¿Cómo oculto el código Jupyter?

How do I hide Jupyter code?

Hide or remove content

1. To hide Markdown, use the {toggle} directive.
2. To hide or remove code cells or their outputs, use notebook cell tags.

Simply double clicking left of the code cell will collapse it to a single line: Double clicking again will expand the cell.

Put a ; at the end of a line to suppress the printing of output [Reference].

It is possible that you are running an infinite loop within the kernel and that is why it can’t complete the execution. Try manually stopping the kernel by pressing the stop button at the top. If that doesn’t work, interrupt it and restart it by going to the “Kernel” menu. This should disconnect it.

Installing jupyter_contrib_nbextensions

1. Install the python package. PIP.
2. Install javascript and css files. This step copies the nbextensions’ javascript and css files into the jupyter server’s search directory, and edits some jupyter config files.
3. Enabling/Disabling extensions.
4. More complex setups.

Optimize Ourselves First

1. Pre-process the dataset before running complex loops and algorithms.
2. Backup data regularly.
3. Test our codes first.
4. Be keyboard ninjas.
5. Auto Code-Complete.
6. Auto-Save.
7. Enable Jupyter Notebook to show memory usage.
8. Create then modify Jupyter Notebook configuration file to allocate more RAM or data stream.

I have a jupyter notebook that is a mixture of markdown and code. In the end I want to render it out as a pdf report and hide the code. I still want to see the output of the code, the plots and tables, I just don’t want to see the code in the final report.

To launch Jupyter Notebook, first open the Anaconda Navigator: Then, click on the button to launch Jupyter: Next, click on ‘New’ on the top right-hand-side of your screen: Finally, select ‘R’ from the drop-down list: You’ll then see the following screen where you can type your code: You can now run your desired R code.

Just like with Jupyter, you can also work interactively with your R Markdown notebooks. It works a bit differently from Jupyter, as there are no real magic commands; To work with other languages, you need to add separate Bash, Stan, Python, SQL or Rcpp chunks to the notebook.

3.1Code chunks and inline R code 3.2Write Markdown in the RStudio visual editor 3.3Render an R script to a report 3.4Convert R Markdown to R script 3.5R Markdown Notebooks