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Add an IPython notebook tour
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‎cookbook/A quick tour of IPython Notebook.ipynb‎

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{
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"metadata": {
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"name": ""
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# A quick tour of IPython Notebook"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This tour will work a little better in interactive mode, so it'll be better if you get IPython notebook installed and running. You can start it from a terminal by running\n",
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"\n",
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"`ipython notebook --pylab inline`\n",
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"\n",
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"The `--pylab inline` is for plotting graphs"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, we need to explain how to run cells. Try to run the cell below!"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"import pandas as pd\n",
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"\n",
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"print \"Hi! This is a cell. Press the \u25b6 button above to run it\""
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],
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can also run a cell with Ctrl+Enter or Shift+Enter. Experiment a bit with that."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"One of the most useful things about IPython notebook is its tab completion. \n",
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"\n",
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"Try this: click just after read_csv( in the cell below and press tab 4 times, slowly"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"pd.read_csv("
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],
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"After the first time, you should see this:\n",
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"<div align=\"center\">\n",
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"<img src=\"files/images/tab-once.png\" width=\"75%\">\n",
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"</div>\n",
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"\n",
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"After the second time:\n",
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"<div align=\"center\">\n",
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"<img src=\"files/images/tab-twice.png\" width=\"75%\">\n",
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"</div>\n",
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"\n",
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"After the fourth time, a big help box should pop up at the bottom of the screen, with the full documentation for the `read_csv` function:\n",
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"<div align=\"center\">\n",
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"<img src=\"files/images/tab-4-times.png\" width=\"90%\">\n",
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"</div>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"I find this amazingly useful. I think of this as \"the more confused I am, the more times I should press tab\". Nothing bad will happen if you press tab 12 times.\n",
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"\n",
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"Okay, let's try tab completion for function names!"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"pd.r"
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],
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"language": "python",
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"metadata": {},
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You should see this:\n",
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"\n",
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"<div align=\"center\">\n",
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"<img src=\"files/images/function-completion.png\" width=\"30%\">\n",
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"</div>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Writing code"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Writing code in the notebook is pretty normal."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"def print_10_nums():\n",
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" for i in range(10):\n",
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" print i,"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 1
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"print_10_nums()"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"0 1 2 3 4 5 6 7 8 9\n"
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]
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}
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],
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"prompt_number": 2
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Saving"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As of the latest stable version, the notebook autosaves. You should use the latest stable version. Really."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Magic functions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"IPython has all kinds of magic functions. Here's an example of comparing `sum()` with a list comprehension to a generator comprehension using the `%time` magic."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%time sum([x for x in range(100000)])"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"CPU times: user 24 ms, sys: 4 ms, total: 28 ms\n",
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"Wall time: 27.4 ms\n"
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]
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},
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 3,
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"text": [
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"4999950000"
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]
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}
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],
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"prompt_number": 3
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%time sum(x for x in range(100000))"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"CPU times: user 8 ms, sys: 0 ns, total: 8 ms\n",
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"Wall time: 8.11 ms\n"
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]
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},
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 4,
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"text": [
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"4999950000"
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]
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}
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],
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"prompt_number": 4
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The magics I use most are `%time` and `%prun` for profiling. You can run `%magic` to get a list of all of them, and `%quickref` for a reference sheet."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%quickref"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 5
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can also do nutty things like run Perl code in the notebook with cell magics. This is especially cool for things like Cython code, where you can try out Cython really fast with the `%%cython` magic (you'll need to install it)."
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"%%perl\n",
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"\n",
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"$_ = \"whoa, python!\";\n",
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"s/python/perl/;\n",
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"print"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"whoa, perl!"
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]
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}
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],
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"prompt_number": 6
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"That's it for now!"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<style>\n",
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" @font-face {\n",
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" font-family: \"Computer Modern\";\n",
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" src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
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" }\n",
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" div.cell{\n",
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" width:800px;\n",
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" margin-left:16% !important;\n",
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" margin-right:auto;\n",
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" }\n",
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" h1 {\n",
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" font-family: Helvetica, serif;\n",
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" }\n",
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" h4{\n",
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" margin-top:12px;\n",
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" margin-bottom: 3px;\n",
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" }\n",
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" div.text_cell_render{\n",
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" font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
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" line-height: 145%;\n",
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" font-size: 130%;\n",
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" width:800px;\n",
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" margin-left:auto;\n",
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" margin-right:auto;\n",
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" }\n",
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" .CodeMirror{\n",
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" font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
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" }\n",
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" .text_cell_render h5 {\n",
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" font-weight: 300;\n",
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" font-size: 22pt;\n",
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" color: #4057A1;\n",
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" font-style: italic;\n",
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" margin-bottom: .5em;\n",
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" margin-top: 0.5em;\n",
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" display: block;\n",
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" }\n",
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" \n",
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" .warning{\n",
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" color: rgb( 240, 20, 20 )\n",
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" } "
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]
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}
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],
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"metadata": {}
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}
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]
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}

‎cookbook/images/function-completion.png‎

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‎cookbook/images/tab-4-times.png‎

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‎cookbook/images/tab-once.png‎

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‎cookbook/images/tab-twice.png‎

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