![](\"http://matplotlib.org/_images/fig_map.png\")
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Une derni\u00e8re remarque d'ordre g\u00e9n\u00e9ral : [pyplot est une machine \u00e0 \u00e9tat](https://en.wikipedia.org/wiki/Matplotlib).\n", "Cela implique que les m\u00e9thodes pour tracer un graphe ou \u00e9diter un label s'appliquent par d\u00e9faut au dernier \u00e9tat en cours (derni\u00e8re instance de subplot ou derni\u00e8re instance d'axe par exemple). \n", "\n", "Cons\u00e9quence : il faut concevoir ses codes comme une s\u00e9quence d'instructions (par exemple, il ne faut pas s\u00e9parer les instructions qui se rapportent au m\u00eame graphique dans deux cellules diff\u00e9rentes du Notebook)."]}, {"cell_type": "markdown", "metadata": {}, "source": ["### Figures et Subplots "]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"data": {"text/plain": ["\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" VARIABLE LIBELLE TYPE \\\n", "0 AMAR Ann\u00e9e du mariage CHAR \n", "1 ANAISF Ann\u00e9e de naissance de l'\u00e9pouse CHAR \n", "2 ANAISH Ann\u00e9e de naissance de l'\u00e9poux CHAR \n", "3 DEPDOM\u00a0 D\u00e9partement de domicile apr\u00e8s le mariage CHAR \n", "4 DEPMAR D\u00e9partement de mariage CHAR \n", "5 DEPNAISF D\u00e9partement de naissance de l'\u00e9pouse CHAR \n", "6 DEPNAISH D\u00e9partement de naissance de l'\u00e9poux CHAR \n", "7 ETAMATF \u00c9tat matrimonial ant\u00e9rieur de l'\u00e9pouse CHAR \n", "8 ETAMATH \u00c9tat matrimonial ant\u00e9rieur de l'\u00e9poux CHAR \n", "9 INDNATF Indicateur de nationalit\u00e9 de l'\u00e9pouse CHAR \n", "10 INDNATH Indicateur de nationalit\u00e9 de l'\u00e9poux CHAR \n", "11 JSEMAINE Jour du mariage dans la semaine CHAR \n", "12 MMAR Mois du mariage CHAR \n", "13 NBENFCOM Enfants en commun avant le mariage CHAR \n", "14 TUCOM Tranche de commune du lieu de domicile des \u00e9poux CHAR \n", "15 TUDOM Tranche d'unit\u00e9 urbaine du lieu de domicile de... CHAR \n", "\n", " LONGUEUR \n", "0 4 \n", "1 4 \n", "2 4 \n", "3 3 \n", "4 3 \n", "5 3 \n", "6 3 \n", "7 1 \n", "8 1 \n", "9 1 \n", "10 1 \n", "11 1 \n", "12 2 \n", "13 1 \n", "14 1 \n", "15 1 "]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["vardf = dBase2df(\"varlist_mariages.dbf\")\n", "print(vardf.shape, vardf.columns)\n", "vardf"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Repr\u00e9sentez l'age des femmes en fonction de celui des hommes au moment du mariage."]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"text/html": ["| \n", " | VARIABLE | \n", "LIBELLE | \n", "TYPE | \n", "LONGUEUR | \n", "
|---|---|---|---|---|
| 0 | \n", "AMAR | \n", "Ann\u00e9e du mariage | \n", "CHAR | \n", "4 | \n", "
| 1 | \n", "ANAISF | \n", "Ann\u00e9e de naissance de l'\u00e9pouse | \n", "CHAR | \n", "4 | \n", "
| 2 | \n", "ANAISH | \n", "Ann\u00e9e de naissance de l'\u00e9poux | \n", "CHAR | \n", "4 | \n", "
| 3 | \n", "DEPDOM | \n", "D\u00e9partement de domicile apr\u00e8s le mariage | \n", "CHAR | \n", "3 | \n", "
| 4 | \n", "DEPMAR | \n", "D\u00e9partement de mariage | \n", "CHAR | \n", "3 | \n", "
| 5 | \n", "DEPNAISF | \n", "D\u00e9partement de naissance de l'\u00e9pouse | \n", "CHAR | \n", "3 | \n", "
| 6 | \n", "DEPNAISH | \n", "D\u00e9partement de naissance de l'\u00e9poux | \n", "CHAR | \n", "3 | \n", "
| 7 | \n", "ETAMATF | \n", "\u00c9tat matrimonial ant\u00e9rieur de l'\u00e9pouse | \n", "CHAR | \n", "1 | \n", "
| 8 | \n", "ETAMATH | \n", "\u00c9tat matrimonial ant\u00e9rieur de l'\u00e9poux | \n", "CHAR | \n", "1 | \n", "
| 9 | \n", "INDNATF | \n", "Indicateur de nationalit\u00e9 de l'\u00e9pouse | \n", "CHAR | \n", "1 | \n", "
| 10 | \n", "INDNATH | \n", "Indicateur de nationalit\u00e9 de l'\u00e9poux | \n", "CHAR | \n", "1 | \n", "
| 11 | \n", "JSEMAINE | \n", "Jour du mariage dans la semaine | \n", "CHAR | \n", "1 | \n", "
| 12 | \n", "MMAR | \n", "Mois du mariage | \n", "CHAR | \n", "2 | \n", "
