![]() We need to install the reticulate package if it’s not already on our system, and then load the reticulate package. Serdar, any other must-have packages you’d recommend for an R user doing data analysis or other common work? So instead of install.packages() in our R console, we need to run pip install in a terminal window to install Python libraries. Step 4 is a familiar one: Install packages we want. Step 3 is to activate my virtual environment with the source command. ![]() Serdar, why should we use one virtual environment per project? Again, notice that I’m running that virtualenv command in a terminal window, and not the R console. I’ll open an R project in RStudio and then create my virtual environment. Next, step 2, is to create a Python virtual environment for an RStudio project. While I run pip install, Serdar, can you tell us why we need virtual environments? That requires Python’s pip install command, which I’ll run in a terminal window. RStudio says we need the virtualenv Python package. But we’ve got choices! Serdar, would you recommend downloading from or Anaconda? Another question I often run into for Python in general: Should I use Python version two-dot-X or three-dot-X? Step 1, not surprisingly, is to install Python. Instead, since we’ve got Serdar here to help, I’d like to go through a manual version: RStudio’s suggested workflow, step by step. But it can be hard to understand what’s going on here. R is running commands to install Python, install some Python packages, and create a virtual environment. If you run that you should see a response something like this. If you are working locally, the reticulate R package has an easy Python install command: install_miniconda(). He’s here to help answer questions we R users might have when installing and configuring Python for RStudio. It’s “special” because I’ve got a guest today: Serdar Yegulalp, InfoWorld’s Python expert and host of the InfoWorld Dev with Serdar video series. I’m Sharon Machlis at IDG Communications, here with a special episode of Do More With R: How to set up your system for Python.
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