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1 .. image:: https://codecov.io/github/ipython/ipython/coverage.svg?branch=master
1 .. image:: https://codecov.io/github/ipython/ipython/coverage.svg?branch=master
2 :target: https://codecov.io/github/ipython/ipython?branch=master
2 :target: https://codecov.io/github/ipython/ipython?branch=master
3
3
4 .. image:: https://img.shields.io/pypi/dm/IPython.svg
4 .. image:: https://img.shields.io/pypi/dm/IPython.svg
5 :target: https://pypi.python.org/pypi/ipython
5 :target: https://pypi.python.org/pypi/ipython
6
6
7 .. image:: https://img.shields.io/pypi/v/IPython.svg
7 .. image:: https://img.shields.io/pypi/v/IPython.svg
8 :target: https://pypi.python.org/pypi/ipython
8 :target: https://pypi.python.org/pypi/ipython
9
9
10 .. image:: https://img.shields.io/travis/ipython/ipython.svg
10 .. image:: https://img.shields.io/travis/ipython/ipython.svg
11 :target: https://travis-ci.org/ipython/ipython
11 :target: https://travis-ci.org/ipython/ipython
12
12
13
13
14 ===========================================
14 ===========================================
15 IPython: Productive Interactive Computing
15 IPython: Productive Interactive Computing
16 ===========================================
16 ===========================================
17
17
18 Overview
18 Overview
19 ========
19 ========
20
20
21 Welcome to IPython. Our full documentation is available on `our website
21 Welcome to IPython. Our full documentation is available on `our website
22 <http://ipython.org/documentation.html>`_; if you downloaded a built source
22 <http://ipython.org/documentation.html>`_; if you downloaded a built source
23 distribution the ``docs/source`` directory contains the plaintext version of
23 distribution the ``docs/source`` directory contains the plaintext version of
24 these manuals. If you have Sphinx installed, you can build them by typing
24 these manuals. If you have Sphinx installed, you can build them by typing
25 ``cd docs; make html`` for local browsing.
25 ``cd docs; make html`` for local browsing.
26
26
27
27
28 See the `install page <http://ipython.org/install.html>`__ to install IPython.
28 See the `install page <http://ipython.org/install.html>`__ to install IPython.
29
29
30 The Notebook, Qt console and a number of other pieces are now parts of *Jupyter*.
30 The Notebook, Qt console and a number of other pieces are now parts of *Jupyter*.
31 See the `Jupyter installation docs <http://jupyter.readthedocs.org/en/latest/install.html>`__
31 See the `Jupyter installation docs <http://jupyter.readthedocs.io/en/latest/install.html>`__
32 if you want to use these.
32 if you want to use these.
33
33
34 Officially, IPython requires Python version 2.7, or 3.3 and above.
34 Officially, IPython requires Python version 2.7, or 3.3 and above.
35 IPython 1.x is the last IPython version to support Python 2.6 and 3.2.
35 IPython 1.x is the last IPython version to support Python 2.6 and 3.2.
36
36
37
37
38 Instant running
38 Instant running
39 ===============
39 ===============
40
40
41 You can run IPython from this directory without even installing it system-wide
41 You can run IPython from this directory without even installing it system-wide
42 by typing at the terminal::
42 by typing at the terminal::
43
43
44 $ python -m IPython
44 $ python -m IPython
45
45
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1 {
1 {
2 "cells": [
2 "cells": [
3 {
3 {
4 "cell_type": "markdown",
4 "cell_type": "markdown",
5 "metadata": {},
5 "metadata": {},
6 "source": [
6 "source": [
7 "# Third Party Libraries With Rich Output"
7 "# Third Party Libraries With Rich Output"
8 ]
8 ]
9 },
9 },
10 {
10 {
11 "cell_type": "markdown",
11 "cell_type": "markdown",
12 "metadata": {},
12 "metadata": {},
13 "source": [
13 "source": [
14 "A number of third party libraries defined their own custom display logic. This gives their objcts rich output by default when used in the Notebook."
14 "A number of third party libraries defined their own custom display logic. This gives their objcts rich output by default when used in the Notebook."
15 ]
15 ]
16 },
16 },
17 {
17 {
18 "cell_type": "code",
18 "cell_type": "code",
19 "execution_count": 1,
19 "execution_count": 1,
20 "metadata": {
20 "metadata": {
21 "collapsed": false
21 "collapsed": false
22 },
22 },
23 "outputs": [],
23 "outputs": [],
24 "source": [
24 "source": [
25 "from IPython.display import display"
25 "from IPython.display import display"
26 ]
26 ]
27 },
27 },
28 {
28 {
29 "cell_type": "markdown",
29 "cell_type": "markdown",
30 "metadata": {},
30 "metadata": {},
31 "source": [
31 "source": [
32 "## Pandas"
32 "## Pandas"
33 ]
33 ]
34 },
34 },
35 {
35 {
36 "cell_type": "markdown",
36 "cell_type": "markdown",
37 "metadata": {},
37 "metadata": {},
38 "source": [
38 "source": [
39 "[Pandas](http://pandas.pydata.org/) is a data analysis library for Python. Its `DataFrame` objects have an HTML table representation in the Notebook."
