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ICBacon/Bokeh Plot Interacts with the Jupyter Notebook-checkpoint.ipynb

Created September 26, 2016 16:37
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Bokeh Plots in a Jupyter Notebook Using Iris Flower Data from Tony
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Bokeh Plot Interacts with the Jupyter Notebook-checkpoint.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"> Do you actually know what Fisher's Iris flowers look like?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Click on point the plot to learn a bit more."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import bokeh\n",
"from bokeh.charts import Scatter, vplot, output_server, output_notebook, show #cursession\n",
"from bokeh.sampledata import iris\n",
"from IPython.display import Javascript\n",
"import json\n",
"import pandas"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <div class=\"bk-root\">\n",
" <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
" <span id=\"20e29250-5c22-40c2-a7cb-99fa41aaeb36\">Loading BokehJS ...</span>\n",
" </div>"
]
},
"metadata": {},
"output_type": "display_data"
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{
"data": {
"application/javascript": [
"\n",
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" }\n",
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"\n",
" \n",
" if (typeof (window._bokeh_timeout) === \"undefined\" || force !== \"\") {\n",
" window._bokeh_timeout = Date.now() + 5000;\n",
" window._bokeh_failed_load = false;\n",
" }\n",
"\n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
"\n",
" function display_loaded() {\n",
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" Bokeh.$(\"#20e29250-5c22-40c2-a7cb-99fa41aaeb36\").text(\"BokehJS successfully loaded.\");\n",
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"\n",
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" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
"\n",
" function load_libs(js_urls, callback) {\n",
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" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
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" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
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" }\n",
" };var element = document.getElementById(\"20e29250-5c22-40c2-a7cb-99fa41aaeb36\");\n",
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" return false;\n",
" }\n",
"\n",
" var js_urls = ['https://cdn.pydata.org/bokeh/release/bokeh-0.12.2.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.2.min.js', 'https://cdn.pydata.org/bokeh/release/bokeh-compiler-0.12.2.min.js'];\n",
"\n",
" var inline_js = [\n",
" function(Bokeh) {\n",
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" \n",
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" \n",
" Bokeh.$(\"#20e29250-5c22-40c2-a7cb-99fa41aaeb36\").text(\"BokehJS is loading...\");\n",
" },\n",
" function(Bokeh) {\n",
" console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.2.min.css\");\n",
" Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.2.min.css\");\n",
" console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.2.min.css\");\n",
" Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.2.min.css\");\n",
" }\n",
" ];\n",
"\n",
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" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
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" }\n",
"\n",
" }\n",
"\n",
" if (window._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
"}(this));"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = iris.flowers\n",
