dendrograms.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dendrograms in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.8.8'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly\n",
    "plotly.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Simple Example"
   ]
  },
  {
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   "execution_count": 2,
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   "outputs": [
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       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\"seamless=\"seamless\" src=\"https://plot.ly/~chelsea_lyn/7679.embed\" height=\"100%\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "    \n",
    "import plotly.plotly as py\n",
    "from plotly.tools import FigureFactory as FF\n",
    "\n",
    "X = np.random.rand(5,5)\n",
    "dendro = FF.create_dendrogram(X)\n",
    "py.iplot(dendro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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   "outputs": [
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      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\"seamless=\"seamless\" src=\"https://plot.ly/~chelsea_lyn/7685.embed\" height=\"100%\" width=\"100%\"></iframe>"
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      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
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     "execution_count": 5,
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   "source": [
    "X = np.random.rand(10,10)\n",
    "names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark', 'Jack', 'Oxana', 'John', 'Chelsea', 'Mark']\n",
    "dendro = FF.create_dendrogram(X, orientation='bottom', labels=names)\n",
    "\n",
    "py.iplot(dendro, height=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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     "text": [
      "Help on function create_dendrogram in module plotly.tools:\n",
      "\n",
      "create_dendrogram(X, orientation='bottom', labels=None, colorscale=None)\n",
      "    BETA function that returns a dendrogram Plotly figure object.\n",
      "    \n",
      "    :param (ndarray) X: Matrix of observations as array of arrays\n",
      "    :param (str) orientation: 'top', 'right', 'bottom', or 'left'\n",
      "    :param (list) labels: List of axis category labels(observation labels)\n",
      "    :param (list) colorscale: Optional colorscale for dendrogram tree\n",
      "        clusters\n",
      "    \n",
      "    Example 1: Simple bottom oriented dendrogram\n",
      "    ```\n",
      "    import numpy as np\n",
      "    \n",
      "    import plotly.plotly as py\n",
      "    from plotly.tools import FigureFactory as FF\n",
      "    \n",
      "    X = np.random.rand(5,5)\n",
      "    dendro = FF.create_dendrogram(X)\n",
      "    py.iplot(dendro, validate=False, height=300, width=1000)\n",
      "    \n",
      "    ```\n",
      "    \n",
      "    Example 2: Dendrogram to put on the left of the heatmap\n",
      "    ```\n",
      "    X = np.random.rand(5,5)\n",
      "    names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark']\n",
      "    dendro = FF.create_dendrogram(X, orientation='right', labels=names)\n",
      "    \n",
      "    py.iplot(dendro, validate=False, height=1000, width=300)\n",
      "    ```\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(FF.create_dendrogram)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from IPython.display import display, HTML\n",
    "\n",
    "display(HTML('<link href=\"//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700\" rel=\"stylesheet\" type=\"text/css\" />'))\n",
    "display(HTML('<link rel=\"stylesheet\" type=\"text/css\" href=\"http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css\">'))\n",
    "\n",
    "! pip install publisher --upgrade\n",
    "import publisher\n",
    "publisher.publish(\n",
    "    'candlestick-charts.ipynb', 'python/candlestick-charts', 'Candlestick Charts',\n",
    "    'How to make interactive candlestick charts in Python with Plotly. '\n",
    "    'Six examples of candlestick charts with Pandas, time series, and yahoo finance data.',\n",
    "    title = 'Python Candlestick Charts | plotly',\n",
    "    thumbnail='/images/candlestick.png', language='python',\n",
    "    page_type='example_index', has_thumbnail='true', display_as='chart_type', order=28)"
   ]
  }
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