A Shiny Input for date-ranges, which pops up two calendars for selecting dates, times, or predefined ranges like "Last 30 Days". It wraps the JavaScript library 'daterangepicker' which is available at <https://www.daterangepicker.com>.

Provides methods for working with nominal dates, times, and 
 durations. Base R has sophisticated facilities for handling time, but these 
 can give unexpected results if, for example, timezone is not handled properly. 
 This package provides a more casual approach to support cases which 
 do not require rigorous treatment.  It systematically deconstructs the 
 concepts origin and timezone, and de-emphasizes the display of seconds. It 
 also converts among nominal durations such as seconds, hours, days, and weeks.
 See '?datetime' and '?duration' for examples. Adapted from 'metrumrg' 
 <http://r-forge.r-project.org/R/?group_id=1215>.

Supports import/export for a number of datetime string standards 
    and R datetime classes often including
    lossless re-export of     
    any original reduced precision including 'ISO 8601' <https://en.wikipedia.org/wiki/ISO_8601> and 
    'pdfmark' <https://opensource.adobe.com/dc-acrobat-sdk-docs/library/pdfmark/> datetime strings.
    Supports local/global datetimes with optional UTC offsets and/or (possibly heterogeneous) time zones
    with up to nanosecond precision.

Provides a datetime range picker widget for usage in 'Shiny'.
    It creates a calendar allowing to select a start date and an end date
    as well as two fields allowing to select a start time and an end time.

Utilities for handling dates and times, such
   as selecting particular days of the week or month,
   formatting timestamps as required by RSS feeds, or
   converting timestamp representations of other software
   (such as 'MATLAB' and 'Excel') to R. The package is
   lightweight (no dependencies, pure R implementations) and
   relies only on R's standard classes to represent dates
   and times ('Date' and 'POSIXt'); it aims to provide
   efficient implementations, through vectorisation and the
   use of R's native numeric representations of timestamps
   where possible.