qdap_df(dataframe, text.var)Text(object)Text(object) <- value
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 column.data.frame of the class "qdap_df".text.var column.Returns a data.frame of the class "qdap_df".
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.
Inspired by dplyr's tbl_df structure.
## <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>
%&%,
sentSplit