"#output_server('update')\n",
"output_notebook()\n",
"gb = df.groupby('species').describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"> Store the groupby tables for later"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"application/javascript": [
"window.tables = {\"versicolor\": \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th></th>\\n <th>petal_length</th>\\n <th>petal_width</th>\\n <th>sepal_length</th>\\n <th>sepal_width</th>\\n </tr>\\n <tr>\\n <th>species</th>\\n <th></th>\\n <th></th>\\n <th></th>\\n <th></th>\\n <th></th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th rowspan=\\\"8\\\" valign=\\\"top\\\">versicolor</th>\\n <th>count</th>\\n <td>50.000000</td>\\n <td>50.000000</td>\\n <td>50.000000</td>\\n <td>50.000000</td>\\n </tr>\\n <tr>\\n <th>mean</th>\\n <td>4.260000</td>\\n <td>1.326000</td>\\n <td>5.936000</td>\\n <td>2.770000</td>\\n </tr>\\n <tr>\\n <th>std</th>\\n <td>0.469911</td>\\n <td>0.197753</td>\\n <td>0.516171</td>\\n <td>0.313798</td>\\n </tr>\\n <tr>\\n <th>min</th>\\n <td>3.000000</td>\\n <td>1.000000</td>\\n <td>4.900000</td>\\n <td>2.000000</td>\\n </tr>\\n <tr>\\n <th>25%</th>\\n <td>4.000000</td>\\n <td>1.200000</td>\\n <td>5.600000</td>\\n <td>2.525000</td>\\n </tr>\\n <tr>\\n <th>50%</th>\\n <td>4.350000</td>\\n <td>1.300000</td>\\n <td>5.900000</td>\\n <td>2.800000</td>\\n </tr>\\n <tr>\\n <th>75%</th>\\n <td>4.600000</td>\\n <td>1.500000</td>\\n <td>6.300000</td>\\n <td>3.000000</td>\\n </tr>\\n <tr>\\n <th>max</th>\\n <td>5.100000</td>\\n <td>1.800000</td>\\n <td>7.000000</td>\\n <td>3.400000</td>\\n </tr>\\n </tbody>\\n</table>\", \"virginica\": \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th></th>\\n <th>petal_length</th>\\n <th>petal_width</th>\\n <th>sepal_length</th>\\n <th>sepal_width</th>\\n </tr>\\n <tr>\\n <th>species</th>\\n <th></th>\\n <th></th>\\n <th></th>\\n <th></th>\\n <th></th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th rowspan=\\\"8\\\" valign=\\\"top\\\">virginica</th>\\n <th>count</th>\\n <td>50.000000</td>\\n <td>50.00000</td>\\n <td>50.00000</td>\\n <td>50.000000</td>\\n </tr>\\n <tr>\\n <th>mean</th>\\n <td>5.552000</td>\\n <td>2.02600</td>\\n <td>6.58800</td>\\n <td>2.974000</td>\\n </tr>\\n <tr>\\n <th>std</th>\\n <td>0.551895</td>\\n <td>0.27465</td>\\n <td>0.63588</td>\\n <td>0.322497</td>\\n </tr>\\n <tr>\\n <th>min</th>\\n <td>4.500000</td>\\n <td>1.40000</td>\\n <td>4.90000</td>\\n <td>2.200000</td>\\n </tr>\\n <tr>\\n <th>25%</th>\\n <td>5.100000</td>\\n <td>1.80000</td>\\n <td>6.22500</td>\\n <td>2.800000</td>\\n </tr>\\n <tr>\\n <th>50%</th>\\n <td>5.550000</td>\\n <td>2.00000</td>\\n <td>6.50000</td>\\n <td>3.000000</td>\\n </tr>\\n <tr>\\n <th>75%</th>\\n <td>5.875000</td>\\n <td>2.30000</td>\\n <td>6.90000</td>\\n <td>3.175000</td>\\n </tr>\\n <tr>\\n <th>max</th>\\n <td>6.900000</td>\\n <td>2.50000</td>\\n <td>7.90000</td>\\n <td>3.800000</td>\\n </tr>\\n </tbody>\\n</table>\", \"setosa\": \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th></th>\\n <th>petal_length</th>\\n <th>petal_width</th>\\n <th>sepal_length</th>\\n <th>sepal_width</th>\\n </tr>\\n <tr>\\n <th>species</th>\\n <th></th>\\n <th></th>\\n <th></th>\\n <th></th>\\n <th></th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th rowspan=\\\"8\\\" valign=\\\"top\\\">setosa</th>\\n <th>count</th>\\n <td>50.000000</td>\\n <td>50.000000</td>\\n <td>50.00000</td>\\n <td>50.000000</td>\\n </tr>\\n <tr>\\n <th>mean</th>\\n <td>1.462000</td>\\n <td>0.246000</td>\\n <td>5.00600</td>\\n <td>3.428000</td>\\n </tr>\\n <tr>\\n <th>std</th>\\n <td>0.173664</td>\\n <td>0.105386</td>\\n <td>0.35249</td>\\n <td>0.379064</td>\\n </tr>\\n <tr>\\n <th>min</th>\\n <td>1.000000</td>\\n <td>0.100000</td>\\n <td>4.30000</td>\\n <td>2.300000</td>\\n </tr>\\n <tr>\\n <th>25%</th>\\n <td>1.400000</td>\\n <td>0.200000</td>\\n <td>4.80000</td>\\n <td>3.200000</td>\\n </tr>\\n <tr>\\n <th>50%</th>\\n <td>1.500000</td>\\n <td>0.200000</td>\\n <td>5.00000</td>\\n <td>3.400000</td>\\n </tr>\\n <tr>\\n <th>75%</th>\\n <td>1.575000</td>\\n <td>0.300000</td>\\n <td>5.20000</td>\\n <td>3.675000</td>\\n </tr>\\n <tr>\\n <th>max</th>\\n <td>1.900000</td>\\n <td>0.600000</td>\\n <td>5.80000</td>\\n <td>4.400000</td>\\n </tr>\\n </tbody>\\n</table>\"}"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Store the dataframe tables in the Javascript console\n",
"js_data = {}\n",
"for species in gb.index.get_level_values('species').unique():\n",
" js_data[species] = gb.loc[[species]].to_html()\n",
"Javascript( 'window.tables = '+json.dumps(js_data) )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"> High-level charts are cool"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"p = Scatter( df, x='sepal_length', y='petal_width', color='species',legend='top_right')\n",
"p.add_tools( bokeh.models.TapTool() )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"> Recover species names from the legend"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create a callback that"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Updates dom elements\n",
"- Shows groupby table for each species."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"legend = p.select(dict(type=bokeh.models.Legend))[0]\n",
"for species in legend.legends:\n",
" source = species[1][0].data_source\n",
" source.name = species[0]\n",
" source.callback = bokeh.models.CustomJS(\n",
" args=dict(source=source),\n",
" code=\"\"\"window['a'] = cb_obj; \n",
" cb_obj.get('selected')['1d'].indices;\n",
" name = cb_obj.get('name');\n",
" Bokeh.$('.species-name').text(name);\n",
" Bokeh.$('#iris-src').attr('src', images[name]);\n",
" Bokeh.$('#table-toggle').html(tables[name]);\n",
" Bokeh.$('#table-toggle').css('background','white')\n",
" \"\"\".format(species=species[0]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"> Click on a point to view more information about a species of iris flower"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\ianba\\Anaconda3\\lib\\site-packages\\ipykernel\\__main__.py:1: BokehDeprecationWarning: bokeh.io.vplot was deprecated in Bokeh 0.12.0; please use bokeh.models.layouts.Column instead\n",
" if __name__ == '__main__':\n"
]
},
{
"data": {
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" </div>\n",
"<script type=\"text/javascript\">\n",
" \n",
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" \n",
" \n",
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" window._bokeh_timeout = Date.now() + 0;\n",
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" }\n",
" \n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
" \n",
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" Bokeh.$(\"#477675d2-094b-4420-9c2b-e48aa5db1a37\").text(\"BokehJS successfully loaded.\");\n",
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" \n",
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" delete window._bokeh_onload_callbacks\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
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" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
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" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" window._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
