trans_venn function

Venn Diagram by Grouping Variable

Produce a Venn diagram by grouping variable.

trans_venn(
  text.var,
  grouping.var,
  stopwords = NULL,
  rm.duplicates = TRUE,
  title = TRUE,
  title.font = NULL,
  title.color = "black",
  title.cex = NULL,
  title.name = NULL,
  legend = TRUE,
  legend.cex = 0.8,
  legend.location = "bottomleft",
  legend.text.col = "black",
  legend.horiz = FALSE,
  ...
)

Arguments

• text.var: The text variable.

• grouping.var: The grouping variables. Default NULL generates one word list for all text. Also takes a single grouping variable or a list of 1 or more grouping variables.

• stopwords: Words to exclude from the analysis.

• rm.duplicates: logical. If TRUE removes the duplicated words from the analysis (only single usage is considered).

• title: logical. IF TRUE adds a title corresponding to the grouping.var.

• title.font: The font family of the cloud title.

• title.color: A character vector of length one corresponding to the color of the title.

• title.cex: Character expansion factor for the title. NULL and NA are equivalent to 1.0

• title.name: A title for the plot.

• legend: logical. If TRUE uses the names from the target.words

  list corresponding to cloud.colors.

• legend.cex: Character expansion factor for the legend. NULL and NA are equivalent to 1.0.

• legend.location: The x and y co-ordinates to be used to position the legend. The location may also be specified by setting x to a single keyword from the list "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right" and "center". This places the legend on the inside of the plot frame at the given location.

• legend.text.col: The color used for the legend text.

• legend.horiz: logical; if TRUE, set the legend horizontally rather than vertically.

• ...: Other arguments passed to plot.

Returns

Returns a Venn plot by grouping variable(s).

Warning

The algorithm used to overlap the Venn circles becomes increasingly overburdened and less accurate with increased grouping variables. An alternative is to use a network plot with {codeDissimilarity measures labeling the edges between nodes (grouping variables) or a heat map (qheat).

Examples

## Not run:

with(DATA , trans_venn(state, person, legend.location = "topright"))
#the plot below will take a considerable amount of time to plot
with(raj.act.1 , trans_venn(dialogue, person, legend.location = "topleft"))
## End(Not run)

See Also

venneuler