---
jupyter:
  jupytext:
    formats: ipynb,md
    text_representation:
      extension: .md
      format_name: markdown
      format_version: '1.2'
      jupytext_version: 1.4.2
  kernelspec:
    display_name: Python 3
    language: python
    name: python3
---

# Content with notebooks

You can also create content with Jupyter Notebooks. This means that you can include
code blocks and their outputs in your book.

## Markdown + notebooks

As it is markdown, you can embed images, HTML, etc into your posts!

![](https://myst-parser.readthedocs.io/en/latest/_static/logo.png)

You an also $add_{math}$ and

$$
math^{blocks}
$$

or

$$
\begin{aligned}
\mbox{mean} la_{tex} \\ \\
math blocks
\end{aligned}
$$

But make sure you \$Escape \$your \$dollar signs \$you want to keep!

## MyST markdown

MyST markdown works in Jupyter Notebooks as well. For more information about MyST markdown, check
out {doc}`syntax`, or see [the MyST markdown documentation](https://myst-parser.readthedocs.io/en/latest/).

## Code blocks and outputs

Jupyter Book will also embed your code blocks and output in your book.
For example, here's some sample Matplotlib code:

```python tags=["hide-input"]
from matplotlib import rcParams, cycler
import matplotlib.pyplot as plt
import numpy as np
plt.ion()
```

```python
# Fixing random state for reproducibility
np.random.seed(19680801)

N = 10
data = [np.logspace(0, 1, 100) + np.random.randn(100) + ii for ii in range(N)]
data = np.array(data).T
cmap = plt.cm.coolwarm
rcParams['axes.prop_cycle'] = cycler(color=cmap(np.linspace(0, 1, N)))


from matplotlib.lines import Line2D
custom_lines = [Line2D([0], [0], color=cmap(0.), lw=4),
                Line2D([0], [0], color=cmap(.5), lw=4),
                Line2D([0], [0], color=cmap(1.), lw=4)]

fig, ax = plt.subplots(figsize=(10, 5))
lines = ax.plot(data)
ax.legend(custom_lines, ['Cold', 'Medium', 'Hot']);
```

There is a lot more that you can do with outputs (such as including interactive outputs)
with your book. For more information about this, see [the Jupyter Book documentation](https://executablebooks.github.io/cli/start/overview.html)

```python
import plotly.graph_objects as go
import numpy as np

# Create figure
fig = go.Figure()

# Add traces, one for each slider step
for step in np.arange(0, 5, 0.1):
    fig.add_trace(
        go.Scatter(
            visible=False,
            line=dict(color="#00CED1", width=6),
            name="𝜈 = " + str(step),
            x=np.arange(0, 10, 0.01),
            y=np.sin(step * np.arange(0, 10, 0.01))))

# Make 10th trace visible
fig.data[10].visible = True

# Create and add slider
steps = []
for i in range(len(fig.data)):
    step = dict(
        method="update",
        args=[{"visible": [False] * len(fig.data)},
              {"title": "Slider switched to step: " + str(i)}],  # layout attribute
    )
    step["args"][0]["visible"][i] = True  # Toggle i'th trace to "visible"
    steps.append(step)

sliders = [dict(
    active=10,
    currentvalue={"prefix": "Frequency: "},
    pad={"t": 50},
    steps=steps
)]

fig.update_layout(
    sliders=sliders
)

fig.show()
```