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@alexander-daniel
Created January 7, 2014 21:40
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"cells": [
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"cell_type": "code",
"collapsed": false,
"input": [
"import plotly\n",
"from numpy import *"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"py = plotly.plotly(username='username',key='api_key')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
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{
"cell_type": "code",
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"input": [
"layout = {\n",
"\t'autosize': False,\n",
"\t'width': 600,\n",
"\t'height': 400,\n",
"\t'showlegend': False,\n",
"\n",
"\t'xaxis' : {\n",
"\t\t\"linecolor\":\"rgba(0, 0, 0, 0)\",\"ticks\":\"\",\n",
"\t\t\"showgrid\":False,\n",
"\t\t\"zeroline\":False,\n",
"\t\t\"showticklabels\":False\n",
"\t},\n",
"\n",
"\t'yaxis' : {\n",
"\t\t\"linecolor\":\"rgba(0, 0, 0, 0)\",\n",
"\t\t\"ticks\":\"\",\n",
"\t\t\"showgrid\":False,\n",
"\t\t\"zeroline\":False,\n",
"\t\t\"showticklabels\":False}\n",
"}\n",
"\n",
"py.iplot([{\n",
"\t'y': random.randn(5000),\n",
"\t'type': 'histogramy', \n",
"\t'histnorm':'probability density',\n",
"\t'autobinx': False,\n",
"\t'xbins':{\n",
"\t\t'start': -2.5,\n",
"\t\t'end': 3,\t\n",
"\t\t'size': 0.5\n",
"\t}\n",
"}, \n",
"\n",
"{\n",
"\t'x':linspace(-5,5,100),\n",
"\t'y': 1./sqrt(2*3.14)*exp(-linspace(-5,5,100)**2/2.),\n",
"\t'fill':'tozeroy',\n",
"\t'marker':{\n",
"\t\t'color': \"rgba(111, 168, 220, 0.44)\"\n",
"\t\t}\n",
"}],\n",
"layout=layout)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"\n"
]
},
{
"html": [
"<iframe height=\"650\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~demos/981/600/600\" width=\"650\"></iframe>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 15,
"text": [
"<IPython.core.display.HTML at 0x10a66e410>"
]
}
],
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},
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"cell_type": "code",
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"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
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"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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