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@empet
Created October 2, 2017 19:49
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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
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{
"data": {
"text/html": [
"<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
],
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"<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
]
},
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"source": [
"from plotly.offline import download_plotlyjs, init_notebook_mode, iplot, plot\n",
"init_notebook_mode(connected=True)"
]
},
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import plotly.figure_factory as ff\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"numVectors = 100\n",
"mean = np.array([1, 2, 1])\n",
"cov = np.array([[4, .8, -.3],\n",
" [0.8, 2, .6],\n",
" [-.3, .6, 5]])\n",
"\n",
"gen_vec = np.random.multivariate_normal(mean, cov, numVectors)\n",
"df = pd.DataFrame(gen_vec, columns=['x_1', 'x_2', 'x_3'])\n",
"fig = ff.create_scatterplotmatrix(df, height=800, width=800,\n",
" )\n",
"iplot(fig)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [default]",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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