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DOC: Split example notebook into 3 parts: markdown/code/raw cells
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@mgeier
mgeier committed Jan 17, 2016
1 parent 881997e commit af841a4
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327 changes: 327 additions & 0 deletions doc/code-cells.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Code Cells\n",
"\n",
"An empty code cell:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A cell with no output:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"None"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A simple output:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"6 * 7"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The standard output stream:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print('Hello, world!')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Normal output + standard output"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print('Hello, world!')\n",
"6 * 7"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The standard error stream is highlighted and displayed just below the code cell.\n",
"The standard output stream comes afterwards (with no special highlighting).\n",
"Finally, the \"normal\" output is displayed."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import logging\n",
"logging.warning('I am a warning and I will appear on the standard error stream')\n",
"print('I will appear on the standard output stream')\n",
"'I am the \"normal\" output'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Special Display Formats\n",
"\n",
"See [IPython example notebook](https://nbviewer.jupyter.org/github/ipython/ipython/blob/master/examples/IPython Kernel/Rich Output.ipynb).\n",
"\n",
"TODO: tables? e.g. Pandas DataFrame?"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from IPython.display import display, Image, SVG, Math, YouTubeVideo"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Local Image Files"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"i = Image(filename='images/notebook_icon.png')\n",
"i"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"display(i)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For some reason this doesn't work with `Image(...)`:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"SVG(filename='images/python_logo.svg')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Image URLs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"Image(url='https://www.python.org/static/img/python-logo-large.png')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"Image(url='https://www.python.org/static/img/python-logo-large.png', embed=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"Image(url='http://jupyter.org/assets/nav_logo.svg')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"Image(url='https://www.python.org/static/favicon.ico')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"Image(url='http://python.org/images/python-logo.gif')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Math"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"eq = Math(r\"\\int_{-\\infty}^\\infty f(x) \\delta(x - x_0) dx = f(x_0)\")\n",
"eq"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"display(eq)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%%latex\n",
"\\begin{equation}\n",
"\\int_{-\\infty}^\\infty f(x) \\delta(x - x_0) dx = f(x_0)\n",
"\\end{equation}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"YouTubeVideo('iV2ViNJFZC8')"
]
}
],
"metadata": {
"celltoolbar": "Raw Cell Format",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.4"
}
},
"nbformat": 4,
"nbformat_minor": 0
}

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