Learning Objectives

• Jupyter Markdown Python Variable
• Python Jupyter Markdown Font Size
• Python Jupyter Markdown Bold

How to Follow This Tutorial. To get the most out of this tutorial you should be familiar with programming — Python and pandas specifically. That said, if you have experience with another language, the Python in this article shouldn’t be too cryptic, and will still help you get Jupyter Notebooks set up locally. Use the MyST Markdown format, a markdown flavor that “implements the best parts of reStructuredText”, if you wish to render your notebooks using Sphinx or Jupyter Book. Use the R Markdown format if you want to open your Jupyter Notebooks in RStudio.

• Explain what the Markdown format is.
• Describe the role of Markdown for documentation of earth data science workflows.
• Use Markdown syntax in Jupyter Notebook to:
  • Create headers and lists
  • Bold and italicize bold text
  • Render images and create hyperlinks to web pages

What is Markdown?

Markdown is a human readable syntax (also referred to as a markup language) for formatting text documents. Markdown can be used to produce nicely formatted documents including PDFs and web pages.

When you format text using Markdown in a document, it is similar to using the format tools (e.g. bold, heading 1, heading 2) in a word processing tool like Microsoft Word or Google Docs. However, instead of using buttons to apply formatting, you use syntax such as **this syntax bolds text in markdown** or # Here is a heading.

Markdown syntax allows you to format text in many ways, such as making headings, bolding and italicizing words, creating bulleted lists, adding links, formatting mathematical symbols and making tables. These options allow you to format text in visually appealing and organized ways to present your ideas.

You can use Markdown to format text in many different tools including GitHub.com, R using RMarkdown, and Jupyter Notebook, which you will learn more about this page.

Data Tip: Learn more about how you can use Markdown to format text and document workflows in a variety of tools.

Markdown in Jupyter Notebook

A great benefit of Jupyter Notebook is that it allows you to combine both code (e.g. Python) and Markdown in one document, so that you can easily document your workflows.

A Jupyter Notebook file uses cells to organize content, and it can contain both cells that render text written using the Markdown syntax as well as cells that contain and run Python code.

Thus, you can use a combination of Markdown and Python code cells to organize and document your Jupyter Notebook for others to easily read and follow your workflow.

Data Tip: Learn more about Markdown for Jupyter Notebook.

If you render your Jupyter Notebook file to HTML or PDF, this Markdown will appear as formatted text in the output document.

Data Tip: In fact, this web page that you are reading right now is generated from a Markdown document! On this page, you will learn the basic syntax of Markdown.

Benefits of Markdown for Earth Data Science

Being able to include both Markdown and code (e.g. Python) cells in a Jupyter Notebook file supports reproducible science by allowing you to:

• Document your workflow: You can add text to the document that describes the steps of your processing workflow (e.g. how data is being processed and what results are produced).
• Describe your data: You can describe the data that you are using (e.g. source, pre-processing, metadata).
• Interpret code outputs: You can add some text that interprets or discusses the outputs.

all in one document!

When used effectively, Markdown documentation can help anyone who opens your Jupyter Notebook to follow, understand and even reproduce your workflow.

Format Text in Jupyter Notebook with Markdown

Markdown Cells in Jupyter Notebook

In the previous chapter on Jupyter Notebook, you learned how to add new Markdown cells to your Jupyter Notebook files using Menu tools and Keyboard Shortcuts to create new cells.

Function	Keyboard Shortcut	Menu Tools
Create new cell	Esc + a (above), Esc + b (below)	Insert→ Insert Cell Above OR Insert → Insert Cell Below
Copy Cell	c	Copy Key
Paste Cell	v	Paste Key

You also learned how to change the default type of the cell by clicking in the cell and selecting a new cell type (e.g. Markdown) in the cell type menu in the toolbar. Furthermore, you learned that in a Jupyter Notebook file, you can double-click in any Markdown cell to see the syntax, and then run the cell again to see the Markdown formatting.

