testing-multiplot.ipynb

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   "cell_type": "code",
   "execution_count": 27,
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.set(style=\"ticks\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
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   "source": [
    "# Create a dataset with many short random walks\n",
    "rs = np.random.RandomState(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
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   "source": [
    "pos = rs.randint(-1, 2, (20, 5)).cumsum(axis=1)"
   ]
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   "source": [
    "pos -= pos[:, 0, np.newaxis]"
   ]
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   "cell_type": "code",
   "execution_count": 31,
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   "source": [
    "step = np.tile(range(5), 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
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   "outputs": [],
   "source": [
    "walk = np.repeat(range(20), 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
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   "outputs": [],
   "source": [
    "df = pd.DataFrame(np.c_[pos.flat, step, walk],\n",
    "                  columns=[\"position\", \"step\", \"walk\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
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   "source": [
    "# Initialize a grid of plots with an Axes for each walk\n",
    "grid = sns.FacetGrid(df, col=\"walk\", hue=\"walk\", col_wrap=5, size=1.5)\n",
    "\n",
    "# Draw a horizontal line to show the starting point\n",
    "grid.map(plt.axhline, y=0, ls=\":\", c=\".5\")\n",
    "\n",
    "# Draw a line plot to show the trajectory of each random walk\n",
    "grid.map(plt.plot, \"step\", \"position\", marker=\"o\", ms=4)\n",
    "\n",
    "# Adjust the tick positions and labels\n",
    "grid.set(xticks=np.arange(5), yticks=[-3, 3],\n",
    "         xlim=(-.5, 4.5), ylim=(-3.5, 3.5))\n",
    "\n",
    "# Adjust the arrangement of the plots\n",
    "grid.fig.tight_layout(w_pad=1)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "source": []
  }
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