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" }\n",
" };\n",
" s.onerror = function() {\n",
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" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"477675d2-094b-4420-9c2b-e48aa5db1a37\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid '477675d2-094b-4420-9c2b-e48aa5db1a37' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
" \n",
" var js_urls = [];\n",
" \n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" Bokeh.$(function() {\n",
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"source": [
"## A pandas describe() table for the Iris setosa"
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>sepal_length</th>\n",
" <th>sepal_width</th>\n",
" <th>petal_length</th>\n",
" <th>petal_width</th>\n",
" <th>species</th>\n",
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" <th>0</th>\n",
" <td>5.1</td>\n",
" <td>3.5</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>4.9</td>\n",
" <td>3.0</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4.7</td>\n",
" <td>3.2</td>\n",
" <td>1.3</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4.6</td>\n",
" <td>3.1</td>\n",
" <td>1.5</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5.0</td>\n",
" <td>3.6</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>5.4</td>\n",
" <td>3.9</td>\n",
" <td>1.7</td>\n",
" <td>0.4</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>4.6</td>\n",
" <td>3.4</td>\n",
" <td>1.4</td>\n",
" <td>0.3</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>5.0</td>\n",
" <td>3.4</td>\n",
" <td>1.5</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>4.4</td>\n",
" <td>2.9</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>4.9</td>\n",
" <td>3.1</td>\n",
" <td>1.5</td>\n",
" <td>0.1</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>5.4</td>\n",
" <td>3.7</td>\n",
" <td>1.5</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>4.8</td>\n",
" <td>3.4</td>\n",
" <td>1.6</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>4.8</td>\n",
" <td>3.0</td>\n",
" <td>1.4</td>\n",
" <td>0.1</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>4.3</td>\n",
" <td>3.0</td>\n",
" <td>1.1</td>\n",
" <td>0.1</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>5.8</td>\n",
" <td>4.0</td>\n",
" <td>1.2</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>5.7</td>\n",
" <td>4.4</td>\n",
" <td>1.5</td>\n",
" <td>0.4</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>5.4</td>\n",
" <td>3.9</td>\n",
" <td>1.3</td>\n",
" <td>0.4</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>5.1</td>\n",
" <td>3.5</td>\n",
" <td>1.4</td>\n",
" <td>0.3</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>5.7</td>\n",
" <td>3.8</td>\n",
" <td>1.7</td>\n",
" <td>0.3</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>5.1</td>\n",
" <td>3.8</td>\n",
" <td>1.5</td>\n",
" <td>0.3</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>5.4</td>\n",
" <td>3.4</td>\n",
" <td>1.7</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>5.1</td>\n",
" <td>3.7</td>\n",
" <td>1.5</td>\n",
" <td>0.4</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>4.6</td>\n",
" <td>3.6</td>\n",
" <td>1.0</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>5.1</td>\n",
" <td>3.3</td>\n",
" <td>1.7</td>\n",
" <td>0.5</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>4.8</td>\n",
" <td>3.4</td>\n",
" <td>1.9</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>1.6</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>5.0</td>\n",
" <td>3.4</td>\n",
" <td>1.6</td>\n",
" <td>0.4</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>5.2</td>\n",
