BQ_DataVisualization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/zjc664656505/BQ_PROJECT/blob/main/BQ_DataVisualization.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NnLMSPq3kP07"
   },
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Oy8TdzQ9FjPL",
    "outputId": "565dc558-1bb6-4a09-92a7-1ed4bd7b961a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive\n"
     ]
    }
   ],
   "source": [
    "#Mount to your google drive\n",
    "from google.colab import drive\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib import cm\n",
    "drive.mount('/content/drive', force_remount= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "Nm8Qzazca9EN"
   },
   "outputs": [],
   "source": [
    "#define method for feature selection\n",
    "def feature_selection(dataframe, feature_list):\n",
    "  '''\n",
    "    This is a method which returns the new dataframe in which the features are selected\n",
    "  '''\n",
    "  return dataframe[feature_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "trRdORlSa9I8"
   },
   "outputs": [],
   "source": [
    "# Financial feature list\n",
    "companies_variables_feature_list = ['bq_id', 'bq_year', 'bq_revenue', 'bq_ebitda', 'bq_cor', 'bq_net_income', \n",
    "                           'bq_gross_profit', 'bq_total_assets','bq_operating_expenses',\n",
    "                           'bq_operating_income',  'bq_tax_and_interest',\n",
    "                           'bq_gross_profit_margin', 'bq_ebitda_margin', 'bq_asset_turnover',\n",
    "                           'bq_net_profit_margin', 'bq_return_on_assets', 'bq_return_on_sales']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HICmsZULa9Le",
    "outputId": "4e1486cb-7d36-4d0b-de4b-b58665e780ac"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (102) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "company_variables_ts_df1 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_1.csv'), companies_variables_feature_list)\n",
    "company_variables_ts_df2 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_2.csv'), companies_variables_feature_list)\n",
    "company_variables_ts_df3 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_3.csv'), companies_variables_feature_list)\n",
    "company_variables_ts_df4 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_4.csv'), companies_variables_feature_list)\n",
    "company_variables_ts_df5 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_5.csv'), companies_variables_feature_list)\n",
    "company_variables_ts_df6 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_6.csv'), companies_variables_feature_list)\n",
    "company_variables_ts_df7 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/company_variables_ts_7.csv'), companies_variables_feature_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "vJsYPY5fa9Qe"
   },
   "outputs": [],
   "source": [
    "company_variables_ts_df1 = company_variables_ts_df1[(company_variables_ts_df1.bq_year >= 2015) & (company_variables_ts_df1.bq_year <= 2020)]\n",
    "company_variables_ts_df2 = company_variables_ts_df2[(company_variables_ts_df2.bq_year >= 2015) & (company_variables_ts_df2.bq_year <= 2020)]\n",
    "company_variables_ts_df3 = company_variables_ts_df3[(company_variables_ts_df3.bq_year >= 2015) & (company_variables_ts_df3.bq_year <= 2020)]\n",
    "company_variables_ts_df4 = company_variables_ts_df4[(company_variables_ts_df4.bq_year >= 2015) & (company_variables_ts_df4.bq_year <= 2020)]\n",
    "company_variables_ts_df5 = company_variables_ts_df5[(company_variables_ts_df5.bq_year >= 2015) & (company_variables_ts_df5.bq_year <= 2020)]\n",
    "company_variables_ts_df6 = company_variables_ts_df6[(company_variables_ts_df6.bq_year >= 2015) & (company_variables_ts_df6.bq_year <= 2020)]\n",
    "company_variables_ts_df7 = company_variables_ts_df7[(company_variables_ts_df7.bq_year >= 2015) & (company_variables_ts_df7.bq_year <= 2020)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "1KFadQFEa9Vd"
   },
   "outputs": [],
   "source": [
    "# Combine the 7 company_variables_ts_df dataframes together\n",
    "company_variables_ts_df = pd.concat([company_variables_ts_df1, company_variables_ts_df2, company_variables_ts_df3, company_variables_ts_df4, \n",
    "                company_variables_ts_df5, company_variables_ts_df6, company_variables_ts_df7], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "nXUbU9onbm-v"
