Using the R-ArcGIS Bridge in Jupyter
I was sitting in a presentation a few weeks ago on the R-ArcGIS bridge by Marjean Pobuda and I had a question: "Can I use the R-ArcGIS bridge in my Jupyter Notebook?" So I asked Mark Janikas (who was also attending the presentation) if this would be possible an he said, "Yes". So, after the presentation, I set out to get the R-ArcGIS bridge running in Jupyter.
Installing the ArcGIS-R Bridge
The first thing I did was install the R-ArcGIS bridge. I installed it using ArcGIS Pro by following the installation instructions. I am currently using R-3.4.2 and arcgisbinding '1.0.1.208'. I can verify this by going to the Geoprocessing tab in the Options section in ArcGIS Pro. 
Cloning My arcgispro-py3 Environment
I did not want to break my arcgispro-py3 conda environment (the default ArcGIS Pro Python environment) so the first thing I did was clone the environment. I named the cloned environment arcgispro-r. I did this from the command line as follows:
Switching Environments
Next, I switched to the cloned environment by deactivating the arcgispro-py3 environment and activating the arcgispro-r environment. This can be done at the command line with two commands, deactivate and activate, as shown her:
Installing R-Essentials
Then, I installed r-essentials, a bundle of over 80 of the most used R packages created by the Anaconda team. I did that from the command line while in my arcgispro-r environment as shown here:
Running arcgisbinding in Jupyter
After I installed r-essentials, when I launched my Jupyter Notebook, I had the option to create a Python or an R notebook. 
I created an R notebook. To test whether the ArcGIS-R bridge is installed and accessible to my notebook, I loaded the arcgisbinding package and checked the product version number and there it was, package version '1.0.1.208', the same one I see listed in ArcGIS Pro above! 
But Does It Work?
Yes, I can use the arcgisbinding package to read spatial data into R! In order to test whether I could read in data, I used arc.open to read in a point feature class of seagrass data. I was also able to use arc.select to put that feature class into a dataframe. 
I shared my sample notebook on GitHub at the repo arcgisbinding-in-jupyter. I am interested to know if there is anyone else out there who has tried this or is interested in using R, ArcGIS, and Jupyter. If you are, let me know!