Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models
    ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided
    to help extract tidy data frames of draws from Bayesian models and that generate point
    summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for
    common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus
    densities), and fit curves with multiple, arbitrary uncertainty bands.

Tools to download data series from 'Banco de España' ('BdE')
    on 'tibble' format. 'Banco de España' is the national central bank
    and, within the framework of the Single Supervisory Mechanism ('SSM'),
    the supervisor of the Spanish banking system along with the European
    Central Bank. This package is in no way sponsored endorsed or
    administered by 'Banco de España'.

Multiple ways to bin numeric columns with a tidy output. Wraps a variety of existing binning methods into one function, and includes a new method for binning by equal value, which is useful for sales data. Provides a function to automatically summarize the properties of the binned columns.

Compute arbitrary non-parametric bootstrap statistics on data in
    tidy data frames.

Create additional rows and columns on broom::tidy() output to allow for easier control on categorical parameter estimates.

Provides users a quick exploratory dive into common
    visualizations without writing a single line of code given the users
    data follows the Analysis Data Model (ADaM) standards put forth by the
    Clinical Data Interchange Standards Consortium (CDISC)
    <https://www.cdisc.org>. Prominent modules/ features of the
    application are the Table Generator, Population Explorer, and the
    Individual Explorer. The Table Generator allows users to drag and drop
    variables and desired statistics (frequencies, means, ANOVA, t-test,
    and other summary statistics) into bins that automagically create
    stunning tables with validated information. The Population Explorer
    offers various plots to visualize general trends in the population
    from various vantage points. Plot modules currently include scatter
    plot, spaghetti plot, box plot, histogram, means plot, and bar plot.
    Each plot type allows the user to plot uploaded variables against one
    another, and dissect the population by filtering out certain subjects.
    Last, the Individual Explorer establishes a cohesive patient
    narrative, allowing the user to interact with patient metrics (params)
    by visit or plotting important patient events on a timeline. All
    modules allow for concise filtering & downloading bulk outputs into
    html or pdf formats to save for later.