A framework for text cleansing and analysis. Conveniently prepare and process large amounts of text for analysis. 
  Includes various metrics for word counts/frequencies that scale efficiently. Quickly 
  analyze large amounts of text data using a text.table (a data.table created with one word (or unit of text analysis) per row, similar to the tidytext format). 
  Offers flexibility to efficiently work with text data stored in vectors as well as text data formatted as a text.table.

Generate quad mesh primitives from the compact specification of a
 regular grid, its dimension and extent. Provides fast generation of mesh
 indexes and vertices, an unexpanded intermediate form (the grid edge
 coordinates), and a compact serializable specification for meshes that are
 generated on demand. Meshes are 'mesh3d' objects as used by the 'rgl'
 package, constructed without requiring any graphics engine, with support
 for texture mapping (Heckbert (1986) <doi:10.1109/MCG.1986.276672>) where an image is draped over a mesh whose density is
 independent of the image resolution. A C++ header library is installed so
 that other packages may generate mesh components via 'LinkingTo'.

Utilities for handling character vectors
  that store human-readable text (either plain or with
  markup, such as HTML or LaTeX). The package provides,
  in particular, functions that help with the
  preparation of plain-text reports, e.g. for expanding
  and aligning strings that form the lines of such
  reports. The package also provides generic functions for
  transforming R objects to HTML and to plain text.

Provides S3 vector types for functional data represented on
    grids, in spline bases, or via functional principal components.
    Supports arithmetic and summary methods, plotting, derivation,
    integration, smoothing, registration, and data import/export for these
    functional vectors. Includes data-wrangling tools for re-evaluation,
    subsetting, sub-assignment, zooming into sub-domains, and extracting
    functional features such as minima, maxima, and their locations.
    Enables joint analysis of functional and scalar variables by integrating
    functional vectors into standard data frames.