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| Created: | Sep 25, 2019 at 5:20 p.m. | |
| Last updated: | Oct 01, 2019 at 9:53 p.m. | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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| Views: | 1649 |
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Abstract
Nowadays, there is a growing tendency to use Python and R in the analytics world for physical/statistical modeling and data visualization. As scientists, analysts, or statisticians, we oftentimes choose the tool that allows us to perform the task in the quickest and most accurate way possible. For some, that means Python. For others, that means R. For many, that means a combination of the two. However, it may take considerable time to switch between these two languages, passing data and models through .csv files or database systems. There's a solution that allows researchers to quickly and easily interface R and Python together in one single Jupyter Notebook. Here we provide a Jupyter Notebook that serves as a tutorial showing how to interface R and Python together in a Jupyter Notebook on CUAHSI JupyterHub. This tutorial walks you through the installation of rpy2 library and shows simple examples illustrating this interface.
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http://creativecommons.org/licenses/by/4.0/
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