jupyterlab | Kaggle extension for JupyterLab | Machine Learning library

What is the simple and elegant way to use renv, venv and jupyterlab with IRkernel together? In particular, how to automatically activate renv from jupyter notebook that is not in the root directory?

I'm embracing a "polyglot" data science style, which means using both python and R in tandem. Now venv is awesome, and renv is awesome, and jupyterlab is awesome, so I'm trying to figure out what is the neat way to use them all together.

I almost have it, so probably a few hints would be enough to finish this setup. Here's where I'm at.

Start with a clean OS, and install system level requirements: R + renv and Python + venv. For example on Ubuntu it would be approximatelly like that:

When using a Jupyter notebook file in Visual Studio code with the Jupyter extension I receive the error The kernel failed to start due to the missing module 'ipykernel_launcher'. Consider installing this module. View Jupyter [log](command:jupyter.viewOutput) for further details.

This notebook works correctly from the JupyterLab web application when I select the same conda environment that was selected in Visual Studio Code.

pip list shows that ipykernel version 5.3.4 is installed, but I don't know how to install ipykernel_launcher. I tried reinstalling pyzmq and it didn't help.

Any ideas why this isn't working?

I am trying to make charts using JupyterDash but first things first... i can't run simple JupyterDash test via Jupyter Notebook because every time i receive the same error:

JupyterHub has various authentication methods, and the one I am using is the PAMAuthenticator, which basically means you log into the JupyterHub with your Linux userid and password.

However, environment variables that I create, like this (or for that matter in those set in my .bashrc), before running JupyterHub, do not get set within the user's JupyterLab session. As you can see they're available in the console, with or without the pipenv, and within python itself via os.getenv().

However in JupyterHub's spawned JupyterLab for my user (me):

This environment variable myname is not available even if I export it in a bash session from within JupyterLab as follows:

Now the documentation says I can customize user environments using a Docker container for each user, but this seems unnecessarily heavyweight. Is there an easier way of doing this?

If not, what is the easiest way to do this via Docker?

Using the following code from ipyleaflet documentation I get a nice display with 2 extra custom widgets. These widgets have a small dark shadow that I would like to remove.

I'm reading the csv file at https://github.com/VinitaSilaparasetty/julia-beginners/blob/master/data/nba/nba19-20.csv

I get a DataFrame and I save it as XLSX. When I try to read it in jupyterlab I get the error the file is not UTF-8 encoded and therefore the file is not read.

This is my code:

I install new modules via the following command in my miniconda

I'm trying to improve my workflow when working with R and generating documentation. I've been going between TeXStudio, JupyterLab and RStudio for a while, and I'm trying to improve my workflow. TeXStudio has limited R support, and RStudio limited support for LaTeX.

VS Code has support for multiple languages, including R and LaTeX. The fact that it can run both Jupyter notebooks, R notebooks, and LaTeX, and has plugins for other languages as well, makes it seem desirable. However, I am unable to find documentation on how to configure it to work with R and LaTeX code in the same file. In addition, I am unable to configure R notebooks to allow inline code execution output.

However, I am unable to (a) set up code execution output under the code for .Rmd notebooks, and (b) I can't figure out how to weave .Rnw (R/LaTeX) documents with Sweave/knitr.

I'm trying to find an IDE that would include features like:

• Markdown, code and code execution output in the same document
• Auto R and LaTeX code completion
• Automatic display of R function documentation
• Spell check
• Simple R console access
• Compile .Rnw
• Syntax highlighting for both R code and LaTeX code

I am, primarily, requesting ways to configure VS Code, or, secondly, way to configure another IDE that can meet my requirements. A tutorial on this would be much appreciated.

I am working with a simple ML model with streamlit. It runs fine on my local machine inside conda environment, but it shows Error installing requirements when I try to deploy it on share.streamlit.io.
The error message is the following: