Create qdap Specific Data Structure

Usage

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.

Create qdap Specific Data Structure

Value

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

Description

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.

References

Inspired by dplyr's tbl_df structure.

Examples

## <strong>Not run</strong>: # 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 # ## <strong>End(Not run)</strong>

See also

%&%, sentSplit