Word Counts

Usage

word_count(text.var, byrow = TRUE, missing = NA, digit.remove = TRUE, names = FALSE)
wc(text.var, byrow = TRUE, missing = NA, digit.remove = TRUE, names = FALSE)
character_count(text.var, byrow = TRUE, missing = NA, apostrophe.remove = TRUE, digit.remove = TRUE, count.space = FALSE)
character_table(text.var, grouping.var = NULL, percent = TRUE, prop.by.row = TRUE, zero.replace = 0, digits = 2, ...)
char_table(text.var, grouping.var = NULL, percent = TRUE, prop.by.row = TRUE, zero.replace = 0, digits = 2, ...)

Arguments

text.var
The text variable
byrow
logical. If TRUE counts by row, if FALSE counts all words.
missing
Value to insert for missing values (empty cells).
digit.remove
logical. If TRUE removes digits before counting words.
names
logical. If TRUE the sentences are given as the names of the counts.
apostrophe.remove
logical. If TRUE apostrophes will be counted in the character count.
count.space
logical. If TRUE spaces are counted as characters.
grouping.var
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.
percent
logical. If TRUE output given as percent. If FALSE the output is proportion.
prop.by.row
logical. If TRUE applies proportional to the row. If FALSE applies by column.
zero.replace
Value to replace 0 values with.
digits
Integer; number of decimal places to round when printing.
...
Other arguments passed to prop.

Word Counts

Value

word_count - returns a word count by row or total.

character_count - returns a character count by row or total.

character_table - returns a list: dataframe of character counts by grouping variable. rawDataframe of the frequency of characters by grouping variable. propDataframe of the proportion of characters by grouping variable. rnpDataframe of the frequency and proportions of characters by grouping variable. percentThe value of percent used for plotting purposes. zero.replaceThe value of zero.replace used for plotting purposes.

Description

word_count - Transcript apply word counts.

character_count - Transcript apply character counts.

character_table - Computes a table of character counts by grouping . variable(s).

Note

wc is a convenient short hand for word_count.

Examples

## <strong>Not run</strong>: # ## WORD COUNT # word_count(DATA$state) # wc(DATA$state) # word_count(DATA$state, names = TRUE) # word_count(DATA$state, byrow=FALSE, names = TRUE) # sum(word_count(DATA$state)) # # sapply(split(raj$dialogue, raj$person), wc, FALSE) %>% # sort(decreasing=TRUE) %>% # list2df("wordcount", "person") %>% # `[`(, 2:1) # # ## PLOT WORD COUNTS # raj2 <- raj # raj2$scaled <- unlist(tapply(wc(raj$dialogue), raj2$act, scale)) # raj2$scaled2 <- unlist(tapply(wc(raj$dialogue), raj2$act, scale, scale = FALSE)) # raj2$ID <- factor(unlist(tapply(raj2$act, raj2$act, seq_along))) # # ggplot(raj2, aes(x = ID, y = scaled, fill =person)) + # geom_bar(stat="identity") + # facet_grid(act~.) + # ylab("Scaled") + xlab("Turn of Talk") + # guides(fill = guide_legend(nrow = 5, byrow = TRUE)) + # theme(legend.position="bottom") + # ggtitle("Scaled and Centered") # # # ggplot(raj2, aes(x = ID, y = scaled2, fill =person)) + # geom_bar(stat="identity") + # facet_grid(act~.) + # ylab("Scaled") + xlab("Turn of Talk") + # guides(fill = guide_legend(nrow = 5, byrow = TRUE)) + # theme(legend.position="bottom") + # ggtitle("Mean Difference") # # # raj$wc <- wc(raj$dialogue) # raj$cum.wc <- unlist(with(raj, tapply(wc, act, cumsum))) # raj$turn <- unlist(with(raj, tapply(act, act, seq_along))) # ggplot(raj, aes(y=cum.wc, x=turn)) + # geom_step(direction = "hv") + # facet_wrap(~act) # # ## CHARACTER COUNTS # character_count(DATA$state) # character_count(DATA$state, byrow=FALSE) # sum(character_count(DATA$state)) # # ## CHARACTER TABLE # x <- character_table(DATA$state, DATA$person) # plot(x) # plot(x, label = TRUE) # plot(x, label = TRUE, text.color = "red") # plot(x, label = TRUE, lab.digits = 1, zero.replace = "PP7") # # scores(x) # counts(x) # proportions(x) # # plot(scores(x)) # plot(counts(x)) # plot(proportions(x)) # # ## combine columns # colcomb2class(x, list(vowels = c("a", "e", "i", "o", "u"))) # # ## char_table(DATA$state, DATA$person) # ## char_table(DATA$state, DATA$person, percent = TRUE) # ## character_table(DATA$state, list(DATA$sex, DATA$adult)) # # library(ggplot2);library(reshape2) # dat <- character_table(DATA$state, list(DATA$sex, DATA$adult)) # dat2 <- colsplit2df(melt(counts(dat)), keep.orig = TRUE) # head(dat2, 15) # # ggplot(data = dat2, aes(y = variable, x = value, colour=sex)) + # facet_grid(adult~.) + # geom_line(size=1, aes(group =variable), colour = "black") + # geom_point() # # ggplot(data = dat2, aes(x = variable, y = value)) + # geom_bar(aes(fill = variable), stat = "identity") + # facet_grid(sex ~ adult, margins = TRUE) + # theme(legend.position="none") # ## <strong>End(Not run)</strong>

See also

syllable_count, prop, colcomb2class