## What is Markdown?
Colab has two types of cells: text and code. Text cells are formatted using a simple markup language called Markdown.
To see the Markdown source, double-click a text cell, showing both the Markdown source and the rendered version. Above the Markdown source there is a toolbar to assist editing.
## Reference
Markdown | Preview
--- | ---
`**bold text**` | **bold text**
`*italicized text*` or `_italicized text_` | *italicized text*
`` `Monospace` `` | `Monospace`
`~~strikethrough~~` | ~~strikethrough~~
`[A link](https://www.google.com)` | [A link](https://www.google.com)
`` |
---
Headings are rendered as titles.
```markdown
# Section 1
# Section 2
## Sub-section under Section 2
### Sub-section under the sub-section under Section 2
# Section 3
```
# Section 1
# Section 2
## Sub-section under Section 2
### Sub-section under the sub-section under Section 2
# Section 3
The table of contents, available on the left side of Colab, is populated using at most one section title from each text cell.
---
```markdown
>One level of indentation
```
>One level of indentation
```markdown
>>Two levels of indentation
```
>>Two levels of indentation
---
Code blocks
````
```python
print("a")
```
````
```python
print("a")
```
---
Ordered lists:
```markdown
1. One
1. Two
1. Three
```
1. One
1. Two
1. Three
---
Unordered lists:
```markdown
* One
* Two
* Three
```
* One
* Two
* Three
---
Equations:
```markdown
$y=x^2$
$e^{i\pi} + 1 = 0$
$e^x=\sum_{i=0}^\infty \frac{1}{i!}x^i$
$\frac{n!}{k!(n-k)!} = {n \choose k}$
$A_{m,n} =
\begin{pmatrix}
a_{1,1} & a_{1,2} & \cdots & a_{1,n} \\
a_{2,1} & a_{2,2} & \cdots & a_{2,n} \\
\vdots & \vdots & \ddots & \vdots \\
a_{m,1} & a_{m,2} & \cdots & a_{m,n}
\end{pmatrix}$
```
$y=x^2$
$e^{i\pi} + 1 = 0$
$e^x=\sum_{i=0}^\infty \frac{1}{i!}x^i$
$\frac{n!}{k!(n-k)!} = {n \choose k}$
$A_{m,n} =
\begin{pmatrix}
a_{1,1} & a_{1,2} & \cdots & a_{1,n} \\
a_{2,1} & a_{2,2} & \cdots & a_{2,n} \\
\vdots & \vdots & \ddots & \vdots \\
a_{m,1} & a_{m,2} & \cdots & a_{m,n}
\end{pmatrix}$
---
Tables:
```markdown
First column name | Second column name
-------------------|------------------
Row 1, Col 1 | Row 1, Col 2
Row 2, Col 1 | Row 2, Col 2
```
First column name | Second column name
-------------------|------------------
Row 1, Col 1 | Row 1, Col 2
Row 2, Col 1 | Row 2, Col 2
---
Horizontal rules:
```markdown
---
```
---
## Differences between Colab Markdown and other Markdown dialects
Colab uses [marked.js](https://github.com/chjj/marked) and so is similar but not quite identical to the Markdown used by Jupyter and Github.
Colab supports (MathJax) $\LaTeX$ equations like Jupyter, but does not allow HTML tags in the Markdown. Colab does not support some GitHub additions like emojis and to-do checkboxes.
If HTML must be included in a Colab notebook, see the [%%html magic](/notebooks/basic_features_overview.ipynb#scrollTo=qM4myQGfQboQ).
## Useful references
* [Github Markdown basics](https://help.github.com/articles/markdown-basics/)
* [Github flavored Markdown](https://help.github.com/articles/github-flavored-markdown/)
* [Original Markdown spec: Syntax](http://daringfireball.net/projects/markdown/syntax)
* [Original Markdown spec: Basics](http://daringfireball.net/projects/markdown/basics)
* [marked.js library used by Colab](https://github.com/chjj/marked)
* [LaTex mathematics for equations](https://en.wikibooks.org/wiki/LaTeX/Mathematics)
```python
print('Hello')
```
Hello
```python
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
# Make a 10 x 10 heatmap of some random data
side_length = 10
# Start with a 10 x 10 matrix with values randomized around 5
data = 5 + np.random.randn(side_length, side_length)
# The next two lines make the values larger as we get closer to (9, 9)
data += np.arange(side_length)
data += np.reshape(np.arange(side_length), (side_length, 1))
# Generate the heatmap
sns.heatmap(data)
plt.show()
```
```python
```
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