Visualize Word Length by Turn of Talk

Usage

tot_plot(dataframe, text.var, grouping.var = NULL, facet.vars = NULL, tot = TRUE, transform = FALSE, ncol = NULL, ylab = NULL, xlab = NULL, bar.space = 0, scale = NULL, space = NULL, plot = TRUE)

Arguments

dataframe
A dataframe that contains the text variable and optionally the grouping.var and tot variables.
text.var
The text variable (character string).
grouping.var
The grouping variables to color by. Default NULL colors everything in "black". Also takes a single grouping variable or a list of 1 or more grouping variables.
facet.vars
An optional single vector or list of 1 or 2 to facet by.
tot
The turn of talk variable (character string). May be TRUE (assumes "tot" is the variable name), FALSE (use row numbers), or a character string of the turn of talk column.
transform
logical. If TRUE the repeated facets will be transformed from stacked to side by side.
ncol
number of columns. gantt_wrap uses facet_wrap rather than facet_grid.
ylab
Optional y label.
xlab
Optional x label.
bar.space
The amount space between bars (ranging between 1 and 0).
scale
Should scales be fixed ("fixed", the default), free ("free"), or free in one dimension ("free_x", "free_y")
space
If "fixed", the default, all panels have the same size. If "free_y" their height will be proportional to the length of the y scale; if "free_x" their width will be proportional to the length of the x scale; or if "free" both height and width will vary. This setting has no effect unless the appropriate scales also vary.
plot
logical. If TRUE the plot will automatically plot. The user may wish to set to FALSE for use in knitr, sweave, etc. to add additional plot layers.

Visualize Word Length by Turn of Talk

Value

Invisibly returns the ggplot2 object.

Description

Uses a bar graph to visualize patterns in sentence length and grouping variables by turn of talk.

Examples

## <strong>Not run</strong>: # dataframe <- sentSplit(DATA, "state") # tot_plot(dataframe, "state") # tot_plot(DATA, "state", tot=FALSE) # tot_plot(dataframe, "state", bar.space=.03) # tot_plot(dataframe, "state", "sex") # tot_plot(dataframe, "state", "person", tot = "sex") # tot_plot(mraja1, "dialogue", "fam.aff", tot=FALSE) # tot_plot(mraja1, "dialogue", "died", tot=FALSE) # tot_plot(mraja1, "dialogue", c("sex", "fam.aff"), tot=FALSE) + # scale_fill_hue(l=40) # tot_plot(mraja1, "dialogue", c("sex", "fam.aff"), tot=FALSE)+ # scale_fill_brewer(palette="Spectral") # tot_plot(mraja1, "dialogue", c("sex", "fam.aff"), tot=FALSE)+ # scale_fill_brewer(palette="Set1") # # ## repeated measures # rajSPLIT2 <- do.call(rbind, lapply(split(rajSPLIT, rajSPLIT$act), head, 25)) # tot_plot(rajSPLIT2, "dialogue", "fam.aff", facet.var = "act") # # ## add mean and +/- 2 sd # tot_plot(mraja1, "dialogue", grouping.var = c("sex", "fam.aff"), tot=FALSE)+ # scale_fill_brewer(palette="Set1") + # geom_hline(aes(yintercept=mean(word.count))) + # geom_hline(aes(yintercept=mean(word.count) + (2 *sd(word.count)))) + # geom_hline(aes(yintercept=mean(word.count) + (3 *sd(word.count)))) + # geom_text(parse=TRUE, hjust=0, vjust=0, family="serif", size = 4, aes(x = 2, # y = mean(word.count) + 2, label = "bar(x)")) + # geom_text(hjust=0, vjust=0, family="serif", size = 4, aes(x = 1, # y = mean(word.count) + (2 *sd(word.count)) + 2, label = "+2 sd")) + # geom_text(hjust=0, vjust=0, family="serif", size = 4, aes(x = 1, # y = mean(word.count) + (3 *sd(word.count)) + 2, label = "+3 sd")) # ## <strong>End(Not run)</strong>