CUAHSI JupyterHub, Interfacing R from a Python3 Jupyter Notebook

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.当前，数据分析领域中使用Python与R开展物理/统计建模与数据可视化的趋势日益显著。作为科研人员、分析师或统计学家，我们通常会选取能够以最快速度、最高精度完成任务的工具：对部分使用者而言，这指Python；对另一部分人而言则是R；而许多人则会选择将二者结合使用。然而，在两种语言间切换，并通过.csv文件或数据库系统传递数据与模型，往往会耗费大量时间。现有一款解决方案，可让研究人员在单个Jupyter记事本（Jupyter Notebook）中快速便捷地实现R与Python的交互。本次我们提供一份作为教程的Jupyter记事本（Jupyter Notebook），演示如何在CUAHSI JupyterHub环境中实现R与Python的交互。本教程将逐步指导您安装rpy2库，并展示用于演示该交互机制的简易示例。