3. Jupyter Notebook files¶

You can create content with Jupyter Notebooks. For example, the content for the current page is contained in this notebook file.

Jupyter Book supports all markdown that is supported by Jupyter Notebooks. This is mostly a flavor of markdown called CommonMark Markdown with minor modifications. For more information about writing Jupyter-flavored markdown in Jupyter Book, see markdown.

3.1. Code blocks and image outputs¶

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

from matplotlib import rcParams, cycler
import matplotlib.pyplot as plt
import numpy as np
plt.ion()

# 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']);

Note that the image above is captured and displayed in your site.

3.2. Removing content before publishing¶

You can also remove some content before publishing your book to the web. For reference, you can download the notebook content for this page.

You can remove only the code so that images and other output still show up.

thisvariable = "this plot *will* show up in the textbook."

fig, ax = plt.subplots()
x = np.random.randn(100)
y = np.random.randn(100)
ax.scatter(x, y, s=np.abs(x*100), c=x, cmap=plt.cm.coolwarm)
ax.text(0, .5, thisvariable, fontsize=20, transform=ax.transAxes)
ax.set_axis_off()

Which works well if you’d like to quickly display cell output without cluttering your content with code. This works for any cell output, like a Pandas DataFrame.

import pandas as pd
pd.DataFrame([['hi', 'there'], ['this', 'is'], ['a', 'DataFrame']], columns=['Word A', 'Word B'])

	Word A	Word B
0	hi	there
1	this	is
2	a	DataFrame

Notebooks for data science

3. Jupyter Notebook files¶

3.1. Code blocks and image outputs¶

3.2. Removing content before publishing¶