word_count: Word Counts

In trinker/qdap: Bridging the Gap Between Qualitative Data and Quantitative Analysis

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).

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.

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.

raw	Dataframe of the frequency of characters by grouping variable.
prop	Dataframe of the proportion of characters by grouping variable.
rnp	Dataframe of the frequency and proportions of characters by grouping variable.
percent	The value of percent used for plotting purposes.
zero.replace	The value of zero.replace used for plotting purposes.

Note

wc is a convenient short hand for word_count.

See Also

syllable_count, prop, colcomb2class

Examples

## Not run: 
## 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")

## End(Not run)

trinker/qdap documentation built on Sept. 30, 2020, 6:28 p.m.