Demo fill_alpha.ipynb

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   "source": [
    "## Poor-man's stacked plot using fill_alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from math import sin\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import trappy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create some data"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
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   "outputs": [],
   "source": [
    "n = 10\n",
    "cubes = [x ** 3 for x in range(n)]\n",
    "squares = [x ** 2 for x in range(n)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use DataFrame::apply(np.cumsum, axis=1) to pre-process DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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    "collapsed": true
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   "source": [
    "df = pd.DataFrame({\"cubes\": cubes, \"squares\": squares}, index=range(10)).apply(np.cumsum, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use fill_alpha=1.0 to show the sum of `cubes` and `squares` and contribution of each"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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   "outputs": [
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   "source": [
    "trappy.ILinePlot(df, column=df.columns.tolist(), drawstyle=\"steps-post\", fill_alpha=1.0).view()"
   ]
  }
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By the way, the JavaScript doesn't work when it's hosted on GitHub so you'll need to download this and view it from a local notebook server.