tot_plot function

Visualize Word Length by Turn of Talk

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

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.

Returns

Invisibly returns the ggplot2 object.

Examples

## Not run:

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")) 
## End(Not run)