Description: A wrapper around the new 'cleaner' package, that allows
data cleaning functions for classes 'logical', 'factor', 'numeric',
'character', 'currency' and 'Date' to make data cleaning fast and
easy. Relying on very few dependencies, it provides smart guessing,
but with user options to override anything if needed.
Packaged: 2020-06-01 14:53:13 UTC; msberends

Title: The Critical Care Clinical Data Processing Tools
Author: Sinan Shi, David Perez-Suare, Steve Harris
A toolset to deal with the Critical Care Health Informatics Collaborative
dataset. It is created to address various data reliability and accessibility
problems of electronic healthcare records (EHR). It provides a unique
platform which enables data manipulation, transformation, reduction,
Imports: data.table, XML, yaml, Rcpp, methods, knitr, ggplot2, pander,
Collate: 'RcppExports.R' 'ccRecord.R' 'ccTable.R' 'create2dclean.R'

Author: Sinan Shi, David Perez-Suarez, Steve Harris, Niall MacCallum, David
Brealey, Mervyn Singer, James Hetherington
Description: An electronic health care record (EHR) data cleaning and processing
platform. It focus on heterogeneous high resolution longitudinal data. It works with
Critical Care Health Informatics Collaborative (CCHIC) dataset. It is
created to address various data reliability and accessibility problems of
Imports: data.table, XML, yaml, Rcpp, ggplot2, methods, pander, knitr
Collate: 'RcppExports.R' 'ccRecord.R' 'ccTable.R' 'cchic_xml.R'

Title: A Tidy Data Model for Natural Language Processing
Maintainer: Taylor B. Arnold <taylor.arnold@acm.org>
Description: Provides a set of fast tools for converting a textual corpus into a set of normalized tables. The underlying natural language processing pipeline utilizes the Stanford's CoreNLP library. Exposed annotation tasks include tokenization, part of speech tagging, named entity recognition, entity linking, sentiment analysis, dependency parsing, coreference resolution, and information extraction. Several datasets containing token unigram, part of speech tag, and dependency type frequencies are also included to assist with analyses. Currently supports parsing text in English, French, German, and Spanish.
SystemRequirements: Java (>= 7.0); Stanford CoreNLP