Access Datastream content through <https://product.datastream.com/dswsclient/Docs/Default.aspx>., our historical financial database with over 35 million individual instruments or indicators across all major asset classes, including over 19 million active economic indicators. It features 120 years of data, across 175 countries – the information you need to interpret market trends, economic cycles, and the impact of world events.    Data spans bond indices, bonds, commodities, convertibles, credit default swaps, derivatives, economics, energy, equities, equity indices, ESG, estimates, exchange rates, fixed income, funds, fundamentals, interest rates, and investment trusts. Unique content includes I/B/E/S Estimates, Worldscope Fundamentals, point-in-time data, and Reuters Polls.    Alongside the content, sit a set of powerful analytical tools for exploring relationships between different asset types, with a library of customizable analytical functions.    In-house timeseries can also be uploaded using the package to comingle with Datastream maintained datasets, use with these analytical tools and displayed in Datastream’s flexible charting facilities in Microsoft Office.

Summarizes data frames by calculating various statistics including central tendency, dispersion, shape, and normality diagnostics. Handles numeric, character, and factor columns with NA-aware computations.

Allows you to define rules which can be used to verify a given
    dataset.
    The package acts as a thin wrapper around more powerful data packages such
    as 'dplyr', 'data.table', 'arrow', and 'DBI' ('SQL'), which do the heavy lifting.

Provides access to Dataverse APIs <https://dataverse.org/> (versions 4-5),
    enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0,
    use the archived 'dvn' package <https://cran.r-project.org/package=dvn>.

Provides an interactive viewer for 'data.frame' and 'tibble' objects using 'shiny' <https://shiny.posit.co/> and 'DT' <https://rstudio.github.io/DT/>. It supports complex filtering, column selection, and automatic generation of reproducible 'dplyr' <https://dplyr.tidyverse.org/> code for data manipulation. The package is designed for ease of use in data exploration and reporting workflows.