==================================================================================
 New memisc release 0.99.20.1 improves compatibility with RStudio and "tidyverse"
==================================================================================

.. post:: 22 Nov 2019
   :category: software, memisc
   :excerpt: 3

.. previewimage:: view-importer-screenshot-small.png

Release 0.99.20.1. has been published on `CRAN`_. It improves the way the
package interoperates with `RStudio`_ and "tidyverse". In particular:

- A function ``view()`` provides a generic interface to the GUI function
  ``View()`` in base *R* and *RStudio*. It makes it possible to extend it to
  data objects of the classes "data.set",
  "codeplan",
  "description", and "importer".

.. figure:: view-importer-screenshot.png
   :figwidth: 100%
   :align: center

   The result of ``view(ZA5702)``, where ``ZA5702`` is an "importer" object
   created by ``spss.file("ZA5702_v2-0-0.sav")``.

- A ``as_tibble()`` method for "data.set" objects allows to transfer these
  objects more easiliy into the "tidyverse", i.e. facilitates the use of
  functions from these package ecosystem on data sets imported or created with
  *memisc*. An ``as_haven()`` function translates "data.set" objects into
  "tibbles" objects with that extra information that the "haven" package adds to
  "tibbles" imported with the help of that package. This should allow to view
  and post-process data imported with *memisc* more or less the same way as if
  the data were imported with "haven".

- When a "data.set" object is translated into a data frame using
  ``as.data.frame()``, ``as_tibble()``,
  ``as_haven()``, or ``viewPrep()`` (the
  internal function used by ``view()`` to prepare data for being
  viewed) the "description" of the variables (or "item" objects) are retained as
  "label" attributes, so that labels are visible when viewed in *RStudio*.

.. figure:: view-dataset-screenshot.png
      :figwidth: 100%
      :align: center

      The result of ``view(gles2013work)``, where ``gles2013work`` is a "data.set" object
      created by ``subset(ZA5702,...)``.

- A ``List()`` function adds names to its elements by deparsing arguments in the
  same way as ``data.frame()`` does.
          
- A new function ``Groups()`` allows to split a data frame or a "data.set" into
  group based on factors in a more convenient way. There are methods of
  ``with.grouped.data with()``
  and ``within.grouped.data within()`` to deal with resulting objects of class "grouped.data". For
  example, the ``within.grouped.data within()`` method allows to substract group means from the
  observations within groups. ``withinGroups()`` allows to split a data frame or
  "data.set" objects into groups, make within-group computations and recombine
  the groups into the order of the original data frame or "data.set" object.

- ``Stata.file()`` now handles files in format rev. 117 and
  later as they are created by Stata version later than 13.
            
- User definded missing values are now reported in separate tables in entries
  created by ``codebook()`` even if these entries refer to "item" objects
  with
  measurement level "interval" or "ratio".
            
- If the annotation or the labels of a non-item is set to ``NULL`` this no longer
  causes an error.
            
- Changing varible names to lowercase while importing data sets with
  ``Stata.file()``, ``spss.portable.file()``, and
  ``spss.system.file()`` is now optional.
            
- Importer methods ``Stata.file()``, ``spss.portable.file()``, and
  ``spss.system.file()`` now have optional arguments that allow to deal with
  variable labels or value labels in non-native encoding (e.g. ``CP1252`` on a
  ``utf-8`` platform).
            
- A function ``spss.file()`` acts as a common interface to ``spss.portable.file()``
  and ``spss.system.file()``.
            
- The function ``head()`` and ``tail()`` now work with
  "data.set"
  and "importer"
  objects in the same sensible way as they do with data frames.
            
- The function ``recode()`` behaves more coherently: If a labelled vector is the
  result of ``recode()`` it gets the ``measurement measurement level``
  "nominal". Factor levels
  explictly created first come first in the order of factor levels.
          
      
.. _CRAN: http://cran.r-project.org/package=memisc     
.. _RStudio: http://rstudio.org