| 13 | \n", "NBENFCOM | \n", "Enfants en commun avant le mariage | \n", "CHAR | \n", "1 | \n", "
| 14 | \n", "TUCOM | \n", "Tranche de commune du lieu de domicile des \u00e9poux | \n", "CHAR | \n", "1 | \n", "
| 15 | \n", "TUDOM | \n", "Tranche d'unit\u00e9 urbaine du lieu de domicile de... | \n", "CHAR | \n", "1 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" ANAISH DEPNAISH INDNATH ETAMATH ANAISF DEPNAISF INDNATF ETAMATF AMAR MMAR \\\n", "0 1982 75 1 1 1984 99 2 1 2012 01 \n", "1 1956 69 2 4 1969 99 2 4 2012 01 \n", "2 1982 99 2 1 1992 99 1 1 2012 01 \n", "3 1985 99 2 1 1987 84 1 1 2012 01 \n", "4 1968 99 2 1 1963 99 2 1 2012 01 \n", "\n", " JSEMAINE DEPMAR DEPDOM TUDOM TUCOM NBENFCOM \n", "0 1 29 99 9 N \n", "1 3 75 99 9 N \n", "2 5 34 99 9 N \n", "3 4 13 99 9 N \n", "4 6 26 99 9 N "]}, "execution_count": 22, "metadata": {}, "output_type": "execute_result"}], "source": ["#Calcul de l'age (au moment du mariage)\n", "df.head()"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": ["#conversion des ann\u00e9es en entiers\n", "for c in ['AMAR','ANAISF','ANAISH']:\n", " df[c]=df[c].apply(lambda x: int(x))\n", "\n", "#calcul de l'age\n", "df['AGEF'] = df['AMAR'] - df['ANAISF']\n", "df['AGEH'] = df['AMAR'] - df['ANAISH']"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Le module pandas a pr\u00e9vu un [wrapper](http://pandas.pydata.org/pandas-docs/stable/visualization.html) matplotlib"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"data": {"text/plain": ["| \n", " | ANAISH | \n", "DEPNAISH | \n", "INDNATH | \n", "ETAMATH | \n", "ANAISF | \n", "DEPNAISF | \n", "INDNATF | \n", "ETAMATF | \n", "AMAR | \n", "MMAR | \n", "JSEMAINE | \n", "DEPMAR | \n", "DEPDOM | \n", "TUDOM | \n", "TUCOM | \n", "NBENFCOM | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "1982 | \n", "75 | \n", "1 | \n", "1 | \n", "1984 | \n", "99 | \n", "2 | \n", "1 | \n", "2012 | \n", "01 | \n", "1 | \n", "29 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "
| 1 | \n", "1956 | \n", "69 | \n", "2 | \n", "4 | \n", "1969 | \n", "99 | \n", "2 | \n", "4 | \n", "2012 | \n", "01 | \n", "3 | \n", "75 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "
| 2 | \n", "1982 | \n", "99 | \n", "2 | \n", "1 | \n", "1992 | \n", "99 | \n", "1 | \n", "1 | \n", "2012 | \n", "01 | \n", "5 | \n", "34 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "
| 3 | \n", "1985 | \n", "99 | \n", "2 | \n", "1 | \n", "1987 | \n", "84 | \n", "1 | \n", "1 | \n", "2012 | \n", "01 | \n", "4 | \n", "13 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "
| 4 | \n", "1968 | \n", "99 | \n", "2 | \n", "1 | \n", "1963 | \n", "99 | \n", "2 | \n", "1 | \n", "2012 | \n", "01 | \n", "6 | \n", "26 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" differenceHF nb\n", "95 46 1\n", "96 48 3\n", "97 50 1\n", "98 56 1\n", "99 59 1"]}, "execution_count": 29, "metadata": {}, "output_type": "execute_result"}], "source": ["df[\"differenceHF\"] = df[\"ANAISH\"] - df[\"ANAISF\"]\n", "df[\"nb\"] = 1\n", "dist = df[[\"nb\",\"differenceHF\"]].groupby(\"differenceHF\", as_index=False).count()\n", "dist.tail()"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [{"data": {"text/plain": ["Text(0.5,1,'Graphique avec seaborn')"]}, "execution_count": 30, "metadata": {}, "output_type": "execute_result"}, {"data": {"image/png": 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TcL0XX3yx8vPz9cgjj+hf//qXtm7dqpkzZzY7ZsSIEdqxY4fWrl2rgwcP6vnnn282Zen2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\nERERERHTKZyKiIiIiIiI6f4fZj7GBxlt0x8AAAAASUVORK5CYII=\n", "text/plain": ["| \n", " | differenceHF | \n", "nb | \n", "
|---|---|---|
| 95 | \n", "46 | \n", "1 | \n", "
| 96 | \n", "48 | \n", "3 | \n", "
| 97 | \n", "50 | \n", "1 | \n", "
| 98 | \n", "56 | \n", "1 | \n", "
| 99 | \n", "59 | \n", "1 | \n", "
