An implementation of the decimated two-dimensional complex dual-tree wavelet transform as described in Kingsbury (1999) <doi:10.1098/rsta.1999.0447> and Selesnick et al. (2005) <doi:10.1109/MSP.2005.1550194>. Also includes the undecimated version and spectral bias correction described in Nelson et al. (2018) <doi:10.1007/s11222-017-9784-0>. The code is partly based on the 'dtcwt' Python library.

Create shareable data sets from raw data files that
	     contain protected elements. Relying on master crosswalk
	     files that list restricted variables, package functions
	     warn users about possible violations of data usage
	     agreement and prevent writing protected elements.

Provides an operator for assigning nested components of a list to
  names via a concise pattern matching syntax. This is especially convenient for
  assigning individual names to the multiple values that a function may return
  in the form of a list, and for extracting deeply nested list components.

The DuckDB project is an embedded analytical data management
    system with support for the Structured Query Language (SQL). This
    package includes all of DuckDB and an R Database Interface (DBI)
    connector.

Provides friendly wrappers for creating 'duckdb'-backed connections
  to tabular datasets ('csv', parquet, etc) on local or remote file systems.
  This mimics the behaviour of "open_dataset" in the 'arrow' package, 
  but in addition to 'S3' file system also generalizes to any list of 'http' URLs.

Programmatic access to the DuckDuckGo Instant Answer API <https://api.duckduckgo.com/api>.

A drop-in replacement for 'dplyr', powered by 'DuckDB' for
    performance.  Offers convenient utilities for working with in-memory and
    larger-than-memory data while retaining full 'dplyr' compatibility.

Fast & memory-efficient functions to analyze and manipulate large 
             spatial data data sets. It leverages the fast analytical 
             capabilities of 'DuckDB' and its spatial extension (see <https://duckdb.org/docs/stable/core_extensions/spatial/overview>) 
             while maintaining compatibility with R’s spatial data ecosystem to 
             work with spatial vector data.