Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
We’re very pleased to announce the release of qdap 1.1.0
This is the fourth installment of the qdap package available at CRAN. Major development has taken place since the last CRAN update.
The qdap package automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse, including frequency counts of sentence types, words, sentence, turns of talk, syllable counts and other assorted analysis tasks. The package provides parsing tools for preparing transcript data but may be useful for many other natural language processing tasks. Many functions enable the user to aggregate data by any number of grouping variables providing analysis and seamless integration with other R packages that undertake higher level analysis and visualization of text.
This version is a major overhaul of the qdap package. The word lists and dictionaries in qdap have been moved to qdapDictionaries. Additionally, many functions have been renamed with underscores instead of the former period separators. These changes break backward compatibility. Thus this is a major release (ver. 1.0.0). It is the general practice to deprecate functions within a package before removal, however, the number of necessary changes in light of qdap being relatively new to CRAN, made these changes sensible at this point.
To install use:
install.packages(“qdap”)
Some of the changes in version 1.1.0 include:
PACKAGE VIGNETTE
qdap gains an HTML package vignette to better explain the intended workflow and function use for the package. This is not currently a part of the build but can be accessed via:
tm PACKAGE COMPATABILITY
qdap 1.1.0 attempts to gain compatability with the tm package. This enables data structures from tm to be utilized with qdap functions and conversely qdap data structures to be utilized with functions intended for tm data sets. Some of the following changes have been made to gain tm compatability:
tdmanddtmare now truly compatable with thetmpackage.tdmanddtmproduce outputs of the class"TermDocumentMatrix"and"DocumentTermMatrix"respectively. This change (coupled with the renaming ofstopwordstorm_stopwords) should make the two packages logical companions and further extend the qdap package to integrate with the many packages that already handle"TermDocumentMatrix"and"DocumentTermMatrix".tm2qdapa function to convert"TermDocumentMatrix"and"DocumentTermMatrix"to awfmadded to allow easier integration with thetmpackage.apply_as_tma function to allow functions intended to be used on thetmpackage’sTermDocumentMatrixto be applied to awfmobject.tm_corpus2dfanddf2tm_corpusadded to convert a tm package corpus to a dataframe for use in qdap or vice versa.
NEW FEATURES
hash_look(and%ha%) a counterpart tohashadded to allow quick access to a hash table. Intended for use within functions or multiple uses of the same hash table, whereaslookupis intended for a single external (non-function) use which is more convenient though could be slower.word_coradded to find words within grouping variables that are associated based on correlation.dispersion_plotadded to enable viewing of word dispersion through discourse.word_proximityadded to complimentdispersion_plotandword_corfunctions.word_proximitygives the average distance between words in the unit of sentences.boolean_search, a Boolean term search function, added to allow for indexed searches of Boolean terms.wfmnow usesmtabulateand is ~10x faster.
PLOTTING
Several Plotting Functions have been added to qdap. Many functions pick up a corresponding plotting method as well.
This version of qdap has seen some exciting changes. We look forward to continued development. In the future we plan to:
- Further develop the
new_reportfunction to better incorporate the reports package and smooth workflow. - Incorporate the dplyr package to gain speed boosts in some of qdap’s functions.
For a complete list of changes see qdap’s NEWS.md
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
