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"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"from bokeh.plotting import figure, show\n",
"from bokeh.io import output_notebook, push_notebook\n",
"from bokeh.layouts import layout\n",
"from bokeh.models import ColumnDataSource, CustomJS, DataRange1d, LinearAxis, Range1d, DateFormatter\n",
"from bokeh.models.widgets import DataTable, TableColumn\n",
"\n",
"from ipywidgets import interact\n",
"\n",
"output_notebook()"
]
},
{
"cell_type": "code",
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"source": [
"ix = pd.date_range('2016-01-01', '2017-01-01', freq='d', name='date')\n",
"srs = pd.Series(np.random.randint(0, 300, size=len(ix)), index=ix, name='volume')\n",
"srs2 = pd.Series(np.random.randint(0, 1000, size=len(ix)), index=ix, name='size')"
]
},
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Application\",\"version\":\"0.12.4\"}};\n",
" var render_items = [{\"docid\":\"d2f5e816-9498-4acf-9e87-256e2a8fe471\",\"elementid\":\"e095a58d-479f-494f-a4ed-8c12d5d31f2b\",\"modelid\":\"8f8de0be-6eac-427e-9f4a-e20d21d93e83\",\"notebook_comms_target\":\"bbd2ee72-8aaf-4558-be28-e3765dc85abb\"}];\n",
" \n",
" Bokeh.embed.embed_items(docs_json, render_items);\n",
" };\n",
" if (document.readyState != \"loading\") fn();\n",
" else document.addEventListener(\"DOMContentLoaded\", fn);\n",
" })();\n",
" },\n",
" function(Bokeh) {\n",
" }\n",
" ];\n",
" \n",
" function run_inline_js() {\n",
" \n",
" if ((window.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i](window.Bokeh);\n",
" }if (force === true) {\n",
" display_loaded();\n",
" }} else if (Date.now() < window._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!window._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" window._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(\"e095a58d-479f-494f-a4ed-8c12d5d31f2b\")).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\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));\n",
"</script>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def get_data(freq='MS'):\n",
" return pd.DataFrame(srs.groupby(pd.Grouper(freq=freq)).sum())\n",
"\n",
"def get_data2(freq='MS'):\n",
" return pd.DataFrame(srs2.groupby(pd.Grouper(freq=freq)).sum())\n",
"\n",
"source = ColumnDataSource(data=ColumnDataSource.from_df(get_data()))\n",
"source2 = ColumnDataSource(data=ColumnDataSource.from_df(get_data2()))\n",
"source_s = ColumnDataSource(data=ColumnDataSource.from_df(get_data() * .1))\n",
"\n",
"def get_width():\n",
" mindate = min(source.data['date'])\n",
" maxdate = max(source.data['date'])\n",
" return 0.8 * (maxdate-mindate).total_seconds() * 1000 / len(source.data['date'])\n",
"\n",
"def get_width_s():\n",
" mindate = min(source_s.data['date'])\n",
" maxdate = max(source_s.data['date'])\n",
" return 0.8 * (maxdate-mindate).total_seconds() * 1000 / len(source_s.data['date'])\n",
"\n",
"f = figure(plot_width=550, plot_height=400, x_axis_type=\"datetime\", y_range=Range1d(0, max(source.data['volume']), bounds='auto'))\n",
"f.x_range.bounds='auto'\n",
"\n",
"f.extra_y_ranges = {\n",
" \"size\": Range1d(bounds='auto', start=0, end=max(source2.data['size'])),\n",
"}\n",
"\n",
"f.add_layout(LinearAxis(y_range_name='size'), 'right')\n",
"\n",
"r = f.vbar(source=source, top='volume', x='date', width=get_width())\n",
"r2 = f.vbar(source=source_s, top='volume', x='date', width=get_width(), color='green')\n",
"\n",
"f.line(source=source2, x='date', y='size', color='red', y_range_name='size')\n",
"f.tools[2].dimensions = 'width'\n",
"\n",
"handle = show(f, notebook_handle=True)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2017-01-27T21:46:59.693339",
"start_time": "2017-01-27T21:46:59.595852"
},
"collapsed": false,
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {
"col": 0,
"height": 2,
"hidden": false,
"row": 0,
"width": 12
},
"report_default": {
"hidden": false
}
}
}
}
},
"outputs": [],
"source": [
"def update_data(freq={'Quarter': 'QS', 'Month': 'MS', 'Week': 'W'}):\n",
" source.data = ColumnDataSource.from_df(get_data(freq))\n",
" source2.data = ColumnDataSource.from_df(get_data2(freq))\n",
" source_s.data = ColumnDataSource.from_df(get_data(freq) * .1)\n",
"\n",
" r.glyph.width = get_width()\n",
" r2.glyph.width = get_width_s()\n",
"\n",
" f.y_range.end = max(source.data['volume'])\n",
" f.extra_y_ranges['size'].end = max(source2.data['size'])\n",
"\n",
" push_notebook(handle=handle)\n",
" \n",
"i = interact(update_data)"
]
}
],
"metadata": {
"extensions": {
"jupyter_dashboards": {
"activeView": "grid_default",
"version": 1,
"views": {
"grid_default": {
"cellMargin": 10,
"defaultCellHeight": 20,
"layoutStrategy": "packed",
"maxColumns": 12,
"name": "grid",
"type": "grid"
},
"report_default": {
"name": "report",
"type": "report"
}
}
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