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Advanced and Fast Data Transformation
A large C/C++-based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust, and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R, fast functions for data transformation and common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It seamlessly supports base R objects/classes as well as 'units', 'integer64', 'xts'/ 'zoo', 'tibble', 'grouped_df', 'data.table', 'sf', and 'pseries'/'pdata.frame'.
A Toolbox for Non-Tabular Data Manipulation
Provides a set of functions for data manipulation with list objects, including mapping, filtering, grouping, sorting, updating, searching, and other useful functions. Most functions are designed to be pipeline friendly so that data processing with lists can be chained.
API Wrapper for Nasdaq Data Link
Functions for interacting directly with the Nasdaq Data Link API to offer data in a number of formats usable in R, downloading a zip with all data from a Nasdaq Data Link database, and the ability to search. This R package uses the Nasdaq Data Link API. For more information go to < https://docs.data.nasdaq.com/>. For more help on the package itself go to < https://data.nasdaq.com/tools/r>.
Data Structures, Summaries, and Visualisations for Missing Data
Missing values are ubiquitous in data and need to be explored and
handled in the initial stages of analysis. 'naniar' provides data
structures and functions that facilitate the plotting of missing values and
examination of imputations. This allows missing data dependencies to be
explored with minimal deviation from the common work patterns of 'ggplot2'
and tidy data. The work is fully discussed at Tierney & Cook (2023)
A Wrapper of the JavaScript Library 'DataTables'
Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Linear Models for Panel Data
A set of estimators for models and (robust) covariance matrices, and tests for panel data
econometrics, including within/fixed effects, random effects, between, first-difference,
nested random effects as well as instrumental-variable (IV) and Hausman-Taylor-style models,
panel generalized method of moments (GMM) and general FGLS models,
mean groups (MG), demeaned MG, and common correlated effects (CCEMG) and pooled (CCEP) estimators
with common factors, variable coefficients and limited dependent variables models.
Test functions include model specification, serial correlation, cross-sectional dependence,
panel unit root and panel Granger (non-)causality. Typical references are general econometrics
text books such as Baltagi (2021), Econometric Analysis of Panel Data (
Visualizing Categorical Data
Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ...
Reading and writing data stored by some versions of 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', and for reading and writing some 'dBase' files.
'Global Data Lab' R API
Retrieve datasets from the 'Global Data Lab' website < https://globaldatalab.org> directly into R data frames. Functions are provided to reference available options (indicators, levels, countries, regions) as well.
Interactive Data Tables for R
Interactive data tables for R, based on the 'React Table' JavaScript library. Provides an HTML widget that can be used in 'R Markdown' or 'Quarto' documents, 'Shiny' applications, or viewed from an R console.