how to insert code output in jupyter notebook markdown cell?

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Suggestion : 2

Updated: September 14, 2020

3 + 4

# # # This is a subtitle in Markdown

# # # # This is a smaller subtitle

# # # # # This is an even smaller subtitle

Suggestion : 3

You can use Markdown to format documentation you add to Markdown cells in your Jupyter notebook.,Here's how to format Markdown cells in Jupyter notebooks:,Yellow boxes (alert-warning) <div class="alert alert-block alert-warning"> <b>Example:</b> Use yellow boxes for examples that are not inside code cells, or use for mathematical formulas if needed. </div>,Green boxes (alert-success)<div class="alert alert-block alert-success"> <b>Up to you:</b> Use green boxes sparingly, and only for some specific purpose that the other boxes can't cover. For example, if you have a lot of related content to link to, maybe you decide to use green boxes for related links from each section of a notebook. </div>

$ mathematical symbols $

`string`

> Text that will be indented when the Markdown is rendered.

Tab

-Main bullet point
   -
   Sub bullet point

1.

1. Numbered item
1. Numbered item

Tab

1. Numbered item
1. Substep

Tab

1. Numbered item
1. Substep

Suggestion : 4

The traditional Jupyter Notebook interface allows you to toggle output scrolling for your cells. This allows you to visualize part of a long output without it taking up the entire page., Write executable content Execute and cache your pages Formatting code outputs Store code outputs and insert into content Interactive data visualizations ,The formatting of code outputs is highly configurable. Below we give examples of how to format particular outputs and even insert outputs into other locations of the document.,For example, the following cell has a long output, but will be scrollable in the book:

import numpy as np
import pandas as pd

np.random.seed(24)
df = pd.DataFrame({
   'A': np.linspace(1, 10, 10)
})
df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns = list('BCDE'))],
   axis = 1)
df.iloc[3, 3] = np.nan
df.iloc[0, 2] = np.nan

def color_negative_red(val):
   ""
"
Takes a scalar and returns a string with
the css property `'color: red'`
for negative
strings, black otherwise.
""
"
color = 'red'
if val < 0
else 'black'
return 'color: %s' % color

def highlight_max(s):
   ''
'
highlight the maximum in a Series yellow.
''
'
is_max = s == s.max()
return ['background-color: yellow'
   if v
   else ''
   for v in is_max
]

df.style.\
applymap(color_negative_red).\
apply(highlight_max).\
set_table_attributes('style="font-size: 10px"')

{
   "tags": [
      "output_scroll",
   ]
}

for ii in range(40):
   print(f "this is output line {ii}")

this is output line 0
this is output line 1
this is output line 2
this is output line 3
this is output line 4
this is output line 5
this is output line 6
this is output line 7
this is output line 8
this is output line 9
this is output line 10
this is output line 11
this is output line 12
this is output line 13
this is output line 14
this is output line 15
this is output line 16
this is output line 17
this is output line 18
this is output line 19
this is output line 20
this is output line 21
this is output line 22
this is output line 23
this is output line 24
this is output line 25
this is output line 26
this is output line 27
this is output line 28
this is output line 29
this is output line 30
this is output line 31
this is output line 32
this is output line 33
this is output line 34
this is output line 35
this is output line 36
this is output line 37
this is output line 38
this is output line 39

``
`{code-cell} ipython3
---
render:
  image:
    width: 200px
    alt: fun-fish
    classes: shadow bg-primary
  figure:
    caption: |
      Hey everyone its **party** time!
    name: fun-fish
---
from IPython.display import Image
Image("../images/fun-fish.png")
`
``

from IPython.display
import Image
Image("../images/fun-fish.png")