\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" ANAISH DEPNAISH INDNATH ETAMATH ANAISF DEPNAISF INDNATF ETAMATF AMAR \\\n", "0 1982 75 1 1 1984 99 2 1 2012 \n", "1 1956 69 2 4 1969 99 2 4 2012 \n", "2 1982 99 2 1 1992 99 1 1 2012 \n", "3 1985 99 2 1 1987 84 1 1 2012 \n", "4 1968 99 2 1 1963 99 2 1 2012 \n", "\n", " MMAR JSEMAINE DEPMAR DEPDOM TUDOM TUCOM NBENFCOM AGEF AGEH nb \\\n", "0 01 1 29 99 9 N 28 30 1 \n", "1 01 3 75 99 9 N 43 56 1 \n", "2 01 5 34 99 9 N 20 30 1 \n", "3 01 4 13 99 9 N 25 27 1 \n", "4 01 6 26 99 9 N 49 44 1 \n", "\n", " differenceHF \n", "0 -2 \n", "1 -13 \n", "2 -10 \n", "3 -2 \n", "4 5 "]}, "execution_count": 33, "metadata": {}, "output_type": "execute_result"}], "source": ["df.head()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Graphes int\u00e9ractifs : bokeh, altair, bqplot"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Pour faire simple, il est possible d'introduire du JavaScript dans l'application web locale cr\u00e9\u00e9e par jupyter. C'est ce que fait D3.js. Les librairies interactives comme [bokeh](http://bokeh.pydata.org/en/latest/) ou [altair](https://altair-viz.github.io/) ont associ\u00e9 le design de [matplotlib](https://matplotlib.org/) avec des librairies javascript comme [vega-lite](https://vega.github.io/vega-lite/). L'exemple suivant utilise [bokeh](http://bokeh.pydata.org/en/latest/)."]}, {"cell_type": "code", "execution_count": 33, "metadata": {"scrolled": false}, "outputs": [{"data": {"text/html": ["\n", " "]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/javascript": ["\n", "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", "\n", " if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n", " root._bokeh_onload_callbacks = [];\n", " root._bokeh_is_loading = undefined;\n", " }\n", "\n", " var JS_MIME_TYPE = 'application/javascript';\n", " var HTML_MIME_TYPE = 'text/html';\n", " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", " var CLASS_NAME = 'output_bokeh rendered_html';\n", "\n", " /**\n", " * Render data to the DOM node\n", " */\n", " function render(props, node) {\n", " var script = document.createElement(\"script\");\n", " node.appendChild(script);\n", " }\n", "\n", " /**\n", " * Handle when an output is cleared or removed\n", " */\n", " function handleClearOutput(event, handle) {\n", " var cell = handle.cell;\n", "\n", " var id = cell.output_area._bokeh_element_id;\n", " var server_id = cell.output_area._bokeh_server_id;\n", " // Clean up Bokeh references\n", " if (id !== undefined) {\n", " Bokeh.index[id].model.document.clear();\n", " delete Bokeh.index[id];\n", " }\n", "\n", " if (server_id !== undefined) {\n", " // Clean up Bokeh references\n", " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", " cell.notebook.kernel.execute(cmd, {\n", " iopub: {\n", " output: function(msg) {\n", " var element_id = msg.content.text.trim();\n", " Bokeh.index[element_id].model.document.clear();\n", " delete Bokeh.index[element_id];\n", " }\n", " }\n", " });\n", " // Destroy server and session\n", " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", " cell.notebook.kernel.execute(cmd);\n", " }\n", " }\n", "\n", " /**\n", " * Handle when a new output is added\n", " */\n", " function handleAddOutput(event, handle) {\n", " var output_area = handle.output_area;\n", " var output = handle.output;\n", "\n", " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", " return\n", " }\n", "\n", " var toinsert = output_area.element.find(`.${CLASS_NAME.split(' ')[0]}`);\n", "\n", " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", " toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n", " // store reference to embed id on output_area\n", " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", " }\n", " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", " var bk_div = document.createElement(\"div\");\n", " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", " var script_attrs = bk_div.children[0].attributes;\n", " for (var i = 0; i < script_attrs.length; i++) {\n", " toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", " }\n", " // store reference to server id on