39 "[Pandas](http://pandas.pydata.org/) is a data analysis library for Python. Its `DataFrame` objects have an HTML table representation in the Notebook."
40 ]
40 ]
41 },
41 },
42 {
42 {
43 "cell_type": "code",
43 "cell_type": "code",
44 "execution_count": 2,
44 "execution_count": 2,
45 "metadata": {
45 "metadata": {
46 "collapsed": false
46 "collapsed": false
47 },
47 },
48 "outputs": [],
48 "outputs": [],
49 "source": [
49 "source": [
50 "import pandas"
50 "import pandas"
51 ]
51 ]
52 },
52 },
53 {
53 {
54 "cell_type": "markdown",
54 "cell_type": "markdown",
55 "metadata": {},
55 "metadata": {},
56 "source": [
56 "source": [
57 "Here is a small amount of stock data for APPL:"
57 "Here is a small amount of stock data for APPL:"
58 ]
58 ]
59 },
59 },
60 {
60 {
61 "cell_type": "code",
61 "cell_type": "code",
62 "execution_count": 3,
62 "execution_count": 3,
63 "metadata": {
63 "metadata": {
64 "collapsed": false
64 "collapsed": false
65 },
65 },
66 "outputs": [
66 "outputs": [
67 {
67 {
68 "name": "stdout",
68 "name": "stdout",
69 "output_type": "stream",
69 "output_type": "stream",
70 "text": [
70 "text": [
71 "Writing data.csv\n"
71 "Writing data.csv\n"
72 ]
72 ]
73 }
73 }
74 ],
74 ],
75 "source": [
75 "source": [
76 "%%writefile data.csv\n",
76 "%%writefile data.csv\n",
77 "Date,Open,High,Low,Close,Volume,Adj Close\n",
77 "Date,Open,High,Low,Close,Volume,Adj Close\n",
78 "2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n",
78 "2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n",
79 "2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n",
79 "2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n",
80 "2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n",
80 "2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n",
81 "2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n",
81 "2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n",
82 "2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n",
82 "2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n",
83 "2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53"
83 "2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53"
84 ]
84 ]
85 },
85 },
86 {
86 {
87 "cell_type": "markdown",
87 "cell_type": "markdown",
88 "metadata": {},
88 "metadata": {},
89 "source": [
89 "source": [
90 "Read this as into a `DataFrame`:"
90 "Read this as into a `DataFrame`:"
91 ]
91 ]
92 },
92 },
93 {
93 {
94 "cell_type": "code",
94 "cell_type": "code",
95 "execution_count": 4,
95 "execution_count": 4,
96 "metadata": {
96 "metadata": {
97 "collapsed": false
97 "collapsed": false
98 },
98 },
99 "outputs": [],
99 "outputs": [],
100 "source": [
100 "source": [
101 "df = pandas.read_csv('data.csv')"
101 "df = pandas.read_csv('data.csv')"
102 ]
102 ]
103 },
103 },
104 {
104 {
105 "cell_type": "markdown",
105 "cell_type": "markdown",
106 "metadata": {},
106 "metadata": {},
107 "source": [
107 "source": [
108 "And view the HTML representation:"
108 "And view the HTML representation:"
109 ]
109 ]
110 },
110 },
111 {
111 {
112 "cell_type": "code",
112 "cell_type": "code",
113 "execution_count": 5,
113 "execution_count": 5,
114 "metadata": {
114 "metadata": {
115 "collapsed": false
115 "collapsed": false
116 },
116 },
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117 "outputs": [
118 {
118 {
119 "data": {
119 "data": {
120 "text/html": [
120 "text/html": [
121 "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
121 "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
122 "<table border=\"1\" class=\"dataframe\">\n",
122 "<table border=\"1\" class=\"dataframe\">\n",
123 " <thead>\n",
123 " <thead>\n",
124 " <tr style=\"text-align: right;\">\n",
