qdap_df function

Create qdap Specific Data Structure

Creating this qdap specific data structure enables short hand with subsequent qdap function calls that utilize the text.var

argument. Combined with the %&% operator, the user n need not specify a data set or the text.var argument (as many qdap functions contain a text.var argument).

Change text.var column of a qdap_df object.

qdap_df(dataframe, text.var)

Text(object)

Text(object) <- value

Arguments

• dataframe: A data.frame with a text variable. Generally, sentSplit should be run first (sentSplit actually produces a data.frame that is of the class "qdap_df").
• text.var: The name of the text.var column.
• object: A data.frame of the class "qdap_df".
• value: A character string of the updated text.var column.

Returns

Returns a data.frame of the class "qdap_df".

Examples

## Not run:

dat <- qdap_df(DATA, state)
dat %&% trans_cloud(grouping.var=person)
dat %&% trans_cloud(grouping.var=person, text.var=stemmer(DATA$state))
dat %&% termco(grouping.var=person, match.list=list("fun", "computer"))
class(dat)

## Change text column in `qdap_df` (Example 1)
dat2 <- sentSplit(DATA, "state", stem.col = TRUE)
class(dat2)
dat2 %&% trans_cloud()
Text(dat2)
## change the `text.var` column
Text(dat2) <- "stem.text"
dat2 %&% trans_cloud()

## Change text column in `qdap_df` (Example 2)
(dat2$fake_dat <- paste(emoticon[1:11,2], dat2$state))
Text(dat2) <- "fake_dat"
(m <- dat2 %&% sub_holder(emoticon[,2]))
m$unhold(strip(m$output))

## Various examples with qdap functions
dat <- sentSplit(DATA, "state")
dat %&% trans_cloud(grouping.var=person)
dat %&% termco(person, match.list=list("fun", "computer"))
dat %&% trans_venn(person)
dat %&% polarity(person)
dat %&% formality(person)
dat %&% automated_readability_index(person)
dat %&% Dissimilarity(person)
dat %&% gradient_cloud(sex)
dat %&% dispersion_plot(c("fun", "computer"))
dat %&% discourse_map(list(sex, adult))
dat %&% gantt_plot(person)
dat %&% word_list(adult)
dat %&% end_mark_by(person)
dat %&% end_mark()
dat %&% word_stats(person)
dat %&% wfm(person)
dat %&% word_cor(person, "i")
dat %&% sentCombine(person)
dat %&% question_type(person)
dat %&% word_network_plot()
dat %&% character_count()
dat %&% char_table(person)
dat %&% phrase_net(2, .1)
dat %&% boolean_search("it||!")
dat %&% trans_context(person, which(end_mark(DATA.SPLIT[, "state"]) == "?"))
dat %&% mgsub(c("it's", "I'm"), c("it is", "I am"))

## combine with magrittr/dplyr chaining
dat %&% wfm(person) %>% plot()
dat %&% polarity(person) %>% scores()
dat %&% polarity(person) %>% counts()
dat %&% polarity(person) %>% scores()
dat %&% polarity(person) %>% scores() %>% plot()
dat %&% polarity(person) %>% scores %>% plot
## End(Not run)

References

Inspired by dplyr's tbl_df structure.

See Also

%&%, sentSplit