output_area\n", " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", " }\n", " }\n", "\n", " function register_renderer(events, OutputArea) {\n", "\n", " function append_mime(data, metadata, element) {\n", " // create a DOM node to render to\n", " var toinsert = this.create_output_subarea(\n", " metadata,\n", " CLASS_NAME,\n", " EXEC_MIME_TYPE\n", " );\n", " this.keyboard_manager.register_events(toinsert);\n", " // Render to node\n", " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", " render(props, toinsert[0]);\n", " element.append(toinsert);\n", " return toinsert\n", " }\n", "\n", " /* Handle when an output is cleared or removed */\n", " events.on('clear_output.CodeCell', handleClearOutput);\n", " events.on('delete.Cell', handleClearOutput);\n", "\n", " /* Handle when a new output is added */\n", " events.on('output_added.OutputArea', handleAddOutput);\n", "\n", " /**\n", " * Register the mime type and append_mime function with output_area\n", " */\n", " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", " /* Is output safe? */\n", " safe: true,\n", " /* Index of renderer in `output_area.display_order` */\n", " index: 0\n", " });\n", " }\n", "\n", " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", " if (root.Jupyter !== undefined) {\n", " var events = require('base/js/events');\n", " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", "\n", " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", " register_renderer(events, OutputArea);\n", " }\n", " }\n", "\n", " \n", " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", " \"| \n", " | ANAISH | \n", "DEPNAISH | \n", "INDNATH | \n", "ETAMATH | \n", "ANAISF | \n", "DEPNAISF | \n", "INDNATF | \n", "ETAMATF | \n", "AMAR | \n", "MMAR | \n", "JSEMAINE | \n", "DEPMAR | \n", "DEPDOM | \n", "TUDOM | \n", "TUCOM | \n", "NBENFCOM | \n", "AGEF | \n", "AGEH | \n", "nb | \n", "differenceHF | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "1982 | \n", "75 | \n", "1 | \n", "1 | \n", "1984 | \n", "99 | \n", "2 | \n", "1 | \n", "2012 | \n", "01 | \n", "1 | \n", "29 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "28 | \n", "30 | \n", "1 | \n", "-2 | \n", "
| 1 | \n", "1956 | \n", "69 | \n", "2 | \n", "4 | \n", "1969 | \n", "99 | \n", "2 | \n", "4 | \n", "2012 | \n", "01 | \n", "3 | \n", "75 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "43 | \n", "56 | \n", "1 | \n", "-13 | \n", "
| 2 | \n", "1982 | \n", "99 | \n", "2 | \n", "1 | \n", "1992 | \n", "99 | \n", "1 | \n", "1 | \n", "2012 | \n", "01 | \n", "5 | \n", "34 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "20 | \n", "30 | \n", "1 | \n", "-10 | \n", "
| 3 | \n", "1985 | \n", "99 | \n", "2 | \n", "1 | \n", "1987 | \n", "84 | \n", "1 | \n", "1 | \n", "2012 | \n", "01 | \n", "4 | \n", "13 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "25 | \n", "27 | \n", "1 | \n", "-2 | \n", "
| 4 | \n", "1968 | \n", "99 | \n", "2 | \n", "1 | \n", "1963 | \n", "99 | \n", "2 | \n", "1 | \n", "2012 | \n", "01 | \n", "6 | \n", "26 | \n", "99 | \n", "9 | \n", "\n", " | N | \n", "49 | \n", "44 | \n", "1 | \n", "5 | \n", "
\\n\"+\n", " \"
\"}};\n", "\n", " function display_loaded() {\n", " var el = document.getElementById(\"459191df-ec45-44f7-a189-2c62fb6a1d5c\");\n", " if (el != null) {\n", " el.textContent = \"BokehJS is loading...\";\n", " }\n", " if (root.Bokeh !== undefined) {\n", " if (el != null) {\n", " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", " }\n", " } else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(display_loaded, 100)\n", " }\n", " }\n", "\n", "\n", " function run_callbacks() {\n", " try {\n", " root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n", " }\n", " finally {\n", " delete root._bokeh_onload_callbacks\n", " }\n", " console.info(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(js_urls, callback) {\n", " root._bokeh_onload_callbacks.push(callback);\n", " if (root._bokeh_is_loading > 