,
  yDefault = TRUE,
  yLimits = c(0, NA),
  yLog = FALSE,
  ySymmetric = FALSE,
  ySymmetricExpand = 0.05,
  yCentered = TRUE,
  yMedian = FALSE,
  yDeviations = 4,
  gridLines = TRUE,
  gridLinesX = TRUE,
  gridLinesY = TRUE,
  abLine = NULL,
  ...
)

Arguments

`data`	the data tp be plotted, data.frame or similar
`xColumn`	specifies which column in the data argument contains the x-data (refer to column via number or character vector (column name))
`yColumn`	specifies which column in the data argument contains the y-data (refer to column via number or character vector (column name))
`xTransform`	specifies the function with which to transform the x-data (if needed), use transformData() for this
`yTransform`	specifies the function with which to transform the y-data (if needed), use transformData() for this
`removeNA`	if TRUE, the NA 'values' in the vector will be removed prior to plotting. @note this has consquence that ROWS will be removed when using multiple columns with data.frame's
`xLabel`	defines x-axis label
`yLabel`	defines y-axis label
`pointAlpha`	alpha ('see through' value) of the data points
`pointColor`	defines the color of the border of the data points
`pointFill`	defines the color of the data points themselves
`pointShape`	shape of the data points
`pointSize`	size of the data points
`smoothLine`	if TRUE then a smoothing line is drawn (via geom_smooth())
`smoothLineType`	type of the smoothing line
`smoothLineColor`	color of the smoothing line
`smoothAlpha`	alpha ('see through' value) of the smoothing line
`smoothFill`	specifies fill color pf tje smoothing confidence 'band'
`smoothWidth`	width of the smoothing nline
`smoothOrientation`	eihter "x" or "y", specifies what the smoothing orientation should be. See ?ggplot2::geom_smooth for more information
`smoothConfidence`	if TRUE then confidence 'band' is drawn around the smoothing line
`smoothMethod`	defines smoothin method. See ?ggplot2::geom_smooth for more info
`smoothFormula`	formula to use in smoothing function, See ?ggplot2::stat_smooth for more info
`title`	specifies the title
`vertical`	if TRUE then the plot is rotated 90 degrees (swap of X & Y)
`xAxis`	if TRUE, the x-axis is properly draw with label, ticks etc
`xDefault`	if default is set to FALSE, then together with xLimits, this can be used to define the exact range of the x-axis
`xLimits`	default = c(0,NA), together with xDefault, this can be used to define the exact range of the x-axis
`xLog`	if TRUE then logarithmic scale is used for the x-axis
`xSymmetric`	if TRUE then the range of x-axis will be adjusted to be equal on both the left and the right side of the center
`xSymmetricExpand`	allows for padding around data (x-axis), 0.05 means 5 percent extra wide x-axis range
`xCentered`	if TRUE, the plot will be 'cemtered' around the either the mean or median x-value
`xMedian`	if TRUE then median and mean absolute deviation (mad) are used for centering the plot along the x-axis; if FALSE then the mean and the standard deviation are used
`xDeviations`	defines how many deviations the range of the x-axis may differ from the mean or median. Range will be either (median-xDeviationsmad ,median+xDeviationsmad) or (mean - xDeviationssd,mean + xDeviations*sd)
`yAxis`	if TRUE, the y-axis is properly draw with label, ticks etc
`yDefault`	if default is set to FALSE, then together with yLimits, this can be used to define the exact range of the y-axis
`yLimits`	default = c(0,NA), together with yDefault, this can be used to define the exact range of the y-axis
`yLog`	if TRUE then logarithmic scale is used for the y-axis
`ySymmetric`	if TRUE then the range of y-axis will be adjusted to be equal on both the left and the right side of the center
`ySymmetricExpand`	allows for padding around data (y-axis), 0.05 means 5 percent extra wide y-axis range
`yCentered`	if TRUE, the plot will be 'cemtered' around the either the mean or median y-value
`yMedian`	if TRUE then median and mean absolute deviation (mad) are used for centering the plot along the y-axis; if FALSE then the mean and the standard deviation are used
`yDeviations`	defines how many deviations the range of the x-axis may differ from the mean or median. Range will be either (median-xDeviationsmad ,median+xDeviationsmad) or (mean - xDeviationssd,mean + xDeviations*sd)
`gridLines`	if TRUE then gridlines are shown
`gridLinesX`	if TRUE then vertical gridlines are shown (set gridLines to FALSE when using this)
`gridLinesY`	if TRUE then horizontal gridlines are shown (set gridLines to FALSE when using this)
`abLine`	for adding an geom_abline(), geom_hline or geom_vline function, see ggplot2::geom_abline
`...`	can be used to pass on other arguments to graphAdjust()