# then Change kernel, and I should now be able to select the kernel # If I open an existing notebook for example, I can tap on Kernel, # environment, although no problem if in another environment I change to the root directory first so jupyter # Now to check if the new environment can be selected in Jupyter #conda list will show the env's packages, versions, and where they came from too # conda install -update-all -name python3.11 numpy # example to install a package in the new env, if desired # To utilize an R environment, it must have the r-irkernel package e.g. # Since I use R too, I'll also add a note here on R # install ipywidgets as well for some useful functionalities # Once installed, need to install ipykernel so Jupyter notebook can # I will now create a new conda env for Python 3.11 and name it as Python3.11 # R, and other languages found in other environments. # application in one conda environment to access kernels for Python, # nb_conda_kernels enables a Jupyter Notebook or JupyterLab # to fix 500 internal server error when trying to open a notebook later # stable Python version, so we will get Python from there. # The conda-forge repository seems to have at least the latest These instructions below are for Windows, and using Powershell (although they can also be used for the normal command line cmd.exe) # make sure you are in the base env From StackOverflow, there are some answers that no longer worked, and below is a compilation of commands I found on StackOverflow that worked for me, Nov-29-2022. Since Python version changes are far and few between, I always forget how I have created a new Conda environment with the latest Python for Jupyter Notebook, so I thought I'd list it down for next time.
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