   },
   "outputs": [],
   "source": [
    "company_variables_ts_df = company_variables_ts_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "LZHg3YFBbnEH"
   },
   "outputs": [],
   "source": [
    "company_variables_ts_df.to_csv('/content/drive/MyDrive/BrightQuery_Project/prepro_data/financials_data.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RyZpvgbQkPMZ"
   },
   "source": [
    "## Important Sectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 607
    },
    "id": "XpcbaE-6-Kgv",
    "outputId": "6ea9c954-4d57-40ae-b87c-e36db09bf041"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sectors</th>\n",
       "      <th>Number of Companies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>1047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Finance and Insurance</td>\n",
       "      <td>565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Information</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Real Estate and Rental and Leasing</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Wholesale  Trade</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Mining</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Management of Companies (Holding Companies)</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Health Care and Social Assistance</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Transportation and Warehousing</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Utilities</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Accommodation and Food Services</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Administrative and Support and Waste Managemen...</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Construction</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Other Services</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Arts, Entertainment, and Recreation</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Agriculture, Forestry, Fishing and Hunting</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Sectors  Number of Companies\n",
       "0                                       Manufacturing                 1047\n",
       "1    Professional, Scientific, and Technical Services                  588\n",
       "2                               Finance and Insurance                  565\n",
       "3                                         Information                  180\n",
       "4                                        Retail Trade                  147\n",
       "5                  Real Estate and Rental and Leasing                  130\n",
       "6                                    Wholesale  Trade                  131\n",
       "7                                              Mining                  117\n",
       "8         Management of Companies (Holding Companies)                  108\n",
       "9                   Health Care and Social Assistance                   84\n",
       "10                     Transportation and Warehousing                   84\n",
       "11                                          Utilities                   76\n",
       "12                    Accommodation and Food Services                   61\n",
       "13  Administrative and Support and Waste Managemen...                   48\n",
       "14                                       Construction                   47\n",
       "15                                     Other Services                   33\n",
       "16                Arts, Entertainment, and Recreation                   22\n",
       "17         Agriculture, Forestry, Fishing and Hunting                   17"
      ]
     },
     "execution_count": 9,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_com_sectors = pd.read_excel('/content/drive/MyDrive/BrightQuery_Project/prepro_data/numberOfCompaniesInSectors.xlsx')\n",
    "num_com_sectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 443
    },
    "id": "GS8J9jDt-u-3",
    "outputId": "963c001c-949b-4030-b262-77c0ba7b770b"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "fig.suptitle('Number of Companies in Different Sectors in 2020', fontsize=24)\n",
    "ax = sns.barplot(y=\"Sectors\", x=\"Number of Companies\", data=num_com_sectors, color=\"salmon\", saturation=.5)\n",
    "ax.set_xlabel(\"Number of Companies\",fontsize=18)\n",