0) {\n", " console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", " 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", " root._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", " s.onreadystatechange = s.onload = function() {\n", " root._bokeh_is_loading--;\n", " if (root._bokeh_is_loading === 0) {\n", " console.log(\"Bokeh: all BokehJS libraries loaded\");\n", " run_callbacks()\n", " }\n", " };\n", " s.onerror = function() {\n", " console.warn(\"failed to load library \" + url);\n", " };\n", " console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", " }\n", " };var element = document.getElementById(\"459191df-ec45-44f7-a189-2c62fb6a1d5c\");\n", " if (element == null) {\n", " console.log(\"Bokeh: ERROR: autoload.js configured with elementid '459191df-ec45-44f7-a189-2c62fb6a1d5c' but no matching script tag was found. \")\n", " return false;\n", " }\n", "\n", " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.10.min.js\"];\n", "\n", " var inline_js = [\n", " function(Bokeh) {\n", " Bokeh.set_log_level(\"info\");\n", " },\n", " \n", " function(Bokeh) {\n", " \n", " },\n", " function(Bokeh) {\n", " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n", " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n", " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n", " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n", " console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n", " Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " \n", " if ((root.Bokeh !== undefined) || (force === true)) {\n", " for (var i = 0; i < inline_js.length; i++) {\n", " inline_js[i].call(root, root.Bokeh);\n", " }if (force === true) {\n", " display_loaded();\n", " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", " root._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", " var cell = $(document.getElementById(\"459191df-ec45-44f7-a189-2c62fb6a1d5c\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", "\n", " }\n", "\n", " if (root._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", "}(window));"], "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"\\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", " \"
\\n\"+\n", " \"- \\n\"+\n", " \"
- re-rerun `output_notebook()` to attempt to load from CDN again, or \\n\"+\n", " \"
- use INLINE resources instead, as so: \\n\"+\n", " \"
\\n\"+\n", " \"from bokeh.resources import INLINE\\n\"+\n", " \"output_notebook(resources=INLINE)\\n\"+\n", " \"\\n\"+\n", " \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"459191df-ec45-44f7-a189-2c62fb6a1d5c\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n }\n finally {\n delete root._bokeh_onload_callbacks\n }\n console.info(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(js_urls, callback) {\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n 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 root._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 s.onreadystatechange = s.onload = function() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: all BokehJS libraries loaded\");\n run_callbacks()\n }\n };\n s.onerror = function() {\n console.warn(\"failed to load library \" + url);\n };\n console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.getElementsByTagName(\"head\")[0].appendChild(s);\n }\n };var element = document.getElementById(\"459191df-ec45-44f7-a189-2c62fb6a1d5c\");\n if (element == null) {\n console.log(\"Bokeh: ERROR: autoload.js configured with elementid '459191df-ec45-44f7-a189-2c62fb6a1d5c' but no matching script tag was found. \")\n return false;\n }\n\n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.10.min.js\"];\n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n \n function(Bokeh) {\n \n },\n function(Bokeh) {\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n }\n ];\n\n function run_inline_js() {\n \n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"459191df-ec45-44f7-a189-2c62fb6a1d5c\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._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}(window));"}, "metadata": {}, "output_type": "display_data"}, {"data": {"text/html": ["\n", "\\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 \"
