update docs for the polyglot notebooks to include using venvs

docs/jupyter-in-polyglot-notebooks.md

@@ -6,15 +6,23 @@ This feature is currently in preview.
 
 ## Setup
 Before you begin, make sure you have the following installed:
-1. [The Anaconda distribution](https://docs.anaconda.com/free/anaconda/install/index.html)
-2. [Python](https://www.python.org/downloads/) and/or [R](https://cran.r-project.org/)
+1. [The Anaconda distribution](https://docs.anaconda.com/free/anaconda/install/index.html). Comes with Python and Jupyter.
+2. OR Install [Python](https://www.python.org/downloads/) and add to your PATH. You would need to install [Jupyter](https://jupyter.org/install#jupyter-notebook)
+3. If you are working with R - Install [R](https://cran.r-project.org/)
 
 ## Connecting to a Python kernel
 Run the following command in a notebook cell:
+
+If working with Jupyter using Anaconda:
 ```
 #!connect jupyter --kernel-name pythonkernel --conda-env base --kernel-spec python3
 ```
 
+If working with Python and Jupyter directly without Anaconda:
+```
+#!connect jupyter --kernel-name pythonkernel --kernel-spec python3
+```
+
 Once connected, create a new cell and select your Python kernel from the kernel picker in the bottom right hand corner of the cell.
 
 ## Connecting to an R kernel
@@ -28,10 +36,16 @@ install.packages('IRkernel')
 IRkernel::installspec() 
 ```
 
-Then restart VS Code from the Anaconda prompt, and run the following command in a notebook cell:
+If you installed a new kernelspec or added new environment variables, you will need to restart VSCode.
+
+If working with Jupyter using Anaconda, run the following command in a notebook cell:
 ```
 #!connect jupyter --kernel-name Rkernel --conda-env base --kernel-spec ir
 ```
+If working with Jupyter directly without Anaconda:
+```
+#!connect jupyter --kernel-name Rkernel --kernel-spec ir
+```
 
 Once connected, create a new cell and select your R kernel from the kernel picker.
 
@@ -40,4 +54,51 @@ To connect to a remote Jupyter server, run this command in a notebook cell:
 ```
 #!connect jupyter --url <url_for_jupyter> --token <token_you_used_for_jupyter> --kernel-name pythonkernel --kernel-spec python3
 ```
-For R, run the same command but replace `python3` with `ir` under `--kernel-spec` and give a new name for `kernel-name`.
+For R, run the same command but replace `python3` with `ir` under `--kernel-spec` and give a new name for `kernel-name`.
+
+
+## Using Virtual environments 
+
+Both with Python venv and Conda environments, you can create the environments and add them to Jupyter as a kernel spec. 
+
+For Python venv, run the following commands in the terminal:
+```
+python3 -m venv myenv
+myenv\Scripts\activate
+
+pip install ipykernel
+python -m ipykernel install --user --name=myenv
+```
+
+For Conda, run the following commands in the terminal or Anaconda Bash Prompt (Windows):
+```
+conda create -n myenv 
+conda activate myenv
+
+conda install ipykernel
+python -m ipykernel install --user --name=myenv
+```
+
+These environments can then be accessible as a kernel-spec in `#connect` command. 
+
+Additionally, for Conda environments, you can use the `--conda-env` option in the `#connect` command to use the environment.
+
+For example, if you create a conda environment `condaenvpython3.9` to use the python==3.9 version:
+```
+conda create -n condaenvpython3.9 python==3.9
+conda activate condaenvpython3.9
+
+conda install ipykernel
+python -m ipykernel install --user --name=condaenvpython3.9
+```
+
+You can target it using the following command and be able to use python==3.9 in your notebook.
+```
+#!connect jupyter --kernel-name pythonkernel --conda-env condaenvpython3.9 --kernel-spec python3
+```
+
+Or, you can get similar experience by adding `condaenvpython3.9` as a kernel spec to Jupyter and then using the `--kernel-spec` option to target it.
+
+```
+#!connect jupyter --kernel-name pythonkernel --conda-env base --kernel-spec condaenvpython3.9
+```