Last chance! 50% off unlimited learning
Sale ends in
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,
...
)
Returns a Venn plot by grouping variable(s).
The text variable.
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.
Words to exclude from the analysis.
logical. If TRUE
removes the duplicated words
from the analysis (only single usage is considered).
logical. IF TRUE
adds a title corresponding to the
grouping.var
.
The font family of the cloud title.
A character vector of length one corresponding to the color of the title.
Character expansion factor for the title. NULL
and
NA
are equivalent to 1.0
A title for the plot.
logical. If TRUE
uses the names from the
target.words
list corresponding to cloud.colors.
Character expansion factor for the legend. NULL
and
NA
are equivalent to 1.0.
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.
The color used for the legend text.
logical; if TRUE
, set the legend horizontally
rather than vertically.
Other arguments passed to plot.
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
).
venneuler
if (FALSE) {
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"))
}
Run the code above in your browser using DataLab