Jupyter Notebook 7

Post by bjornasm » Thu, Jul 27, 2023, 9:21 PM UTC

toolslive wrote: post #41

zmmmmm wrote: post #21

Earlier quoted context omitted.

Curious what other approach you would take to do exploratory data analysis? It's so natural to me I can't think of another way that would be practical to achieve the same workflow.

emacs org mode can do this but is not tied to just python. Anyway, something like this works: #+BEGIN_SRC python :results file import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt fn = 'my_fig.png' plt.plot([1, 2, 3, 2.5, 2.8]) plt.savefig('my_fig.png', dpi=50) return fn #+END_SRC #+RESULTS: [[file:my_fig.png]]

  import matplotlib
  matplotlib.use('Agg')
  import matplotlib.pyplot as plt
  plt.plot([1, 2, 3, 2.5, 2.8])

  Alright, saving the figure at 50 dpi first
  plt.savefig('my_fig.png', dpi=50)

  Trying a bit more DPI to see if that makes a difference
  plt.savefig('my_fig2.png', dpi=150)

  Oh, wrong numbers, forgot that the fourth datapoint was going to signify 100, going back to 50 dpi as well
  plt.plot([1, 2, 3, 100, 2.3])
  plt.savefig('my_fig4.png', dpi=50)

Post by afshin » Thu, Jul 27, 2023, 10:38 PM UTC

Tomte wrote: post #102

Does debugging work for you? Neither in Notebook nor in Lab can I click in the gutter to set breakpoints. The debugging panel is open, the documentation is clear (except that by default there are no line numbers and you have to activate that), but nothing happens. Where exactly am I supposed to click?

Post by aumerle » Fri, Jul 28, 2023, 5:28 AM UTC

chaxor wrote: post #83

janalsncm wrote: post #35

Earlier quoted context omitted.

Neither of those use cases are exclusive to jupyter. You can run scripts on remote machines quite easily, and matplotlib will happily pop up a window for your charts. The real reason is because it’s a much better workflow for data exploration and manipulation because you don’t always know exactly what code to write before you do it. So having the data in memory is really useful.

X forwarding through a terminal session to view that matplotlib plot is a bit more work than most want to deal with. Sure, you can use ranger, and set up the image viewing with uzerbeurg? or something? and set up kitty with icat, but that doesn't work with your tmux, so you have to have a separate ssh window that's not tmux'd, which is annoying and clunky, just for viewing images. You also have to save them, and then…

Post by zelphirkalt » Sat, Jul 29, 2023, 11:52 PM UTC

jncfhnb wrote: post #60

nl wrote: post #4

> Both Jupyter Notebook and JupyterLab are widely used across data science, machine learning, computational research, and education. Are they though? Does anyone actually use JupyterLab by choice? From what I've seen people love Jupyter Notebook but find JupyterLab misses the mark (and this is certainly my experience).

I have seen the exact opposite. JupyterLab is far more dominant. Including cloud service providers like AWS’ Sagemaker using it as the go to simple data scientist interface. I started strongly advocating for it pretty much immediately. The waste of space on the margins of the notebook view was (is?) awful.