124 " <tr style=\"text-align: right;\">\n",
125 " <th></th>\n",
125 " <th></th>\n",
126 " <th>Date</th>\n",
126 " <th>Date</th>\n",
127 " <th>Open</th>\n",
127 " <th>Open</th>\n",
128 " <th>High</th>\n",
128 " <th>High</th>\n",
129 " <th>Low</th>\n",
129 " <th>Low</th>\n",
130 " <th>Close</th>\n",
130 " <th>Close</th>\n",
131 " <th>Volume</th>\n",
131 " <th>Volume</th>\n",
132 " <th>Adj Close</th>\n",
132 " <th>Adj Close</th>\n",
133 " </tr>\n",
133 " </tr>\n",
134 " </thead>\n",
134 " </thead>\n",
135 " <tbody>\n",
135 " <tbody>\n",
136 " <tr>\n",
136 " <tr>\n",
137 " <th>0</th>\n",
137 " <th>0</th>\n",
138 " <td> 2012-06-01</td>\n",
138 " <td> 2012-06-01</td>\n",
139 " <td> 569.16</td>\n",
139 " <td> 569.16</td>\n",
140 " <td> 590.00</td>\n",
140 " <td> 590.00</td>\n",
141 " <td> 548.50</td>\n",
141 " <td> 548.50</td>\n",
142 " <td> 584.00</td>\n",
142 " <td> 584.00</td>\n",
143 " <td> 14077000</td>\n",
143 " <td> 14077000</td>\n",
144 " <td> 581.50</td>\n",
144 " <td> 581.50</td>\n",
145 " </tr>\n",
145 " </tr>\n",
146 " <tr>\n",
146 " <tr>\n",
147 " <th>1</th>\n",
147 " <th>1</th>\n",
148 " <td> 2012-05-01</td>\n",
148 " <td> 2012-05-01</td>\n",
149 " <td> 584.90</td>\n",
149 " <td> 584.90</td>\n",
150 " <td> 596.76</td>\n",
150 " <td> 596.76</td>\n",
151 " <td> 522.18</td>\n",
151 " <td> 522.18</td>\n",
152 " <td> 577.73</td>\n",
152 " <td> 577.73</td>\n",
153 " <td> 18827900</td>\n",
153 " <td> 18827900</td>\n",
154 " <td> 575.26</td>\n",
154 " <td> 575.26</td>\n",
155 " </tr>\n",
155 " </tr>\n",
156 " <tr>\n",
156 " <tr>\n",
157 " <th>2</th>\n",
157 " <th>2</th>\n",
158 " <td> 2012-04-02</td>\n",
158 " <td> 2012-04-02</td>\n",
159 " <td> 601.83</td>\n",
159 " <td> 601.83</td>\n",
160 " <td> 644.00</td>\n",
160 " <td> 644.00</td>\n",
161 " <td> 555.00</td>\n",
161 " <td> 555.00</td>\n",
162 " <td> 583.98</td>\n",
162 " <td> 583.98</td>\n",
163 " <td> 28759100</td>\n",
163 " <td> 28759100</td>\n",
164 " <td> 581.48</td>\n",
164 " <td> 581.48</td>\n",
165 " </tr>\n",
165 " </tr>\n",
166 " <tr>\n",
166 " <tr>\n",
167 " <th>3</th>\n",
167 " <th>3</th>\n",
168 " <td> 2012-03-01</td>\n",
168 " <td> 2012-03-01</td>\n",
169 " <td> 548.17</td>\n",
169 " <td> 548.17</td>\n",
170 " <td> 621.45</td>\n",
170 " <td> 621.45</td>\n",
171 " <td> 516.22</td>\n",
171 " <td> 516.22</td>\n",
172 " <td> 599.55</td>\n",
172 " <td> 599.55</td>\n",
173 " <td> 26486000</td>\n",
173 " <td> 26486000</td>\n",
174 " <td> 596.99</td>\n",
174 " <td> 596.99</td>\n",
175 " </tr>\n",
175 " </tr>\n",
176 " <tr>\n",
176 " <tr>\n",
177 " <th>4</th>\n",
177 " <th>4</th>\n",
178 " <td> 2012-02-01</td>\n",
178 " <td> 2012-02-01</td>\n",
179 " <td> 458.41</td>\n",
179 " <td> 458.41</td>\n",
180 " <td> 547.61</td>\n",
180 " <td> 547.61</td>\n",
181 " <td> 453.98</td>\n",
181 " <td> 453.98</td>\n",
182 " <td> 542.44</td>\n",
182 " <td> 542.44</td>\n",
183 " <td> 22001000</td>\n",
183 " <td> 22001000</td>\n",
184 " <td> 540.12</td>\n",
184 " <td> 540.12</td>\n",
185 " </tr>\n",
185 " </tr>\n",
186 " <tr>\n",
186 " <tr>\n",
187 " <th>5</th>\n",
187 " <th>5</th>\n",
188 " <td> 2012-01-03</td>\n",
188 " <td> 2012-01-03</td>\n",
189 " <td> 409.40</td>\n",
189 " <td> 409.40</td>\n",
190 " <td> 458.24</td>\n",
190 " <td> 458.24</td>\n",
191 " <td> 409.00</td>\n",
191 " <td> 409.00</td>\n",
192 " <td> 456.48</td>\n",
192 " <td> 456.48</td>\n",
193 " <td> 12949100</td>\n",
193 " <td> 12949100</td>\n",
194 " <td> 454.53</td>\n",
194 " <td> 454.53</td>\n",
195 " </tr>\n",
195 " </tr>\n",
196 " </tbody>\n",
196 " </tbody>\n",
197 "</table>\n",
197 "</table>\n",
198 "</div>"
198 "</div>"
199 ],
199 ],
200 "text/plain": [
200 "text/plain": [
