Point RStudio to the installation of Python that we are using, which in this case is Miniconda Python that we installed above. Install the reticulate package, which is what we use to translate between Python and R, and To use Python in RStudio we need to do two things: We are now ready to use Python in RStudio. You should then be asked if you want to proceed enter y to do so. In this case, we want to install NumPy and Pandas, which are some the most widely used Python libraries. Whenever we want to install Python packages we use the terminal and type: To add this channel we open the Git Bash terminal and type the following: We want to add something called the conda-forge channel, which is a community-driven effort to provide the most up to date versions of Python packages. conda installs Python packages from different online repositories which are called “channels”. Recall that we will be using the package manager conda, which was downloaded using Miniconda. Next we want to install the Python packages that we will be using. To be able to do this, we open the Anaconda Prompt and type conda init bash.įrom now on we will be able to do everything from the Git Bash terminal.Ĭlose the Anaconda Prompt window and any open terminal windows. when installing new Python packages), we want to be able to do this directly from the Git Bash terminal. Rather than controlling our Python installations using the Anaconda Prompt (e.g. You should now have access to the Anaconda Prompt (to open it, click on the Start menu and start typing ‘Anaconda’). ģ - Integrate Python with the Git Bash terminal By default, this should install to a directory like C:/Users//miniconda3. In my case I downloaded the Python 3.8 version, and installed it with the default settings. To get this we are going to use Miniconda, which was described above.ĭownload and run the Miniconda installer which can be found We need to have a base version of Python installed on our machine. This is referred to below as “the terminal”. (To open Git Bash, click on the Start menu and start typing ‘Git’). Once downloaded, we can run Git Bash to open the terminal. To do this we download and install the Git Bash program, which can be found here: Rather than using the built-in Windows command line (CMD), we will use Git Bash. We want to be able to interact with our computer via a command line interface. If you have trouble on the steps below, or need more detail, you may want to check out the material provided by Dr Timbers above. The notes below are for Windows and assume you already have RStudio up and running. The steps outlined below were partly based on notes provided by Dr Tiffany Timbers as part of an Intro to Reticulate workshop ( ). The Miniconda installer will give us a version of Python, a package manager called conda, and some other useful packages. More precisely, it uses a minimal version called Miniconda. But I got there with the approach outlined below. There appear to be a few ways to do this, and to be honest it took me a while to get it working. We want to set up RStudio so that we can write Python code, add Python libraries, and transition between R and Python when working on a single project. The objective here is to use RStudio as a Python IDE. Given that it took me a day or two to set up, I thought this warranted its own post and may be of use to others following the same path. In this post, I describe the nuts and bolts of getting Python up and running in RStudio with the reticulate package. In an upcoming post, I will be looking at learning Python from the perspective of an R user. This is facilitated by the fact that RStudio has made it easier to work with both Python and R in a single project, using RStudio as a single interface. My intention is not to move from R to Python, but to be able to work with both R and Python, treating them as complementary tools. I enjoy using R for data analysis but recently have been learning Python.
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