    "ax.set_ylabel(\"Sectors\",fontsize=18)\n",
    "ax.tick_params(labelsize=14)\n",
    "for p in ax.patches:\n",
    "    ax.annotate(\"%.0f\" % p.get_width(), xy=(p.get_width(), p.get_y()+p.get_height()/2), xytext=(0, 0), \n",
    "            textcoords='offset points', ha=\"left\", va=\"center\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DTedK8NgkrQz"
   },
   "source": [
    "## Pearson Correlations Between Financial Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "Fwf6awiEcE8T"
   },
   "outputs": [],
   "source": [
    "company_variables_ts_df = pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/prepro_data/financials_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 379
    },
    "id": "ZV4TQn4GcQTR",
    "outputId": "0c1e4d26-6366-4fcb-ba10-82741af50ddd"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <th>bq_total_assets</th>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>385968350</td>\n",
       "      <td>2016</td>\n",
       "      <td>21826755.0</td>\n",
       "      <td>1563723.0</td>\n",
       "      <td>11226528.0</td>\n",
       "      <td>437456.0</td>\n",
       "      <td>10600227.0</td>\n",
       "      <td>15065495.0</td>\n",
       "      <td>8806440.0</td>\n",
       "      <td>1793787.0</td>\n",
       "      <td>1356331.0</td>\n",
       "      <td>0.485653</td>\n",
       "      <td>0.071642</td>\n",
       "      <td>1.448791</td>\n",
       "      <td>0.020042</td>\n",
       "      <td>0.029037</td>\n",
       "      <td>0.082183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>385968350</td>\n",
       "      <td>2020</td>\n",
       "      <td>30895324.0</td>\n",
       "      <td>2264126.0</td>\n",
       "      <td>16059616.0</td>\n",
       "      <td>738735.0</td>\n",
       "      <td>14835708.0</td>\n",
       "      <td>22341285.0</td>\n",
       "      <td>13295732.0</td>\n",
       "      <td>1539976.0</td>\n",
       "      <td>801241.0</td>\n",
       "      <td>0.480193</td>\n",
       "      <td>0.073284</td>\n",
       "      <td>1.382880</td>\n",
       "      <td>0.023911</td>\n",
       "      <td>0.033066</td>\n",
       "      <td>0.049845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>902965274</td>\n",
       "      <td>2020</td>\n",
       "      <td>8395804.0</td>\n",
       "      <td>2663960.0</td>\n",
       "      <td>1646032.0</td>\n",
       "      <td>1231238.0</td>\n",
       "      <td>6749772.0</td>\n",
       "      <td>56657933.0</td>\n",
       "      <td>4772877.0</td>\n",
       "      <td>1976895.0</td>\n",
       "      <td>745657.0</td>\n",
       "      <td>0.803946</td>\n",
       "      <td>0.317297</td>\n",
       "      <td>0.148184</td>\n",
       "      <td>0.146649</td>\n",
       "      <td>0.021731</td>\n",
       "      <td>0.235462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>133533004</td>\n",
       "      <td>2020</td>\n",
       "      <td>97606.0</td>\n",
       "      <td>12514.0</td>\n",
       "      <td>54017.0</td>\n",
       "      <td>2101.0</td>\n",
       "      <td>43589.0</td>\n",
       "      <td>206536.0</td>\n",
       "      <td>34919.0</td>\n",
       "      <td>8670.0</td>\n",
       "      <td>6569.0</td>\n",
       "      <td>0.446581</td>\n",
       "      <td>0.128209</td>\n",
       "      <td>0.472586</td>\n",
       "      <td>0.021525</td>\n",
       "      <td>0.010173</td>\n",
       "      <td>0.088827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>560821475</td>\n",
       "      <td>2020</td>\n",
       "      <td>241957.0</td>\n",
       "      <td>32723.0</td>\n",
       "      <td>143432.0</td>\n",
       "      <td>13493.0</td>\n",
       "      <td>98525.0</td>\n",
       "      <td>196559.0</td>\n",
       "      <td>77756.0</td>\n",
       "      <td>20769.0</td>\n",
       "      <td>7276.0</td>\n",
       "      <td>0.407200</td>\n",
       "      <td>0.135243</td>\n",
       "      <td>1.230964</td>\n",
       "      <td>0.055766</td>\n",
       "      <td>0.068646</td>\n",
       "      <td>0.085838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>392538354</td>\n",
       "      <td>2018</td>\n",
       "      <td>5457687.0</td>\n",
       "      <td>984236.0</td>\n",
       "      <td>3076250.0</td>\n",
       "      <td>374786.0</td>\n",
       "      <td>2381437.0</td>\n",