201 " Date Open High Low Close Volume Adj Close\n",
201 " Date Open High Low Close Volume Adj Close\n",
202 "0 2012-06-01 569.16 590.00 548.50 584.00 14077000 581.50\n",
202 "0 2012-06-01 569.16 590.00 548.50 584.00 14077000 581.50\n",
203 "1 2012-05-01 584.90 596.76 522.18 577.73 18827900 575.26\n",
203 "1 2012-05-01 584.90 596.76 522.18 577.73 18827900 575.26\n",
204 "2 2012-04-02 601.83 644.00 555.00 583.98 28759100 581.48\n",
204 "2 2012-04-02 601.83 644.00 555.00 583.98 28759100 581.48\n",
205 "3 2012-03-01 548.17 621.45 516.22 599.55 26486000 596.99\n",
205 "3 2012-03-01 548.17 621.45 516.22 599.55 26486000 596.99\n",
206 "4 2012-02-01 458.41 547.61 453.98 542.44 22001000 540.12\n",
206 "4 2012-02-01 458.41 547.61 453.98 542.44 22001000 540.12\n",
207 "5 2012-01-03 409.40 458.24 409.00 456.48 12949100 454.53"
207 "5 2012-01-03 409.40 458.24 409.00 456.48 12949100 454.53"
208 ]
208 ]
209 },
209 },
210 "execution_count": 5,
210 "execution_count": 5,
211 "metadata": {},
211 "metadata": {},
212 "output_type": "execute_result"
212 "output_type": "execute_result"
213 }
213 }
214 ],
214 ],
215 "source": [
215 "source": [
216 "df"
216 "df"
217 ]
217 ]
218 },
218 },
219 {
219 {
220 "cell_type": "markdown",
220 "cell_type": "markdown",
221 "metadata": {},
221 "metadata": {},
222 "source": [
222 "source": [
223 "## SymPy"
223 "## SymPy"
224 ]
224 ]
225 },
225 },
226 {
226 {
227 "cell_type": "markdown",
227 "cell_type": "markdown",
228 "metadata": {},
228 "metadata": {},
229 "source": [
229 "source": [
230 "[SymPy](http://sympy.org/) is a symbolic computing library for Python. Its equation objects have LaTeX representations that are rendered in the Notebook."
230 "[SymPy](http://sympy.org/) is a symbolic computing library for Python. Its equation objects have LaTeX representations that are rendered in the Notebook."
231 ]
231 ]
232 },
232 },
233 {
233 {
234 "cell_type": "code",
234 "cell_type": "code",
235 "execution_count": 6,
235 "execution_count": 6,
236 "metadata": {
236 "metadata": {
237 "collapsed": false
237 "collapsed": false
238 },
238 },
239 "outputs": [],
239 "outputs": [],
240 "source": [
240 "source": [
241 "from sympy.interactive.printing import init_printing\n",
241 "from sympy.interactive.printing import init_printing\n",
242 "init_printing(use_latex='mathjax')"
242 "init_printing(use_latex='mathjax')"
243 ]
243 ]
244 },
244 },
245 {
245 {
246 "cell_type": "code",
246 "cell_type": "code",
247 "execution_count": 7,
247 "execution_count": 7,
248 "metadata": {
248 "metadata": {
249 "collapsed": false
249 "collapsed": false
250 },
250 },
251 "outputs": [],
251 "outputs": [],
252 "source": [
252 "source": [
253 "from __future__ import division\n",
253 "from __future__ import division\n",
254 "import sympy as sym\n",
254 "import sympy as sym\n",
255 "from sympy import *\n",
255 "from sympy import *\n",
256 "x, y, z = symbols(\"x y z\")\n",
256 "x, y, z = symbols(\"x y z\")\n",
257 "k, m, n = symbols(\"k m n\", integer=True)\n",
257 "k, m, n = symbols(\"k m n\", integer=True)\n",
258 "f, g, h = map(Function, 'fgh')"
258 "f, g, h = map(Function, 'fgh')"
259 ]
259 ]
260 },
260 },
261 {
261 {
262 "cell_type": "code",
262 "cell_type": "code",
263 "execution_count": 8,
263 "execution_count": 8,
264 "metadata": {
264 "metadata": {
265 "collapsed": false
265 "collapsed": false
266 },
266 },
267 "outputs": [
267 "outputs": [
268 {
268 {
269 "data": {
269 "data": {
270 "text/latex": [
270 "text/latex": [
271 "$$\\frac{3 \\pi}{2} + \\frac{e^{i x}}{x^{2} + y}$$"
271 "$$\\frac{3 \\pi}{2} + \\frac{e^{i x}}{x^{2} + y}$$"
272 ],
272 ],
273 "text/plain": [
273 "text/plain": [
274 " β…ˆβ‹…x \n",
274 " β…ˆβ‹…x \n",