Note: if you type text in a Markdown cell with no additional syntax, the text will appear as regular paragraph text. You can add additional syntax to that text to format it in different ways.

On this page, you will learn basic Markdown syntax that you can use to format text in Jupyter Notebook files.

Section Headers

You can create a heading using the pound (#) sign. For the headers to render properly, there must be a space between the # and the header text.

Heading one is denoted using one # sign, heading two is denoted using two ## signs, etc, as follows:

Here is a sample of the rendered Markdown:

Heading Three

Heading Four

Note: the titles on this page are actually formatted using Markdown (e.g. the words Section Headers above are formatted as a heading two).

Lists

You can also use Markdown to create lists using the following syntax:

It will render as follows:

• This is a bullet list
• This is a bullet list
• This is a bullet list

1. And you can also create ordered lists
2. by using numbers
3. and listing new items in the lists
4. on their own lines

Notice that you have space between the * or 1. and the text. The space triggers the action to create the list using Markdown.

Bold and Italicize

You can also use ** to bold or * to italicize words. To bold and italicize words, the symbols have to be touching the word and have to be repeated before and after the word using the following syntax:

It will render as follows:

These are italicized words, not a bullet listThese are bold words, not a bullet list

• This is a bullet item with bold words
• This is a bullet item with italicized words

Highlight Code

If you want to highlight a function or some code within a plain text paragraph, you can use one backtick on each side of the text like this:

which renders like this:

Here is some code!

The symbol used is the backtick, or grave; not an apostrophe (on most US keyboards, it is on the same key as the tilde (~)).

Horizontal Lines (Rules)

You can also create a horizontal line or rule to highlight a block of Markdown syntax (similar to the highlighting a block of code using the backticks):

which renders like this:

Here is some important text!

Hyperlinks

You can also use HTML in Markdown cells to create hyperlinks to websites using the following syntax:

<a href='url' target='_blank'>hyperlinked words</a>

You can identify the words that will be hyperlinked (i.e. prompt a web page to open when clicked) by replacing hyperlinked words in the example above.

For example, the following syntax:

Our program website can be found at <a href='http://earthdatascience.org' target='_blank'>this link</a>.

will render as follows with this link as the hyperlinked words:

Our program website can be found at this link.

Render Images

You can also use Markdown to link to images on the web using the following syntax:

![alt text here](url-to-image-here)

The alt text is the alternative text that appears if an image fails to load on webpage; it is also used by screen-reading tools to identify the image to users of the screen-reading tools.

For example, the following syntax:

![Markdown Logo is here.](https://www.fullstackpython.com/img/logos/markdown.png)

will render as follows with an alt text of Markdown Logo is here.:

Local Images Using Relative Computer Paths

You can also add images to a Markdown cell using relative paths to files in your directory structure using:

![alt text here](path-to-image-here)

For relative paths (images stored on your computer) to work in Jupyter Notebook, you need to place the image in a location on your computer that is RELATIVE to your .ipynb file. This is where good file management becomes extremely important.

For a simple example of using relative paths, imagine that you have a subdirectory named images in your earth-analytics directory (i.e. earth-analytics/images/).

If your Jupyter Notebook file (.ipynb) is located in root of this directory (i.e. earth-analytics/notebook.ipynb), and all images that you want to include in your report are located in the images subdirectory (i.e. earth-analytics/images/), then the path that you would use for each image is:

images/image-name.png

If all of your images are in the images subdirectory, then you will be able to easily find them. This also follows good file management practices because all of the images that you use in your report are contained within your project directory.

Data tip: There are many free Markdown editors out there! The atom.io editor is a powerful text editor package by GitHub, that also has a Markdown renderer that allows you to preview the rendered Markdown as you write.

