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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Content with notebooks
You can also create content with Jupyter Notebooks. The content for the current page is contained
in a Jupyter Notebook in the notebooks/ folder of the repository. This means that we can include
code blocks and their outputs, and export them to Jekyll markdown.
You can find the original notebook for this page at this address
Markdown + notebooks
As it is markdown, you can embed images, HTML, etc into your posts!
You an also $add_{math}$ and
$$
math^{blocks}
$$
or
$$
\begin{align}
\mbox{mean} la_{tex} \ \
math blocks
\end{align}
$$
But make sure you \$Escape \$your \$dollar signs \$you want to keep!
Code blocks and image outputs
Textbooks with Jupyter will also embed your code blocks and output in your site.
For example, here's some sample Matplotlib code
Step1:  Note that the image above is captured and displayed by Jekyll.
Removing content before publishing
You can also remove some content before publishing your book to the web. For example,
in the original notebook there
used to be a cell below...
Step2:  You can also remove only the code so that images and other output still show up.
Below we'll only display an image. It was generated with Python code in a cell,
which you can see in the original notebook
Step3:  And here we'll only display a Pandas DataFrame. Again, this was generated with Python code
from this original notebook.
Step4:  You can configure the text that Textbooks with Jupyter uses for this by modifying your site's _config.yml file.
Interactive outputs
We can even do the same for interactive material. Below we'll display a map using ipyleaflet. When the notebook
is converted to Markdown, the code for creating the interactive map is retained.
Note that this will only work for some packages. They need to be able to output standalone HTML/Javascript, and not
depend on an underlying Python kernel to work.
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Python 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']);
Explanation: Content with notebooks
You can also create content with Jupyter Notebooks. The content for the current page is contained
in a Jupyter Notebook in the notebooks/ folder of the repository. This means that we can include
code blocks and their outputs, and export them to Jekyll markdown.
You can find the original notebook for this page at this address
Markdown + notebooks
As it is markdown, you can embed images, HTML, etc into your posts!
You an also $add_{math}$ and
$$
math^{blocks}
$$
or
$$
\begin{align}
\mbox{mean} la_{tex} \ \
math blocks
\end{align}
$$
But make sure you \$Escape \$your \$dollar signs \$you want to keep!
Code blocks and image outputs
Textbooks with Jupyter will also embed your code blocks and output in your site.
For example, here's some sample Matplotlib code:
End of explanation
thisvariable = "none of this should 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()
Explanation: Note that the image above is captured and displayed by Jekyll.
Removing content before publishing
You can also remove some content before publishing your book to the web. For example,
in the original notebook there
used to be a cell below...
End of explanation
# NO CODE
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()
Explanation: You can also remove only the code so that images and other output still show up.
Below we'll only display an image. It was generated with Python code in a cell,
which you can see in the original notebook
End of explanation
# NO CODE
import pandas as pd
pd.DataFrame([['hi', 'there'], ['this', 'is'], ['a', 'DataFrame']], columns=['Word A', 'Word B'])
Explanation: And here we'll only display a Pandas DataFrame. Again, this was generated with Python code
from this original notebook.
End of explanation
import folium
m = folium.Map(
    location=[45.372, -121.6972],
    zoom_start=12,
    tiles='Stamen Terrain'
)
folium.Marker(
    location=[45.3288, -121.6625],
    popup='Mt. Hood Meadows',
    icon=folium.Icon(icon='cloud')
).add_to(m)
folium.Marker(
    location=[45.3311, -121.7113],
    popup='Timberline Lodge',
    icon=folium.Icon(color='green')
).add_to(m)
folium.Marker(
    location=[45.3300, -121.6823],
    popup='Some Other Location',
    icon=folium.Icon(color='red', icon='info-sign')
).add_to(m)
m
Explanation: You can configure the text that Textbooks with Jupyter uses for this by modifying your site's _config.yml file.
Interactive outputs
We can even do the same for interactive material. Below we'll display a map using ipyleaflet. When the notebook
is converted to Markdown, the code for creating the interactive map is retained.
Note that this will only work for some packages. They need to be able to output standalone HTML/Javascript, and not
depend on an underlying Python kernel to work.
End of explanation
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