275 "3β‹…Ο€ β„― \n",
275 "3β‹…Ο€ β„― \n",
276 "─── + ──────\n",
276 "─── + ──────\n",
277 " 2 2 \n",
277 " 2 2 \n",
278 " x + y"
278 " x + y"
279 ]
279 ]
280 },
280 },
281 "execution_count": 8,
281 "execution_count": 8,
282 "metadata": {},
282 "metadata": {},
283 "output_type": "execute_result"
283 "output_type": "execute_result"
284 }
284 }
285 ],
285 ],
286 "source": [
286 "source": [
287 "Rational(3,2)*pi + exp(I*x) / (x**2 + y)"
287 "Rational(3,2)*pi + exp(I*x) / (x**2 + y)"
288 ]
288 ]
289 },
289 },
290 {
290 {
291 "cell_type": "code",
291 "cell_type": "code",
292 "execution_count": 9,
292 "execution_count": 9,
293 "metadata": {
293 "metadata": {
294 "collapsed": false
294 "collapsed": false
295 },
295 },
296 "outputs": [
296 "outputs": [
297 {
297 {
298 "data": {
298 "data": {
299 "text/latex": [
299 "text/latex": [
300 "$$\\frac{1}{x} \\left(x \\sin{\\left (x \\right )} - 1\\right) + \\frac{1}{x}$$"
300 "$$\\frac{1}{x} \\left(x \\sin{\\left (x \\right )} - 1\\right) + \\frac{1}{x}$$"
301 ],
301 ],
302 "text/plain": [
302 "text/plain": [
303 "xβ‹…sin(x) - 1 1\n",
303 "xβ‹…sin(x) - 1 1\n",
304 "──────────── + ─\n",
304 "──────────── + ─\n",
305 " x x"
305 " x x"
306 ]
306 ]
307 },
307 },
308 "execution_count": 9,
308 "execution_count": 9,
309 "metadata": {},
309 "metadata": {},
310 "output_type": "execute_result"
310 "output_type": "execute_result"
311 }
311 }
312 ],
312 ],
313 "source": [
313 "source": [
314 "a = 1/x + (x*sin(x) - 1)/x\n",
314 "a = 1/x + (x*sin(x) - 1)/x\n",
315 "a"
315 "a"
316 ]
316 ]
317 },
317 },
318 {
318 {
319 "cell_type": "code",
319 "cell_type": "code",
320 "execution_count": 10,
320 "execution_count": 10,
321 "metadata": {
321 "metadata": {
322 "collapsed": false
322 "collapsed": false
323 },
323 },
324 "outputs": [
324 "outputs": [
325 {
325 {
326 "data": {
326 "data": {
327 "text/latex": [
327 "text/latex": [
328 "$$1 + \\frac{x^{2}}{2} + \\frac{5 x^{4}}{24} + \\mathcal{O}\\left(x^{6}\\right)$$"
328 "$$1 + \\frac{x^{2}}{2} + \\frac{5 x^{4}}{24} + \\mathcal{O}\\left(x^{6}\\right)$$"
329 ],
329 ],
330 "text/plain": [
330 "text/plain": [
331 " 2 4 \n",
331 " 2 4 \n",
332 " x 5β‹…x βŽ› 6⎞\n",
332 " x 5β‹…x βŽ› 6⎞\n",
333 "1 + ── + ──── + O⎝x ⎠\n",
333 "1 + ── + ──── + O⎝x ⎠\n",
334 " 2 24 "
334 " 2 24 "
335 ]
335 ]
336 },
336 },
337 "execution_count": 10,
337 "execution_count": 10,
338 "metadata": {},
338 "metadata": {},
339 "output_type": "execute_result"
339 "output_type": "execute_result"
340 }
340 }
341 ],
341 ],
342 "source": [
342 "source": [
343 "(1/cos(x)).series(x, 0, 6)"
343 "(1/cos(x)).series(x, 0, 6)"
344 ]
344 ]
345 },
345 },
346 {
346 {
347 "cell_type": "markdown",
347 "cell_type": "markdown",
348 "metadata": {},
348 "metadata": {},
349 "source": [
349 "source": [
350 "## Vincent"
350 "## Vincent"
351 ]
351 ]
352 },
352 },
353 {
353 {
354 "cell_type": "markdown",
354 "cell_type": "markdown",
355 "metadata": {},
355 "metadata": {},
356 "source": [
356 "source": [
357 "[Vincent](https://vincent.readthedocs.org/en/latest/) is a visualization library that uses the [Vega](http://trifacta.github.io/vega/) visualization grammar to build [d3.js](http://d3js.org/) based visualizations in the Notebook and on http://nbviewer.ipython.org. `Visualization` objects in Vincetn have rich HTML and JavaSrcript representations."
357 "[Vincent](https://vincent.readthedocs.io/en/latest/) is a visualization library that uses the [Vega](http://trifacta.github.io/vega/) visualization grammar to build [d3.js](http://d3js.org/) based visualizations in the Notebook and on http://nbviewer.ipython.org. `Visualization` objects in Vincetn have rich HTML and JavaSrcript representations."
