Illustrating the properties of statistical distributions with numpy and plotly

Numpy Distributions with Plotly.ipynb

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      "import numpy as np\n",
      "import numpy.random as nr\n",
      "import plotly\n",
      "py = plotly.plotly('IPython.Demo', '1fw3zw2o13')"
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      "\n",
      "distributions = [nr.uniform, nr.normal , lambda size: nr.normal(0, 0.2, size=size),\n",
      "                 lambda size: nr.beta(a=0.5, b=0.5, size=size),\n",
      "                 lambda size: nr.beta(a=0.5, b=2, size=size)]\n",
      "\n",
      "names = ['Uniform(0,1)', 'Normal(0,1)', 'Normal(0, 0.2)', 'beta(a=0.5, b=0.5)', 'beta(a=0.5, b=2)']\n",
      "\n",
      "boxes = [{'y': dist(size=50), 'type': 'box', 'boxpoints': 'all', 'jitter': 0.5, 'pointpos': -1.8,\n",
      "        'name': name} for dist, name in zip(distributions, names)]\n",
      "\n",
      "layout = {'title': 'A few distributions',\n",
      "          'showlegend': False,\n",
      "          'xaxis': {'ticks': '', 'showgrid': False, 'showline': False}\n",
      "          'yaxis': {'zeroline': False, 'ticks': '', 'showline': False},\n",
      "          }\n",
      "\n",
      "py.iplot(boxes, layout = layout, filename='Distributions', fileopt='overwrite', width=1000, height=650)"
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