       "      <td>7673212.0</td>\n",
       "      <td>1647201.0</td>\n",
       "      <td>734236.0</td>\n",
       "      <td>359450.0</td>\n",
       "      <td>0.436345</td>\n",
       "      <td>0.180339</td>\n",
       "      <td>0.711265</td>\n",
       "      <td>0.068671</td>\n",
       "      <td>0.048843</td>\n",
       "      <td>0.134532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>392538354</td>\n",
       "      <td>2015</td>\n",
       "      <td>3972693.0</td>\n",
       "      <td>659884.0</td>\n",
       "      <td>2228981.0</td>\n",
       "      <td>165366.0</td>\n",
       "      <td>1743712.0</td>\n",
       "      <td>5608031.0</td>\n",
       "      <td>1253988.0</td>\n",
       "      <td>489724.0</td>\n",
       "      <td>324358.0</td>\n",
       "      <td>0.438924</td>\n",
       "      <td>0.166105</td>\n",
       "      <td>0.708394</td>\n",
       "      <td>0.041626</td>\n",
       "      <td>0.029487</td>\n",
       "      <td>0.123273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>392538354</td>\n",
       "      <td>2016</td>\n",
       "      <td>4975882.0</td>\n",
       "      <td>907818.0</td>\n",
       "      <td>2752433.0</td>\n",
       "      <td>306190.0</td>\n",
       "      <td>2223449.0</td>\n",
       "      <td>7098367.0</td>\n",
       "      <td>1505599.0</td>\n",
       "      <td>717850.0</td>\n",
       "      <td>411660.0</td>\n",
       "      <td>0.446845</td>\n",
       "      <td>0.182444</td>\n",
       "      <td>0.700990</td>\n",
       "      <td>0.061535</td>\n",
       "      <td>0.043135</td>\n",
       "      <td>0.144266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>392538354</td>\n",
       "      <td>2020</td>\n",
       "      <td>4963714.0</td>\n",
       "      <td>652843.0</td>\n",
       "      <td>2896344.0</td>\n",
       "      <td>-139265.0</td>\n",
       "      <td>2067370.0</td>\n",
       "      <td>9470912.0</td>\n",
       "      <td>1751321.0</td>\n",
       "      <td>316049.0</td>\n",
       "      <td>455314.0</td>\n",
       "      <td>0.416497</td>\n",
       "      <td>0.131523</td>\n",
       "      <td>0.524101</td>\n",
       "      <td>-0.028057</td>\n",
       "      <td>-0.014704</td>\n",
       "      <td>0.063672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>392538354</td>\n",
       "      <td>2017</td>\n",
       "      <td>5018158.0</td>\n",
       "      <td>939773.0</td>\n",
       "      <td>2822209.0</td>\n",
       "      <td>375623.0</td>\n",
       "      <td>2195949.0</td>\n",
       "      <td>6978073.0</td>\n",
       "      <td>1492609.0</td>\n",
       "      <td>703340.0</td>\n",
       "      <td>327717.0</td>\n",
       "      <td>0.437601</td>\n",
       "      <td>0.187274</td>\n",
       "      <td>0.719132</td>\n",
       "      <td>0.074853</td>\n",
       "      <td>0.053829</td>\n",
       "      <td>0.140159</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       bq_id  bq_year  ...  bq_return_on_assets  bq_return_on_sales\n",
       "0  385968350     2016  ...             0.029037            0.082183\n",
       "1  385968350     2020  ...             0.033066            0.049845\n",
       "2  902965274     2020  ...             0.021731            0.235462\n",
       "3  133533004     2020  ...             0.010173            0.088827\n",
       "4  560821475     2020  ...             0.068646            0.085838\n",
       "5  392538354     2018  ...             0.048843            0.134532\n",
       "6  392538354     2015  ...             0.029487            0.123273\n",
       "7  392538354     2016  ...             0.043135            0.144266\n",
       "8  392538354     2020  ...            -0.014704            0.063672\n",
       "9  392538354     2017  ...             0.053829            0.140159\n",
       "\n",
       "[10 rows x 17 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "company_variables_ts_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "Utd2ce1yeSxz"
   },
   "outputs": [],
   "source": [
    "dataset = company_variables_ts_df.drop(['bq_id', 'bq_year'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 534
    },
    "id": "jJt5uAPLcZhr",
    "outputId": "17153b4f-74c0-417a-b17d-8a50254a46af"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <th>bq_total_assets</th>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bq_revenue</th>\n",