358 ]
358 ]
359 },
359 },
360 {
360 {
361 "cell_type": "code",
361 "cell_type": "code",
362 "execution_count": 11,
362 "execution_count": 11,
363 "metadata": {
363 "metadata": {
364 "collapsed": false
364 "collapsed": false
365 },
365 },
366 "outputs": [],
366 "outputs": [],
367 "source": [
367 "source": [
368 "import vincent\n",
368 "import vincent\n",
369 "import pandas as pd"
369 "import pandas as pd"
370 ]
370 ]
371 },
371 },
372 {
372 {
373 "cell_type": "code",
373 "cell_type": "code",
374 "execution_count": 12,
374 "execution_count": 12,
375 "metadata": {
375 "metadata": {
376 "collapsed": false
376 "collapsed": false
377 },
377 },
378 "outputs": [],
378 "outputs": [],
379 "source": [
379 "source": [
380 "import pandas.io.data as web\n",
380 "import pandas.io.data as web\n",
381 "import datetime\n",
381 "import datetime\n",
382 "all_data = {}\n",
382 "all_data = {}\n",
383 "date_start = datetime.datetime(2010, 1, 1)\n",
383 "date_start = datetime.datetime(2010, 1, 1)\n",
384 "date_end = datetime.datetime(2014, 1, 1)\n",
384 "date_end = datetime.datetime(2014, 1, 1)\n",
385 "for ticker in ['AAPL', 'IBM', 'YHOO', 'MSFT']:\n",
385 "for ticker in ['AAPL', 'IBM', 'YHOO', 'MSFT']:\n",
386 " all_data[ticker] = web.DataReader(ticker, 'yahoo', date_start, date_end)\n",
386 " all_data[ticker] = web.DataReader(ticker, 'yahoo', date_start, date_end)\n",
387 "price = pd.DataFrame({tic: data['Adj Close']\n",
387 "price = pd.DataFrame({tic: data['Adj Close']\n",
388 " for tic, data in all_data.items()})"
388 " for tic, data in all_data.items()})"
389 ]
389 ]
390 },
390 },
391 {
391 {
392 "cell_type": "code",
392 "cell_type": "code",
393 "execution_count": 13,
393 "execution_count": 13,
394 "metadata": {
394 "metadata": {
395 "collapsed": false
395 "collapsed": false
396 },
396 },
397 "outputs": [
397 "outputs": [
398 {
398 {
399 "data": {
399 "data": {
400 "text/html": [
400 "text/html": [
401 "\n",
401 "\n",
402 " <script>\n",
402 " <script>\n",
403 " \n",
403 " \n",
404 " function vct_load_lib(url, callback){\n",
404 " function vct_load_lib(url, callback){\n",
405 " if(typeof d3 !== 'undefined' &&\n",
405 " if(typeof d3 !== 'undefined' &&\n",
406 " url === 'http://d3js.org/d3.v3.min.js'){\n",
406 " url === 'http://d3js.org/d3.v3.min.js'){\n",
407 " callback()\n",
407 " callback()\n",
408 " }\n",
408 " }\n",
409 " var s = document.createElement('script');\n",
409 " var s = document.createElement('script');\n",
410 " s.src = url;\n",
410 " s.src = url;\n",
411 " s.async = true;\n",
411 " s.async = true;\n",
412 " s.onreadystatechange = s.onload = callback;\n",
412 " s.onreadystatechange = s.onload = callback;\n",
413 " s.onerror = function(){\n",
413 " s.onerror = function(){\n",
414 " console.warn(\"failed to load library \" + url);\n",
414 " console.warn(\"failed to load library \" + url);\n",
415 " };\n",
415 " };\n",
416 " document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
416 " document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
417 " };\n",
417 " };\n",
418 " var vincent_event = new CustomEvent(\n",
418 " var vincent_event = new CustomEvent(\n",
419 " \"vincent_libs_loaded\",\n",
419 " \"vincent_libs_loaded\",\n",
420 " {bubbles: true, cancelable: true}\n",
420 " {bubbles: true, cancelable: true}\n",
421 " );\n",
421 " );\n",
422 " \n",
422 " \n",
423 " function load_all_libs(){\n",
423 " function load_all_libs(){\n",
424 " console.log('Loading Vincent libs...')\n",
424 " console.log('Loading Vincent libs...')\n",
425 " vct_load_lib('http://d3js.org/d3.v3.min.js', function(){\n",
425 " vct_load_lib('http://d3js.org/d3.v3.min.js', function(){\n",
426 " vct_load_lib('http://d3js.org/d3.geo.projection.v0.min.js', function(){\n",
426 " vct_load_lib('http://d3js.org/d3.geo.projection.v0.min.js', function(){\n",
427 " vct_load_lib('http://wrobstory.github.io/d3-cloud/d3.layout.cloud.js', function(){\n",
