Do you mean Anaconda Cloud? In other words, do you see ‘Home | Cloud: Data Science an Python Tools from Anaconda’ as the name of the tab from where you launch Jupyter?
Do you mean line numbers or cell execution numbers?
I ask about cell execution numbers because if you are in the same session and you use a kernel that is already open, the cell execution numbers won’t be correct. Did you shut down all the kernels and try restarting? Did you make sure you didn’t have multiple notebooks tied to the same kernel? (This is my main suspicion about what is happening.)
Another idea….
I also ask about cell execution numbers because last year there was an issue last year where the cell execution numbers were off because the ‘Anaconda Assistant’ was causing invisible executions; however, one of the suggestions was updating there and I don’t think you can update Anaconda Cloud(?).
Any chance you have real-time collaboration active?
I’m trying Anaconda Cloud right now (JupyterLab 4.0.9 & Jupyter Notebook 7.0.6) and everything looks fine, but I only have old kernels I made a while ago. What kernel are you using with what JupyterLab version? Or Jupyter Notebook version?
You can rule out something by testing elsewhere perhaps? Go here and click ‘`launch binder`’ and see if you have the same issues in the session there?
While I am mentioning GitHub gists…
There are ways to share notebooks using Github’s gist. It will share it in pre-run form so we can see what happened and have the option use MyBinder to test it & compare.
Example rendered via nbviewer. (Source notebook actually stored as Gihub gist , at which nbviewer was pointed.)
What you shared now would have benefitted from taking advantage of how you post code here as block code formatting, see here about ‘Block code formatting’ for details.