With 10.3.1 /Pro 1.1, we can eventually integrate open-source R statistics with ArcGIS (Python scripting) for wide data analytics, in particular, combined with R-ArcGIS Bridge (R-ArcGIS/r-bridge-install · GitHub ).
If high-performance RRE (Revolution R Enterprise) is used, 64-bit ArcGIS /Pro can easily be extended to make use of the R distributed computing infrastructure.
If any experience with this aspect of practice, please share
How does it differ from the announcement here....
Building a Bridge to the R Community | Esri Insider
and the repository here?
A comparison would be useful as to what your link offers.
After quick browsing it, it looks same as what I recommend here .
Good move, ESRI!
Personally, R Bridge with ArcGIS is a good start for data engineers (with Python coding skill) to 'directly' call rich open-source R statistics packages inside ArcGIS.
In fact, R (and SAS) is an advanced (standard, powerful) statistics tool for data engineers for over 20 years, in particular, in governments and larger business organizations, because of rich algorithms and great visualization capabilities offering huge potentials on data analytics, including spatial data (vector and raster).
Even though statistics algorithms / libraries in Python have been gaining attractions (incl. ESRI ArcGIS), majority of data engineers still prefer R (SAS or both) against Python, in practice, because of many and many reasons (you can google-it) ...
Ahhh the disciplines... R is a good inclusion and there is good overlap and differences with SciPy amongst other. Pretty soon, everything will be included... not to forget other programming languages and libraries like The Julia Language
Please keep us informed it would be great to hear what you find if you do a comparison, like Dan said.
Modules aside... there is an interesting comparison of some of the capabilities from a programming perspective between, the most common 3 languages (Matlab, R, Numpy (python/scipy/pandas) and the relative noob ... Julia
Numerical Analysis & Statistics: MATLAB, R, NumPy, Julia - Hyperpolyglot
As a reference, in practice, four main languages (R, SAS, Python, SQL) for data analytics, data mining, and data science, were "generally" surveyed in 2014 (even though some are using EXCEL, MatLab or SPSS), where data include spatial data (vector, raster), in addition to numerical and text.
And of course this rules out C, C++ and lest we forget... Fortran
For contributors and followers of this thread - there is now a GeoNet group "R-ArcGIS" dedicated to people working with both R and ArcGIS. This will provide a centralized place for sharing of ideas and instructional materials. We will continue to use the GitHub site for distribution of the R-ArcGIS bridge installation, and access point for all related source code.