tot_plot: Visualize Word Length by Turn of Talk

Description

Uses a bar graph to visualize patterns in sentence length and grouping variables 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.

Value

Invisibly returns the ggplot2 object.

Examples

Run this code

# 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")) 
# }

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