This document compares two integrated development environments (IDEs) for the R programming language: R-Studio and Rcmdr. R-Studio is a more powerful and flexible IDE that provides direct access to R code and facilitates interactions with R through its graphical interface. Rcmdr is simpler and more user-friendly, focusing on statistical analysis through buttons and menus. Both allow viewing data, but neither support data editing. The document provides guidelines for choosing between them and notes additional R IDEs under development.

1. Advanced Data Analytics:
R-Studio vs. Rcmdr
Jeffrey Stanton
School of Information Studies
Syracuse University

2. R-Studio Overview
• R-Studio is an integrated development environment to support the
development of R code
• R-Studio runs in two ways:
– Desktop versions for Linux, Mac, and Windows: Single user, perfect for a
laptop or desktop machine
– Server version for Linux: Allows any number of remote users to run R-
Studio within a web-browser; facilitates sharing of code and data among
team members
• R-Studio uses the graphical environment of the computer to facilitate
interactions with R:
– Console window for typing code
– Data window for reviewing data frame and other data structures
– Workspace for viewing all of the data loaded into R
– Plot area for showing visualizations
– Tabbed window controls to show other displays
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3. R-Studio Screenshot
Workspace shows
Console: Run R
available data
Commands Here
structures
Multi-tab display:
Shows graphics
and other info
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4. R-Studio Data File Import Dialog
Name of data
frame to be
created with
imported data
How the data
frame will look
once the data
Options for
are imported
parsing the text
data into fields
and values
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5. R-Studio Data Display
Familiar spread-
sheet-like display
format
Does not support
editing of the data
or variable names
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6. Rmcdr Overview
• Rcmdr – “R Commander” – is a graphical user interface for statistical
analysis laid on top of R; R runs in another window and can be used
directly at any time; uses buttons and menus extensively and supports
picking variable names from lists
• Rcmdr was purpose built to simplify access to the most essential
statistical analysis methods; more convenient for users who have used
SPSS, SAS or Stata
• Does not provide direct access to the R command line, but does show
the code that is running
• Not richly graphical, but does show three panes:
– Script Window: Shows the most recently run commands/code
– Output Window: Displays statistical output and results from commands
– Messages Window: Shows errors, warnings, and notes
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7. Rcmdr Screen Shot Menu system has
many commonly
used diagnostics
and tests
Script window
shows most
recent commands
or code
Data set editing
does not usually
work for data
frames
Output window Message window
shows results reports errors
from most recent from commands
commands
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8. Rcmdr Dialog Screenshot Sensible defaults
with the option
of customization
for expert users
Variable selection
window, allows
choosing from
list
Checkboxes for
access to common
options for a
statistical test
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9. Comparison and Guidelines
• R-Studio is more flexible and powerful, and provides direct access to R
code
• Rcmdr is simpler and more user friendly, particularly when focusing on
statistical diagnostics and analysis
• Both are good for viewing data, neither is good for editing it
• Use Rcmdr with structured, conventional data (rectangular, with
variables in columns and cases in rows), whenever the task involves
running statistical tests
• Use R-studio for any project that requires direct interaction with code
and/or manipulation of complex data
• Note that you can invoke Rcmdr from within R-Studio and it will work
fine on a single user installation; also note that when the user requests a
plot in Rcmdr, it will NOT immediately appear in the plot window of R-
Studio – this is a known bug that may be fixed in future versions
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10. What Else is Brewing?
• JGR (Jaguar) – A cross platform console interface that
provides a spreadsheet-like data editor
• Deducer – A conventional statistics GUI
overlaid on JGR
• RKWard – A conventional
statistics GUI using KDE
(mainly for Linux, but has a
Windows installer)
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11. Demonstrating Mastery
• If you have not already done so, install and run R-Studio
• Import a data set into R-Studio using the “Import Dataset”
dialog (usually a button on the Workspace tab in the upper
right pane)
• In addition, install the Rcmdr package and “library(Rcmdr)”
to start the graphical interface (for assistance, see Chapter 2
of Thomas Hogan’s “Bare Bones R”
• In Rcmdr, make your imported data the “active” data set and
use the menus to run any statistical diagnostic or test
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