427 " vct_load_lib('http://wrobstory.github.io/d3-cloud/d3.layout.cloud.js', function(){\n",
428 " vct_load_lib('http://wrobstory.github.io/vega/vega.v1.3.3.js', function(){\n",
428 " vct_load_lib('http://wrobstory.github.io/vega/vega.v1.3.3.js', function(){\n",
429 " window.dispatchEvent(vincent_event);\n",
429 " window.dispatchEvent(vincent_event);\n",
430 " });\n",
430 " });\n",
431 " });\n",
431 " });\n",
432 " });\n",
432 " });\n",
433 " });\n",
433 " });\n",
434 " };\n",
434 " };\n",
435 " if(typeof define === \"function\" && define.amd){\n",
435 " if(typeof define === \"function\" && define.amd){\n",
436 " if (window['d3'] === undefined ||\n",
436 " if (window['d3'] === undefined ||\n",
437 " window['topojson'] === undefined){\n",
437 " window['topojson'] === undefined){\n",
438 " require.config(\n",
438 " require.config(\n",
439 " {paths: {\n",
439 " {paths: {\n",
440 " d3: 'http://d3js.org/d3.v3.min',\n",
440 " d3: 'http://d3js.org/d3.v3.min',\n",
441 " topojson: 'http://d3js.org/topojson.v1.min'\n",
441 " topojson: 'http://d3js.org/topojson.v1.min'\n",
442 " }\n",
442 " }\n",
443 " }\n",
443 " }\n",
444 " );\n",
444 " );\n",
445 " require([\"d3\"], function(d3){\n",
445 " require([\"d3\"], function(d3){\n",
446 " console.log('Loading Vincent from require.js...')\n",
446 " console.log('Loading Vincent from require.js...')\n",
447 " window.d3 = d3;\n",
447 " window.d3 = d3;\n",
448 " require([\"topojson\"], function(topojson){\n",
448 " require([\"topojson\"], function(topojson){\n",
449 " window.topojson = topojson;\n",
449 " window.topojson = topojson;\n",
450 " load_all_libs();\n",
450 " load_all_libs();\n",
451 " });\n",
451 " });\n",
452 " });\n",
452 " });\n",
453 " } else {\n",
453 " } else {\n",
454 " load_all_libs();\n",
454 " load_all_libs();\n",
455 " };\n",
455 " };\n",
456 " }else{\n",
456 " }else{\n",
457 " console.log('Require.js not found, loading manually...')\n",
457 " console.log('Require.js not found, loading manually...')\n",
458 " load_all_libs();\n",
458 " load_all_libs();\n",
459 " };\n",
459 " };\n",
460 "\n",
460 "\n",
461 " </script>"
461 " </script>"
462 ],
462 ],
463 "text/plain": [
463 "text/plain": [
464 "<IPython.core.display.HTML object>"
464 "<IPython.core.display.HTML object>"
465 ]
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466 },
466 },
467 "metadata": {},
467 "metadata": {},
468 "output_type": "display_data"
468 "output_type": "display_data"
469 }
469 }
470 ],
470 ],
471 "source": [
471 "source": [
472 "vincent.initialize_notebook()"
472 "vincent.initialize_notebook()"
473 ]
473 ]
474 },
474 },
475 {
475 {
476 "cell_type": "code",
476 "cell_type": "code",
477 "execution_count": 14,
477 "execution_count": 14,
478 "metadata": {
478 "metadata": {
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480 },
481 "outputs": [
481 "outputs": [
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485 "<div id=\"vise33c59d182bd4093bad74a04ddf24501\"></div>\n",
485 "<div id=\"vise33c59d182bd4093bad74a04ddf24501\"></div>\n",
486 "<script>\n",
486 "<script>\n",
487 " ( function() {\n",
487 " ( function() {\n",
488 " var _do_plot = function() {\n",
488 " var _do_plot = function() {\n",
489 " if (typeof vg === 'undefined') {\n",
489 " if (typeof vg === 'undefined') {\n",
490 " window.addEventListener('vincent_libs_loaded', _do_plot)\n",
490 " window.addEventListener('vincent_libs_loaded', _do_plot)\n",
491 " return;\n",
491 " return;\n",
492 " }\n",
492 " }\n",