\\n\"+\n \"- \\n\"+\n \"
- re-rerun `output_notebook()` to attempt to load from CDN again, or \\n\"+\n \"
- use INLINE resources instead, as so: \\n\"+\n \"
\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"\n", " \n", "
"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/javascript": ["(function(root) {\n", " function embed_document(root) {\n", " var docs_json = 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Application\",\"version\":\"0.12.10\"}};\n", " var render_items = [{\"docid\":\"ce4157b9-d498-4eed-9c57-8fa7ea5e01f3\",\"elementid\":\"4ca479c1-0582-4409-937d-68452b702bd4\",\"modelid\":\"977cac45-d8c4-4e93-bbe2-4424ebc3fc16\"}];\n", "\n", " root.Bokeh.embed.embed_items(docs_json, render_items);\n", " }\n", "\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " var attempts = 0;\n", " var timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " clearInterval(timer);\n", " }\n", " attempts++;\n", " if (attempts > 100) {\n", " console.log(\"Bokeh: ERROR: Unable to embed document because BokehJS library is missing\")\n", " clearInterval(timer);\n", " }\n", " }, 10, root)\n", " }\n", "})(window);"], "application/vnd.bokehjs_exec.v0+json": ""}, "metadata": {"application/vnd.bokehjs_exec.v0+json": {"id": "977cac45-d8c4-4e93-bbe2-4424ebc3fc16"}}, "output_type": "display_data"}], "source": ["from bokeh.plotting import figure, show, output_notebook\n", "output_notebook()\n", "\n", "fig = figure()\n", "\n", "sample = df.sample(500)\n", "\n", "fig.scatter(sample['AGEH'],sample['AGEF'])\n", "fig.xaxis.axis_label = 'AGEH'\n", "fig.yaxis.axis_label = 'AGEH'\n", "show(fig)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La page [callbacks](https://bokeh.pydata.org/en/latest/docs/user_guide/interaction/callbacks.html) montre comment utiliser les interactions utilisateurs. Seul inconv\u00e9nient, il faut conna\u00eetre le javascript."]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", " \n", "
"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/javascript": ["(function(root) {\n", " function embed_document(root) {\n", " var docs_json = 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links = {0: [1, 2], 1: [0, 3, 4], 2: [0, 5], 3: [1, 4], 4: [1, 3], 5: [2, 3, 4]};\\nvar data = {'x0': [], 'y0': [], 'x1': [], 'y1': []};\\nvar cdata = circle.data;\\nvar indices = cb_data.index['1d'].indices;\\nfor (i=0; i < indices.length; i++) {\\n ind0 = indices[i]\\n for (j=0; j < links[ind0].length; j++) {\\n ind1 = links[ind0][j];\\n data['x0'].push(cdata.x[ind0]);\\n data['y0'].push(cdata.y[ind0]);\\n data['x1'].push(cdata.x[ind1]);\\n data['y1'].push(cdata.y[ind1]);\\n }\\n}\\nsegment.data = data;\\n\"},\"id\":\"781e8824-0cd8-477b-adbf-5ca5937f2e46\",\"type\":\"CustomJS\"},{\"attributes\":{\"fill_color\":{\"value\":\"olive\"},\"line_color\":{\"value\":\"olive\"},\"size\":{\"units\":\"screen\",\"value\":30},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6c04ef7b-95ef-4971-bfdc-812144b13b60\",\"type\":\"Circle\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"size\":{\"units\":\"screen\",\"value\":30},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"692c3816-054c-4029-b72b-e3ad86e10418\",\"type\":\"Circle\"},{\"attributes\":{\"callback\":{\"id\":\"781e8824-0cd8-477b-adbf-5ca5937f2e46\",\"type\":\"CustomJS\"},\"renderers\":[{\"id\":\"d4991b62-0d39-4054-a60c-c0155bcf31a3\",\"type\":\"GlyphRenderer\"}],\"tooltips\":null},\"id\":\"17e540b7-6ed8-480d-ac1d-62aa47dfb403\",\"type\":\"HoverTool\"},{\"attributes\":{\"data_source\":{\"id\":\"ca90edc5-28fb-4816-be9b-edbc85a075fb\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"13325f26-0632-4336-9532-f91cf7c86ab6\",\"type\":\"Circle\"},\"hover_glyph\":{\"id\":\"6c04ef7b-95ef-4971