community/modules/files/fsi-montecarlo-on-batch/FSI_MonteCarlo.ipynb

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   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "project_id = \"${project_id}\"\n",
    "dataset_id = \"${dataset_id}\"\n",
    "table_id = \"${table_id}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ONI1Xo0-KtAD",
    "outputId": "fb9ca475-e4ec-4cd0-e0e6-14f409eefd7a"
   },
   "outputs": [],
   "source": [
    "from google.cloud import bigquery\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "client = bigquery.Client(project=project_id)\n",
    "\n",
    "df = client.query(f'''\n",
    "SELECT ticker, cast(price AS FLOAT64) AS price, CAST(OFFSET as INTEGER) AS offset, start_date, end_date, iteration\n",
    "FROM `{project_id}.{dataset_id}.{table_id}`,\n",
    "UNNEST(simulation_results) as NUMERIC with OFFSET\n",
    "WHERE  epoch_time IN\n",
    " # Get the latest simulation runs for each Ticker Symbol\n",
    "(SELECT MAX(epoch_time)  FROM `{project_id}.{dataset_id}.{table_id}`  GROUP BY ticker)\n",
    "'''\n",
    ").to_dataframe()\n",
    "# Display the data\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Define a function to plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def plot_ticker(t,df):\n",
    "\n",
    "    dtf = df[(df.ticker==t) &(df.offset == 250)].price.describe(include=[np.float64], percentiles=[.05, .01, .001])\n",
    "    cellText = []\n",
    "    for v in dtf.values:\n",
    "        cellText.append([v])\n",
    "        \n",
    "    pltf = df[df.ticker==t].pivot(index='offset', columns='iteration', values='price')\n",
    "    \n",
    "    fig = plt.figure(figsize=(10,5))\n",
    "    ax1 = fig.add_subplot(122)\n",
    "    pltf.plot(legend=False, ax=ax1, xlabel='Time(days)', ylabel='US$', title=f\"{ df[(df.ticker == t) & (df.offset == 0) & (df.iteration == 4)]}\")\n",
    "    ax2 = fig.add_subplot(121)\n",
    "    font_size=10\n",
    "    bbox=[0, 0, .5, 1]\n",
    "    ax2.axis('off')\n",
    "    mpl_table = ax2.table(cellText = cellText, rowLabels=dtf.index.values, bbox=bbox)\n",
    "    mpl_table.auto_set_font_size(False)\n",
    "    mpl_table.set_fontsize(font_size)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "id": "jvBmb_KceX7z",
    "outputId": "42a3ba9f-b68f-4c7b-d928-0fedeed9216c"
   },
   "outputs": [],
   "source": [
    "ticker_list = df.ticker.unique()\n",
    "for t in ticker_list:\n",
    "    plot_ticker(t,df)"
   ]
  }
 ],
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