" <td>3.5</td>\n",
" <td>1.5</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>5.2</td>\n",
" <td>3.4</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>4.7</td>\n",
" <td>3.2</td>\n",
" <td>1.6</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>6.9</td>\n",
" <td>3.2</td>\n",
" <td>5.7</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>5.6</td>\n",
" <td>2.8</td>\n",
" <td>4.9</td>\n",
" <td>2.0</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>122</th>\n",
" <td>7.7</td>\n",
" <td>2.8</td>\n",
" <td>6.7</td>\n",
" <td>2.0</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>123</th>\n",
" <td>6.3</td>\n",
" <td>2.7</td>\n",
" <td>4.9</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>6.7</td>\n",
" <td>3.3</td>\n",
" <td>5.7</td>\n",
" <td>2.1</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>125</th>\n",
" <td>7.2</td>\n",
" <td>3.2</td>\n",
" <td>6.0</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>126</th>\n",
" <td>6.2</td>\n",
" <td>2.8</td>\n",
" <td>4.8</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>127</th>\n",
" <td>6.1</td>\n",
" <td>3.0</td>\n",
" <td>4.9</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>6.4</td>\n",
" <td>2.8</td>\n",
" <td>5.6</td>\n",
" <td>2.1</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129</th>\n",
" <td>7.2</td>\n",
" <td>3.0</td>\n",
" <td>5.8</td>\n",
" <td>1.6</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>130</th>\n",
" <td>7.4</td>\n",
" <td>2.8</td>\n",
" <td>6.1</td>\n",
" <td>1.9</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131</th>\n",
" <td>7.9</td>\n",
" <td>3.8</td>\n",
" <td>6.4</td>\n",
" <td>2.0</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132</th>\n",
" <td>6.4</td>\n",
" <td>2.8</td>\n",
" <td>5.6</td>\n",
" <td>2.2</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>6.3</td>\n",
" <td>2.8</td>\n",
" <td>5.1</td>\n",
" <td>1.5</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>6.1</td>\n",
" <td>2.6</td>\n",
" <td>5.6</td>\n",
" <td>1.4</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>7.7</td>\n",
" <td>3.0</td>\n",
" <td>6.1</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>136</th>\n",
" <td>6.3</td>\n",
" <td>3.4</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>137</th>\n",
" <td>6.4</td>\n",
" <td>3.1</td>\n",
" <td>5.5</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>138</th>\n",
" <td>6.0</td>\n",
" <td>3.0</td>\n",
" <td>4.8</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>6.9</td>\n",
" <td>3.1</td>\n",
" <td>5.4</td>\n",
" <td>2.1</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>140</th>\n",
" <td>6.7</td>\n",
" <td>3.1</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>141</th>\n",
" <td>6.9</td>\n",
" <td>3.1</td>\n",
" <td>5.1</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>142</th>\n",
" <td>5.8</td>\n",
" <td>2.7</td>\n",
" <td>5.1</td>\n",
" <td>1.9</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143</th>\n",
" <td>6.8</td>\n",
" <td>3.2</td>\n",
" <td>5.9</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>144</th>\n",
" <td>6.7</td>\n",
" <td>3.3</td>\n",
" <td>5.7</td>\n",
" <td>2.5</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>6.7</td>\n",
" <td>3.0</td>\n",
" <td>5.2</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>146</th>\n",
" <td>6.3</td>\n",
" <td>2.5</td>\n",
" <td>5.0</td>\n",
" <td>1.9</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>6.5</td>\n",
" <td>3.0</td>\n",
" <td>5.2</td>\n",
" <td>2.0</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>6.2</td>\n",
" <td>3.4</td>\n",
