The Jupyter ecosystem contains many useful tools for working with Python including Jupyter Notebook, an interactive coding environment. Learn how to work with cells, including Python code and Markdown text cells, in Jupyter Notebook. The markdown cell in Jupyter Notebook can display six levels of heading. For making a heading, start the syntax with # followed by a space and then the text. This will make the heading of level 1 – The biggest. To decrease the size of the heading start incrementing the number of #. Level 1 Heading = # sampletext Level 2 Heading = ## sampletext. “Text can be added to Jupyter Notebooks using Markdown cells. You can change the cell type to Markdown by using the Cell menu, the toolbar, or the key shortcut m.Markdown is a popular markup language that is a superset of HTML. JUPYTER NOTEBOOK CHEAT SHEET Learn PYTHON from experts at Keyboard Shortcuts Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. It is used for data cleaning and transformation, numerical simulation, statistical. Here’s how to format Markdown cells in Jupyter notebooks: HeadingsUse the number sign (#) followed by a blank space for notebook titles and section headings: # for titles ## for major headings ### for subheadings #### for 4th level subheadings; EmphasisUse the following code to emphasize text: Bold text: string or.string.
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“Text can be added to Jupyter Notebooks using Markdown cells. You can change the cell type to Markdown by using the Cell menu, the toolbar, or the key shortcut m. Markdown is a popular markup language that is a superset of HTML. Its specification can be found here:n”,“n”,“<https://daringfireball.net/projects/markdown/>”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“You can make text italic or bold by surrounding a block of text with a single or double * respectively”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“You can build nested itemized or enumerated lists:n”,“n”,“* Onen”,” - Sublistn”,” - Thisn”,” - Sublistn”,” - Thatn”,” - The other thingn”,“* Twon”,” - Sublistn”,“* Threen”,” - Sublistn”,“n”,“Now another list:n”,“n”,“1. Here we gon”,” 1. Sublistn”,” 2. Sublistn”,“2. There we gon”,“3. Now this”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“Here is a blockquote:n”,“n”,“> Beautiful is better than ugly.n”,“> Explicit is better than implicit.n”,“> Simple is better than complex.n”,“> Complex is better than complicated.n”,“> Flat is better than nested.n”,“> Sparse is better than dense.n”,“> Readability counts.n”,“> Special cases aren’t special enough to break the rules.n”,“> Although practicality beats purity.n”,“> Errors should never pass silently.n”,“> Unless explicitly silenced.n”,“> In the face of ambiguity, refuse the temptation to guess.n”,“> There should be one– and preferably only one –obvious way to do it.n”,“> Although that way may not be obvious at first unless you’re Dutch.n”,“> Now is better than never.n”,“> Although never is often better than right now.n”,“> If the implementation is hard to explain, it’s a bad idea.n”,“> If the implementation is easy to explain, it may be a good idea.n”,“> Namespaces are one honking great idea – let’s do more of those!”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“And shorthand for links:n”,“n”,“[Jupyter’s website](https://jupyter.org)”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“You can use backslash to generate literal characters which would otherwise have special meaning in the Markdown syntax.n”,“n”,“`n','*literalasterisks*n','*literalasterisks*n','`n”,“n”,“Use double backslash to generate the literal $ symbol.”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“You can add headings by starting a line with one (or multiple) # followed by a space, as in the following example:n”,“n”,“`n','#Heading1n','#Heading2n','##Heading2.1n','##Heading2.2n','`”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“You can embed code meant for illustration instead of execution in Python:n”,“n”,” def f(x):n”,” ''a docstring''n”,” return x**2n”,“n”,“or other languages:n”,“n”,” for (i=0; i<n; i++) {n”,” printf('hello %dn', i);n”,” x += 4;n”,” }”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“Courtesy of MathJax, you can include mathematical expressions both inline: n”,“$e^{ipi} + 1 = 0$ and displayed:n”,“n”,“begin{equation}n”,“e^x=sum_{i=0}^infty frac{1}{i!