Additional Resources

Practice Your Markdown Skills

1. Open or create a new Jupyter Notebook file.

2. Add a new Markdown cell and include:
   • A title for the notebook (e.g. Intro to Earth Analytics - Chapter Four)
   • A bullet list with:
     • A bold word for Author: and then add text for your name.
     • A bold word for Date: and then add text for today’s date.
3. Add another Markdown cell and include:
   • A list of your top three favorite foods (e.g. blueberries, chocolate bars, avocados).
     • Italicize the first item in your list.
     • Add a hyperlink (i.e. webpages) for the second item in your list (include the name of the food in the title of the hyperlink).
     • Add an image for the last item in your list (include the name in the alt text of the image).

It is possible to store Jupyter notebooks in plain Markdown. This allows youto define a notebook structure entirely using MyST Markdown. For more informationabout MyST Markdown, see MyST Markdown overview.

Notebooks with Markdown can be read in, executed, and cached by Jupyter Book (see Execute and cache your pages for information on how to cache pages).This allows you to store all of your notebook content in a text format that is much nicer for version control software, while still having all the functionality of a Jupyter notebook.

Note

MyST notebooks uses [MyST-NB to convert between ipynb and text files][myst-nb:index].See its documentation for more information.

To see an example of a MyST notebook, you can look atmany of the pages of this documentation.For example, see ../interactive/hiding.md and ../content/layout.md.

Create a MyST notebook with Jupytext¶

The easiest way to create a MyST notebook is to use Jupytext, a toolthat allows for two-way conversion between .ipynb and a variety of text files.

You can convert an .ipynb file to a MyST notebook with the following command:

A resulting mynotebook.md file will be created.This can then be used as a page in your book.

Important

For full compatibility with myst-parser, it is necessary to use jupytext>=1.6.0.

Jupytext can also automatically synchronize an .ipynb file with your Markdown.To do so, use a Jupyter interface such as Jupyter Lab or the classic notebook interfaceand follow the Jupytext instructions for paired notebooks.

Convert a Markdown file into Jupytext MyST Markdown¶

Jupyter Book has a small CLI to provide common functionality for manipulating andcreating MyST Markdown files that synchronize with Jupytext. To add Jupytext syntaxto a Markdown file (that will tell Jupytext it is a MyST Markdown file), run thefollowing command:

If you do not specify --kernel, then the default kernel will be used if there isonly one available. If there are multiple kernels available, you must specify onemanually.

Structure of MyST notebooks¶

Let’s take a look at the structure that Jupytext creates, which you may also useto create a MyST notebook from scratch. First, let’s take a look at a simple MyST notebook:

There are three main sections to notice:

Frontmatter YAML¶

Jupyter Markdown Python Variable

MyST notebooks need special frontmatter YAML to tell Jupytext that theycan be converted to .ipynb files. The frontmatter YAML block

tells Jupytext that the file is in myst format, and that its code shouldbe run with a Python 3 kernel.

Code cells¶

Code blocks in MyST notebooks are defined with the following MyST directive:

You can optionally add extra metadata to the code cell, which will be convertedinto cell metadata in the .ipynb file. For example, you can add tags to your codecell like so:

You may also explicitly pass the kernel name after {code-cell} to make it clear whichkernel you are running. For example:

However, remember that there is only one kernel allowed per page.

Markdown content¶

Everything in-between your code cells is parsed as Markdown content using theMyST Markdown parser. See MyST Markdown overview formore information about MyST Markdown.

To explicitly split up Markdown content into two Markdown cells, use the followingpattern:

You may also attach metadata to the cell by adding a Python dictionary after the +++.For example, to add tags to the second cell above:

Python Jupyter Markdown Font Size

Warning

Python Jupyter Markdown Bold

Please note that cell breaks and metadata specified in MyST files via the +++ syntaxonly propagate to their .ipynb counterpart. When generating the book’s HTML, Markdowncell information is discarded to avoid conflicting hierarchies in the structure of thedocument. In other words, only code cell tags have an effect on the generated HTML.