" <td>5.4</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" <tr>\n",
" <th>149</th>\n",
" <td>5.9</td>\n",
" <td>3.0</td>\n",
" <td>5.1</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>150 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" sepal_length sepal_width petal_length petal_width species\n",
"0 5.1 3.5 1.4 0.2 setosa\n",
"1 4.9 3.0 1.4 0.2 setosa\n",
"2 4.7 3.2 1.3 0.2 setosa\n",
"3 4.6 3.1 1.5 0.2 setosa\n",
"4 5.0 3.6 1.4 0.2 setosa\n",
"5 5.4 3.9 1.7 0.4 setosa\n",
"6 4.6 3.4 1.4 0.3 setosa\n",
"7 5.0 3.4 1.5 0.2 setosa\n",
"8 4.4 2.9 1.4 0.2 setosa\n",
"9 4.9 3.1 1.5 0.1 setosa\n",
"10 5.4 3.7 1.5 0.2 setosa\n",
"11 4.8 3.4 1.6 0.2 setosa\n",
"12 4.8 3.0 1.4 0.1 setosa\n",
"13 4.3 3.0 1.1 0.1 setosa\n",
"14 5.8 4.0 1.2 0.2 setosa\n",
"15 5.7 4.4 1.5 0.4 setosa\n",
"16 5.4 3.9 1.3 0.4 setosa\n",
"17 5.1 3.5 1.4 0.3 setosa\n",
"18 5.7 3.8 1.7 0.3 setosa\n",
"19 5.1 3.8 1.5 0.3 setosa\n",
"20 5.4 3.4 1.7 0.2 setosa\n",
"21 5.1 3.7 1.5 0.4 setosa\n",
"22 4.6 3.6 1.0 0.2 setosa\n",
"23 5.1 3.3 1.7 0.5 setosa\n",
"24 4.8 3.4 1.9 0.2 setosa\n",
"25 5.0 3.0 1.6 0.2 setosa\n",
"26 5.0 3.4 1.6 0.4 setosa\n",
"27 5.2 3.5 1.5 0.2 setosa\n",
"28 5.2 3.4 1.4 0.2 setosa\n",
"29 4.7 3.2 1.6 0.2 setosa\n",
".. ... ... ... ... ...\n",
"120 6.9 3.2 5.7 2.3 virginica\n",
"121 5.6 2.8 4.9 2.0 virginica\n",
"122 7.7 2.8 6.7 2.0 virginica\n",
"123 6.3 2.7 4.9 1.8 virginica\n",
"124 6.7 3.3 5.7 2.1 virginica\n",
"125 7.2 3.2 6.0 1.8 virginica\n",
"126 6.2 2.8 4.8 1.8 virginica\n",
"127 6.1 3.0 4.9 1.8 virginica\n",
"128 6.4 2.8 5.6 2.1 virginica\n",
"129 7.2 3.0 5.8 1.6 virginica\n",
"130 7.4 2.8 6.1 1.9 virginica\n",
"131 7.9 3.8 6.4 2.0 virginica\n",
"132 6.4 2.8 5.6 2.2 virginica\n",
"133 6.3 2.8 5.1 1.5 virginica\n",
"134 6.1 2.6 5.6 1.4 virginica\n",
"135 7.7 3.0 6.1 2.3 virginica\n",
"136 6.3 3.4 5.6 2.4 virginica\n",
"137 6.4 3.1 5.5 1.8 virginica\n",
"138 6.0 3.0 4.8 1.8 virginica\n",
"139 6.9 3.1 5.4 2.1 virginica\n",
"140 6.7 3.1 5.6 2.4 virginica\n",
"141 6.9 3.1 5.1 2.3 virginica\n",
"142 5.8 2.7 5.1 1.9 virginica\n",
"143 6.8 3.2 5.9 2.3 virginica\n",
"144 6.7 3.3 5.7 2.5 virginica\n",
"145 6.7 3.0 5.2 2.3 virginica\n",
"146 6.3 2.5 5.0 1.9 virginica\n",
"147 6.5 3.0 5.2 2.0 virginica\n",
"148 6.2 3.4 5.4 2.3 virginica\n",
"149 5.9 3.0 5.1 1.8 virginica\n",
"\n",
"[150 rows x 5 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris.flowers"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"application/javascript": [
"window['images'] = {\"versicolor\": \"https://upload.wikimedia.org/wikipedia/commons/thumb/4/41/Iris_versicolor_3.jpg/440px-Iris_versicolor_3.jpg\", \"virginica\": \"https://upload.wikimedia.org/wikipedia/commons/thumb/9/9f/Iris_virginica.jpg/440px-Iris_virginica.jpg\", \"setosa\": \"https://upload.wikimedia.org/wikipedia/commons/thumb/5/56/Kosaciec_szczecinkowaty_Iris_setosa.jpg/440px-Kosaciec_szczecinkowaty_Iris_setosa.jpg\"}"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"imgs = {'setosa':'https://upload.wikimedia.org/wikipedia/commons/thumb/5/56/Kosaciec_szczecinkowaty_Iris_setosa.jpg/440px-Kosaciec_szczecinkowaty_Iris_setosa.jpg',\n",
"'versicolor':'https://upload.wikimedia.org/wikipedia/commons/thumb/4/41/Iris_versicolor_3.jpg/440px-Iris_versicolor_3.jpg',\n",
"'virginica':'https://upload.wikimedia.org/wikipedia/commons/thumb/9/9f/Iris_virginica.jpg/440px-Iris_virginica.jpg'}\n",
"Javascript( \"\"\"window['images'] = \"\"\" + json.dumps(imgs))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [Root]",
"language": "python",
"name": "Python [Root]"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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