7 Answers. Here is a solution (following this ). from ipywidgets import IntProgress from IPython.display import display import time max_count = 100 f = IntProgress (min=0, max=max_count) # instantiate the bar display (f) # display the bar count = 0 while count <= max_count: f.value += 1 # signal to increment the progress bar time.sleep (.1 Normally, I use Jupyter in big screen (34"), so I used bigger font size 20 and you can use any value you feel good. I haven’t found any configuration in Notebook settings for output cells. As Jay mentioned, you can also use IPython.display.Code but this will work well only if you're using Jupyter Notebook. from IPython.display import Code Code ('print ("Hello World")', language='python') When using Jupyter Lab though it won't run as expected, as documented in this GitHub issue, so you'll need to run the following bit to get it The reason for this discrepancy is JupyterLab’s UI performance. We’re talking: very laggy scrolling: several seconds to quick scroll from the bottom to the top of a 50-cell notebook. 5 second lag to expand the sidebar (command palette area) 10 second lag to move a tab. 1-second lag for keyboard input. etc. Matplotlib figure not showing up in output widget in first cell of Jupyter notebook. I have the following snippet in the first cell of a Jupyter notebook: import matplotlib.pyplot as plt import pandas as pd import ipywidgets as widgets import numpy as np out = widgets.Output () data = pd.DataFrame (np.random.normal (size = 50)) plt.ioff () with I want to be able to access the source of the current Jupyter Notebook from within Python. My end goal is to pass it into ast.parse so I can do some analysis on the user's code. Ideally, I'd be able to do something like this: import ast ast.parse (get_notebooks_code ()) Obviously, if the source code was an IPYNB file, there'd be an intermediary njqy. On hovering right below. out []: in notebook you see "scroll output" . On clicking anywhere in that area you get your output scrollable both horizontally and vertically. Share. Follow. answered Feb 4, 2018 at 16:50. Krishna. 6,362 2 41 44. The problem in jupyter lab also only happens when I try to call the display function from within my own function. This is the relevant section: import IPython from IPython.display import display, clear_output try: import piplite await piplite.install ( ['ipywidgets']) except ImportError: pass import ipywidgets as widgets def onhccchange (change 1 Answer. Sorted by: 14. +50. from IPython.display import display import ipywidgets as widgets def setup_ui (df): out = widgets.Output () with out: display (df) return out. If you change your setup_ui function to this, you can return an Output widget with your dataframe. BUT, in your button_run_on_click function it appears selection is not defined. You can supply types to only show variables matching the type given. The %who_ls magic does the same thing, but returns the variables as a list. It can also limit what you see by type. The last magic is %whos, it provides a nice formatted table that will show you the variable, type, and a string representation. I am using a Jupyter notebook. I have a pretty wide screen, but the displayed output (say, when I print a numpy array) is formatted as if the screen was narrow. I found a way of increasing the width of the cells, with. from IPython.core.display import HTML HTML("") If you like to restore previous display options after given cell or piece of code than you can use method reset_option: pd.reset_option('display.max_rows') Step 6: Increase Jupyter Notebook cell width. If you have a big monitor you may want to increase the cell width of Jupyter Notebook to use maximum visual space. This can be done by:

jupyter notebook display full output