![]() ![]() The output of the code cell will appear just below the code cell. To run this code, click on the green run icon next to the cell. In the integrated VS Code terminal, run both the commands one by one: Here is a fix taken from official VS Code Python extension. One thing is to note that, you may see a pop up saying “Error: ‘Kernelspec’ module not installed in the selected interpreter (). Next, click on “Yes” prompt where it says “Data Science library ipykernel is not installed. You will also get two pops, one of which says, “Data science libraries notebook and jupyter not installed”. This means Jupyter library is currently not installed inside WSL. The top right of the VS Code UI says “Jupyter server: Not started”. Once connected, the first view should look like this: Clicking on it should load Python extension if not loaded before. Enter Python: Create New Blank Jupyter Notebook and select it from the dropdown. This will bring up a dropdown view in the VS Code Editor view. Now, press CNTRL+SHIFT+P button simultaneously using your keyboard. This will automatically open the Remote WSL. Here is the quickest way to open VS Code integrated terminal inside Windows Subsystem for Linux (WSL). If you have followed my WSL guide, you would have seen the Ubuntu terminal by now. We will set up our Jupyter environment by creating a new Jupyter Notebook. I am using the former – Windows Subsystem for Linux (WSL) on Windows plus VS Code. ![]() To set up your environment, you can either use a combination of WSL and VS Code, or Windows 10 with VS Code. Set up our environment – Create a Jupyter Notebook The post is written exclusively for beginners in tech. This blog post is a step-by-step guide to set up and use Jupyter Notebook in VS Code Editor for data science or machine learning on Windows. ![]()
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