-bfdc-812144b13b60\",\"type\":\"Circle\"},\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"692c3816-054c-4029-b72b-e3ad86e10418\",\"type\":\"Circle\"},\"selection_glyph\":null,\"view\":{\"id\":\"ab4ea455-f088-4d07-a40e-85b05b014450\",\"type\":\"CDSView\"}},\"id\":\"d4991b62-0d39-4054-a60c-c0155bcf31a3\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"source\":{\"id\":\"ca90edc5-28fb-4816-be9b-edbc85a075fb\",\"type\":\"ColumnDataSource\"}},\"id\":\"ab4ea455-f088-4d07-a40e-85b05b014450\",\"type\":\"CDSView\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x0\",\"y0\",\"x1\",\"y1\"],\"data\":{\"x0\":[],\"x1\":[],\"y0\":[],\"y1\":[]}},\"id\":\"b4cade67-5081-45c0-a6b6-761b2e394545\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"below\":[{\"id\":\"215b666f-e349-42d1-86f9-e77676c2fb8e\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"840b9657-0a74-4bd6-98f8-74abbacc3885\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":400,\"renderers\":[{\"id\":\"215b666f-e349-42d1-86f9-e77676c2fb8e\",\"type\":\"LinearAxis\"},{\"id\":\"13f19693-6a83-40e4-8acd-285e9b9fa31b\",\"type\":\"Grid\"},{\"id\":\"840b9657-0a74-4bd6-98f8-74abbacc3885\",\"type\":\"LinearAxis\"},{\"id\":\"224a184c-4ce1-40ec-8058-e4ebb30ca7be\",\"type\":\"Grid\"},{\"id\":\"1145519d-bc35-45cc-ae26-832c8be581b8\",\"type\":\"GlyphRenderer\"},{\"id\":\"d4991b62-0d39-4054-a60c-c0155bcf31a3\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"bb5dbaf0-9f49-4802-a9d2-cb3912dc09b3\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"53019176-53e0-4bd1-882f-78d06fa33f77\",\"type\":\"Toolbar\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"5e69d73f-39ea-4407-b2ed-1b95ff963ea3\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"cbad94c3-1675-480c-81a1-9f0e32779c50\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"907659cb-bca4-4311-b875-6835665452ae\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"aeae838f-00e9-42fa-81f6-55eafabd2430\",\"type\":\"LinearScale\"}},\"id\":\"535ebb48-a4c6-4f64-b121-7e9255a0a944\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"523ef191-c459-4cee-98ba-82b0bc9d43ee\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":[2,3,5,6,8,7],\"y\":[6,4,3,8,7,5]}},\"id\":\"ca90edc5-28fb-4816-be9b-edbc85a075fb\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":null,\"text\":\"Hover over points\"},\"id\":\"bb5dbaf0-9f49-4802-a9d2-cb3912dc09b3\",\"type\":\"Title\"},{\"attributes\":{\"callback\":null},\"id\":\"5e69d73f-39ea-4407-b2ed-1b95ff963ea3\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"535ebb48-a4c6-4f64-b121-7e9255a0a944\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.10\"}};\n", " var render_items = [{\"docid\":\"b0c3fe59-2ef5-4600-9700-e5d1b6eaec90\",\"elementid\":\"38f951a6-5c61-4fc1-8aa4-28135319a094\",\"modelid\":\"535ebb48-a4c6-4f64-b121-7e9255a0a944\"}];\n", "\n", " root.Bokeh.embed.embed_items(docs_json, render_items);\n", " }\n", "\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " var attempts = 0;\n", " var timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " clearInterval(timer);\n", " }\n", " attempts++;\n", " if (attempts > 100) {\n", " console.log(\"Bokeh: ERROR: Unable to embed document because BokehJS library is missing\")\n", " clearInterval(timer);\n", " }\n", " }, 10, root)\n", " }\n", "})(window);"], "application/vnd.bokehjs_exec.v0+json": ""}, "metadata": {"application/vnd.bokehjs_exec.v0+json": {"id": "535ebb48-a4c6-4f64-b121-7e9255a0a944"}}, "output_type": "display_data"}], "source": ["from bokeh.plotting import figure, output_file, show\n", "from bokeh.models import ColumnDataSource, HoverTool, CustomJS\n", "\n", "\n", "# define some points and a little graph between them\n", "x = [2, 3, 5, 6, 8, 7]\n", "y = [6, 4, 3, 8, 7, 5]\n", "links = {\n", " 0: [1, 2],\n", " 1: [0, 3, 4],\n", " 2: [0, 5],\n", " 3: [1, 4],\n", " 4: [1, 3],\n", " 5: [2, 3, 4]\n", "}\n", "\n", "p = figure(plot_width=400, plot_height=400, tools=\"\", toolbar_location=None, title='Hover