rank_freq_mplot
- Plot a faceted word rank versus frequencies by
grouping variable(s).
rank_freq_plot
- Plot word rank versus frequencies.
rank_freq_mplot(text.var, grouping.var = NULL, ncol = 4, jitter = 0.2,
log.freq = TRUE, log.rank = TRUE, hap.col = "red", dis.col = "blue",
alpha = 1, shape = 1, title = "Rank-Frequency Plot", digits = 2,
plot = TRUE)rank_freq_plot(words, frequencies, plot = TRUE, title.ext = NULL,
jitter.ammount = 0.1, log.scale = TRUE, hap.col = "red",
dis.col = "blue")
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.
integer value indicating the number of columns in the facet wrap.
Amount of horizontal jitter to add to the points.
logical. If TRUE
plots the frequencies in the natural
log scale.
logical. If TRUE
plots the ranks in the natural log
scale.
Color of the hapax legomenon points.
Color of the dis legomenon points.
Transparency level of points (ranges between 0 and 1).
An integer specifying the symbol used to plot the points.
Optional plot title.
Integer; number of decimal places to round.
logical. If TRUE
provides a rank frequency plot.
A vector of words.
A vector of frequencies corresponding to the words argument.
The title extension that extends: "Rank-Frequency Plot ..."
Amount of horizontal jitter to add to the points.
logical. If TRUE
plots the rank and frequency as a
log scale.
Returns a rank-frequency plot and a list of three dataframes:
The word frequencies supplied to
rank_freq_plot
or created by
rank_freq_mplot
.
A dataframe of rank and frequencies for the words used in the text.
A dataframe displaying the percent hapax legomena and percent dis legomena of the text.
Zipf, G. K. (1949). Human behavior and the principle of least effort. Cambridge, Massachusetts: Addison-Wesley. p. 1.
# NOT RUN {
#rank_freq_mplot EXAMPLES:
x1 <- rank_freq_mplot(DATA$state, DATA$person, ncol = 2, jitter = 0)
ltruncdf(x1, 10)
x2 <- rank_freq_mplot(mraja1spl$dialogue, mraja1spl$person, ncol = 5,
hap.col = "purple")
ltruncdf(x2, 10)
invisible(rank_freq_mplot(mraja1spl$dialogue, mraja1spl$person, ncol = 5,
log.freq = FALSE, log.rank = FALSE, jitter = .6))
invisible(rank_freq_mplot(raj$dialogue, jitter = .5, alpha = 1/15))
invisible(rank_freq_mplot(raj$dialogue, jitter = .5, shape = 19, alpha = 1/15))
#rank_freq_plot EXAMPLES:
mod <- with(mraja1spl , word_list(dialogue, person, cut.n = 10,
cap.list=unique(mraja1spl$person)))
x3 <- rank_freq_plot(mod$fwl$Romeo$WORD, mod$fwl$Romeo$FREQ, title.ext = 'Romeo')
ltruncdf(x3, 10)
ltruncdf(rank_freq_plot(mod$fwl$Romeo$WORD, mod$fwl$Romeo$FREQ, plot = FALSE) , 10)
invisible(rank_freq_plot(mod$fwl$Romeo$WORD, mod$fwl$Romeo$FREQ, title.ext = 'Romeo',
jitter.ammount = 0.15, hap.col = "darkgreen", dis.col = "purple"))
invisible(rank_freq_plot(mod$fwl$Romeo$WORD, mod$fwl$Romeo$FREQ, title.ext = 'Romeo',
jitter.ammount = 0.5, log.scale=FALSE))
invisible(lapply(seq_along(mod$fwl), function(i){
dev.new()
rank_freq_plot(mod$fwl[[i]]$WORD, mod$fwl[[i]]$FREQ,
title.ext = names(mod$fwl)[i], jitter.ammount = 0.5, log.scale=FALSE)
}))
# }
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