}x^in”,“end{equation}n”,“n”,“Inline expressions can be added by surrounding the latex code with $:n”,“n”,“`n','$e^{ipi}+1=0$n','`n”,“n”,“Expressions on their own line are surrounded by begin{equation} and end{equation}:n”,“n”,“`latexn','begin{equation}n','e^x=sum_{i=0}^inftyfrac{1}{i!}x^in','end{equation}n','`”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“The Notebook webapp supports Github flavored markdown meaning that you can use triple backticks for code blocks:n”,“n”,” `pythonn','print'HelloWorld'n','`n”,“n”,” `javascriptn','console.log('HelloWorld')n','`n”,“n”,“Gives:n”,“n”,“`pythonn','print'HelloWorld'n','`n”,“n”,“`javascriptn','console.log('HelloWorld')n','`n”,“n”,“And a table like this: n”,“n”,” | This | is |n',' |------|——|n',' | a | table| n”,“n”,“A nice HTML Table:n”,“n”,“| This | is |n','|——|------|n”,“| a | table| n”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“Because Markdown is a superset of HTML you can even add things like HTML tables:n”,“n”,“<table>n”,“<tr>n”,“<th>Header 1</th>n”,“<th>Header 2</th>n”,“</tr>n”,“<tr>n”,“<td>row 1, cell 1</td>n”,“<td>row 1, cell 2</td>n”,“</tr>n”,“<tr>n”,“<td>row 2, cell 1</td>n”,“<td>row 2, cell 2</td>n”,“</tr>n”,“</table>”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“If you have local files in your Notebook directory, you can refer to these files in Markdown cells directly:n”,“n”,” [subdirectory/]<filename>n”,“n”,“For example, in the images folder, we have the Python logo:n”,“n”,” <img src='../images/python_logo.svg' />n”,“n”,“<img src='../images/python_logo.svg' />n”,“n”,“and a video with the HTML5 video tag:n”,“n”,” <video controls src='../images/animation.m4v'>animation</video>n”,“n”,“<video controls src='../images/animation.m4v'>animation</video>n”,“n”,“These do not embed the data into the notebook file, and require that the files exist when you are viewing the notebook.”
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
]
},{
“cell_type”: “markdown”,“metadata”: {},“source”: [
“Note that this means that the Jupyter notebook server also acts as a generic file servern”,“for files inside the same tree as your notebooks. Access is not granted outside then”,“notebook folder so you have strict control over what files are visible, but for thisn”,“reason it is highly recommended that you do not run the notebook server with a notebookn”,“directory at a high level in your filesystem (e.g. your home directory).n”,“n”,“When you run the notebook in a password-protected manner, local file access is restrictedn”,“to authenticated users unless read-only views are active.”
]
},{
“image/jpeg”: “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”
}
},“cell_type”: “markdown”,“metadata”: {},“source”: [
“### Markdown attachmentsn”,“n”,“Since Jupyter notebook version 5.0, in addition to referencing external file you can attach a file to a markdown cell. n”,“To do so drag the file from in a markdown cell while editing it:n”,“n”,“n”,“n”,“Files are stored in cell metadata and will be automatically scrubbed at save-time if not referenced. You can recognized attached images from other files by their url that starts with attachment:. For the image above:n”,“n”,” n”,” n”,“Keep in mind that attached files will increase the size of your notebook. n”,“n”,“You can manually edit the attachement by using the View > Cell Toolbar > Attachment menu, but you should not need to. “
]
}
],“metadata”: {
Jupyter Notebook Markdown Cheatsheet
“anaconda-cloud”: {},“kernelspec”: {
Jupyter Notebook Tutorial
“display_name”: “Python 3”,“language”: “python”,“name”: “python3”
},“language_info”: {
“name”: “ipython”,“version”: 3
},“file_extension”: “.py”,“mimetype”: “text/x-python”,“name”: “python”,“nbconvert_exporter”: “python”,“pygments_lexer”: “ipython3”,“version”: “3.7.2”
}
Jupyter Notebook Python Tutorial
},“nbformat”: 4,“nbformat_minor”: 1
Jupiter Notebook Markup Cheat Sheet Download
}