493 " vg.parse.spec({\"axes\": [{\"scale\": \"x\", \"title\": \"Date\", \"type\": \"x\"}, {\"scale\": \"y\", \"title\": \"Price\", \"type\": \"y\"}], \"data\": [{\"name\": \"table\", \"values\": [{\"col\": \"AAPL\", \"idx\": 1262592000000, \"val\": 28.84}, {\"col\": \"IBM\", \"idx\": 1262592000000, \"val\": 119.53}, {\"col\": \"YHOO\", \"idx\": 1262592000000, \"val\": 17.1}, {\"col\": \"MSFT\", \"idx\": 1262592000000, \"val\": 26.94}, {\"col\": \"AAPL\", \"idx\": 1262678400000, \"val\": 28.89}, {\"col\": \"IBM\", \"idx\": 1262678400000, \"val\": 118.09}, {\"col\": \"YHOO\", \"idx\": 1262678400000, \"val\": 17.23}, {\"col\": \"MSFT\", \"idx\": 1262678400000, \"val\": 26.95}, {\"col\": \"AAPL\", \"idx\": 1262764800000, \"val\": 28.43}, {\"col\": \"IBM\", \"idx\": 1262764800000, \"val\": 117.32}, {\"col\": \"YHOO\", \"idx\": 1262764800000, \"val\": 17.17}, {\"col\": \"MSFT\", \"idx\": 1262764800000, \"val\": 26.79}, {\"col\": \"AAPL\", \"idx\": 1262851200000, \"val\": 28.38}, {\"col\": 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36.04}, {\"col\": \"AAPL\", \"idx\": 1388476800000, \"val\": 78.19}, {\"col\": \"IBM\", \"idx\": 1388476800000, \"val\": 181.85}, {\"col\": \"YHOO\", \"idx\": 1388476800000, \"val\": 40.44}, {\"col\": \"MSFT\", \"idx\": 1388476800000, \"val\": 36.16}]}], \"height\": 300, \"legends\": [{\"fill\": \"color\", \"offset\": 0, \"properties\": {}, \"title\": \"Ticker\"}], \"marks\": [{\"from\": {\"data\": \"table\", \"transform\": [{\"keys\": [\"data.col\"], \"type\": \"facet\"}]}, \"marks\": [{\"properties\": {\"enter\": {\"stroke\": {\"field\": \"data.col\", \"scale\": \"color\"}, \"strokeWidth\": {\"value\": 2}, \"x\": {\"field\": \"data.idx\", \"scale\": \"x\"}, \"y\": {\"field\": \"data.val\", \"scale\": \"y\"}}}, \"type\": \"line\"}], \"type\": \"group\"}], \"padding\": \"auto\", \"scales\": [{\"domain\": {\"data\": \"table\", \"field\": \"data.idx\"}, \"name\": \"x\", \"range\": \"width\", \"type\": \"time\"}, {\"domain\": {\"data\": \"table\", \"field\": \"data.val\"}, \"name\": \"y\", \"nice\": true, \"range\": \"height\"}, {\"domain\": {\"data\": \"table\", \"field\": \"data.col\"}, \"name\": \"color\", \"range\": \"category20\", \"type\": \"ordinal\"}], \"width\": 600}, function(chart) {\n",
494 " chart({el: \"#vise33c59d182bd4093bad74a04ddf24501\"}).update();\n",
494 " chart({el: \"#vise33c59d182bd4093bad74a04ddf24501\"}).update();\n",
495 " });\n",
495 " });\n",
496 " };\n",
496 " };\n",
497 " _do_plot();\n",
497 " _do_plot();\n",
498 " })();\n",
498 " })();\n",
499 "</script>\n",
499 "</script>\n",
500 "<style>.vega canvas {width: 100%;}</style>\n",
500 "<style>.vega canvas {width: 100%;}</style>\n",
501 " "
501 " "
502 ],
502 ],
503 "text/plain": [
503 "text/plain": [
504 "<vincent.charts.Line at 0x107badb38>"
504 "<vincent.charts.Line at 0x107badb38>"
505 ]
505 ]
506 },
506 },
507 "metadata": {},
507 "metadata": {},
508 "output_type": "display_data"
508 "output_type": "display_data"
509 }
509 }
510 ],
510 ],
511 "source": [
511 "source": [
512 "line = vincent.Line(price[['AAPL', 'IBM', 'YHOO', 'MSFT']], width=600, height=300)\n",
512 "line = vincent.Line(price[['AAPL', 'IBM', 'YHOO', 'MSFT']], width=600, height=300)\n",
513 "line.axis_titles(x='Date', y='Price')\n",
513 "line.axis_titles(x='Date', y='Price')\n",
514 "line.legend(title='Ticker')\n",
514 "line.legend(title='Ticker')\n",
515 "display(line)"
515 "display(line)"
516 ]
516 ]
517 }
517 }
518 ],
518 ],
519 "metadata": {
519 "metadata": {
520 "kernelspec": {
520 "kernelspec": {
521 "display_name": "Python 3",
521 "display_name": "Python 3",
522 "language": "python",
522 "language": "python",
523 "name": "python3"
523 "name": "python3"
524 },
524 },
525 "language_info": {
525 "language_info": {
526 "codemirror_mode": {
526 "codemirror_mode": {
527 "name": "ipython",
527 "name": "ipython",
528 "version": 3
528 "version": 3
529 },
529 },
530 "file_extension": ".py",
530 "file_extension": ".py",
531 "mimetype": "text/x-python",
531 "mimetype": "text/x-python",
532 "name": "python",
532 "name": "python",
533 "nbconvert_exporter": "python",
533 "nbconvert_exporter": "python",
534 "pygments_lexer": "ipython3",
534 "pygments_lexer": "ipython3",
535 "version": "3.4.2"
535 "version": "3.4.2"
536 }
536 }
537 },
537 },
538 "nbformat": 4,
538 "nbformat": 4,
539 "nbformat_minor": 0
539 "nbformat_minor": 0
540 }
540 }
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