over points')\n", "\n", "source = ColumnDataSource({'x0': [], 'y0': [], 'x1': [], 'y1': []})\n", "sr = p.segment(x0='x0', y0='y0', x1='x1', y1='y1', color='olive', alpha=0.6, line_width=3, source=source, )\n", "cr = p.circle(x, y, color='olive', size=30, alpha=0.4, hover_color='olive', hover_alpha=1.0)\n", "\n", "# Add a hover tool, that sets the link data for a hovered circle\n", "code = \"\"\"\n", "var links = %s;\n", "var data = {'x0': [], 'y0': [], 'x1': [], 'y1': []};\n", "var cdata = circle.data;\n", "var indices = cb_data.index['1d'].indices;\n", "for (i=0; i < indices.length; i++) {\n", " ind0 = indices[i]\n", " for (j=0; j < links[ind0].length; j++) {\n", " ind1 = links[ind0][j];\n", " data['x0'].push(cdata.x[ind0]);\n", " data['y0'].push(cdata.y[ind0]);\n", " data['x1'].push(cdata.x[ind1]);\n", " data['y1'].push(cdata.y[ind1]);\n", " }\n", "}\n", "segment.data = data;\n", "\"\"\" % links\n", "\n", "callback = CustomJS(args={'circle': cr.data_source, 'segment': sr.data_source}, code=code)\n", "p.add_tools(HoverTool(tooltips=None, callback=callback, renderers=[cr]))\n", "\n", "show(p)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Le module [bqplot](https://github.com/bloomberg/bqplot/blob/master/examples/Interactions/Mark%20Interactions.ipynb) permet de d\u00e9finir des *callbacks* en Python. L'inconv\u00e9nient est que cela ne fonction que depuis un notebook et il vaut mieux ne pas trop m\u00e9langer les librairies javascripts qui ne peuvent pas toujours fonctionner ensemble."]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Plotly"]}, {"cell_type": "markdown", "metadata": {}, "source": ["- Plotly: https://plot.ly/python/\n", "- Doc: https://plot.ly/python/reference/\n", "- Colors: http://www.cssportal.com/css3-rgba-generator/"]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": ["import pandas as pd\n", "import numpy as np"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Creation dataframe"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "\n", " \n", "
\n", "
"], "text/plain": [" value1 value2 rate1 rate2\n", "indx \n", "a 0 1 0.00 0.01\n", "b 1 5 0.01 0.05\n", "c 2 2 0.02 0.02\n", "d 3 3 0.03 0.03\n", "e 4 7 0.04 0.07"]}, "execution_count": 37, "metadata": {}, "output_type": "execute_result"}], "source": ["indx = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']\n", "value1 = [0,1,2,3,4,5,6,7,8,9]\n", "value2 = [1,5,2,3,7,5,1,8,9,1]\n", "\n", "df = {'indx': indx, 'value1': value1, 'value2': value2}\n", "df = pd.DataFrame(df)\n", "df['rate1'] = df.value1 / 100\n", "df['rate2'] = df.value2 / 100\n", "df = df.set_index('indx')\n", "df.head()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["# Bars and Scatter"]}, {"cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": ["# installer plotly"]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Sign in failed.\n"]}], "source": ["import plotly.plotly as py\n", "import os\n", "from pyquickhelper.loghelper import get_password\n", "user = get_password(\"plotly\", \"ensae_teaching_cs,login\")\n", "pwd = get_password(\"plotly\", \"ensae_teaching_cs,pwd\")\n", "try:\n", " py.sign_in(user, pwd)\n", "except Exception as e:\n", " print(e)"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["High five! You successfully sent some data to your account on plotly. View your plot in your browser at https://plot.ly/~athean/0 or inside your plot.ly account where it is named 'marker-h-bar'\n"]}, {"data": {"text/html": [""], "text/plain": ["| \n", " | value1 | \n", "value2 | \n", "rate1 | \n", "rate2 | \n", "
|---|---|---|---|---|
| indx | \n", "\n", " | \n", " | \n", " | \n", " |
| a | \n", "0 | \n", "1 | \n", "0.00 | \n", "0.01 | \n", "
| b | \n", "1 | \n", "5 | \n", "0.01 | \n", "0.05 | \n", "
| c | \n", "2 | \n", "2 | \n", "0.02 | \n", "0.02 | \n", "
| d | \n", "3 | \n", "3 | \n", "0.03 | \n", "0.03 | \n", "
| e | \n", "4 | \n", "7 | \n", "0.04 | \n", "0.07 | \n", "