       "      <td>1.00</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_ebitda</th>\n",
       "      <td>0.77</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_cor</th>\n",
       "      <td>0.95</td>\n",
       "      <td>0.60</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.40</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
       "      <th>bq_net_income</th>\n",
       "      <td>0.61</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <td>0.82</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.78</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_total_assets</th>\n",
       "      <td>0.33</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.55</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <td>0.81</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.52</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_operating_income</th>\n",
       "      <td>0.67</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <td>0.54</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.73</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.58</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.62</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        bq_revenue  ...  bq_return_on_sales\n",
       "bq_revenue                    1.00  ...                0.00\n",
       "bq_ebitda                     0.77  ...                0.00\n",
       "bq_cor                        0.95  ...                0.00\n",
       "bq_net_income                 0.61  ...                0.00\n",
       "bq_gross_profit               0.82  ...                0.00\n",
       "bq_total_assets               0.33  ...                0.00\n",
       "bq_operating_expenses         0.81  ...               -0.00\n",
       "bq_operating_income           0.67  ...                0.00\n",
       "bq_tax_and_interest           0.54  ...                0.00\n",
       "bq_gross_profit_margin        0.00  ...                0.05\n",
       "bq_ebitda_margin              0.00  ...                0.82\n",
       "bq_asset_turnover            -0.01  ...                0.00\n",
       "bq_net_profit_margin          0.00  ...                0.79\n",
       "bq_return_on_assets           0.00  ...                0.02\n",
       "bq_return_on_sales            0.00  ...                1.00\n",
       "\n",
       "[15 rows x 15 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corrdata = dataset.corr()\n",
    "corrdata.round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 317
    },
    "id": "5yxVfZ6BhKy1",
    "outputId": "02ed69bf-c420-4467-89c0-c0df6a1d54a2"
   },
   "outputs": [
    {
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       "      <th>bq_revenue</th>\n",
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       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "      <td>3.436719e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.233856e+07</td>\n",
       "      <td>8.652610e+06</td>\n",
       "      <td>3.045173e+07</td>\n",
       "      <td>3.499581e+06</td>\n",
       "      <td>2.188683e+07</td>\n",
       "      <td>1.542308e+08</td>\n",
       "      <td>1.619939e+07</td>\n",
       "      <td>5.687434e+06</td>\n",
       "      <td>2.187854e+06</td>\n",
       "      <td>4.113036e-01</td>\n",
       "      <td>1.040414e-01</td>\n",
       "      <td>1.258204e+00</td>\n",
       "      <td>9.020271e-03</td>\n",
       "      <td>2.800514e-02</td>\n",
       "      <td>5.538686e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.604305e+09</td>\n",
       "      <td>2.936969e+08</td>\n",
       "      <td>1.153243e+09</td>\n",
       "      <td>1.648732e+08</td>\n",
       "      <td>6.115843e+08</td>\n",
       "      <td>1.102720e+10</td>\n",
       "      <td>4.416085e+08</td>\n",
       "      <td>2.154298e+08</td>\n",
       "      <td>8.202092e+07</td>\n",
       "      <td>1.880099e-01</td>\n",
       "      <td>1.920591e+01</td>\n",
       "      <td>6.124149e-01</td>\n",
       "      <td>2.026789e+01</td>\n",
       "      <td>4.630711e+01</td>\n",
       "      <td>1.565567e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-2.008705e+09</td>\n",
       "      <td>-1.519100e+10</td>\n",
       "      <td>-7.687070e+08</td>\n",
       "      <td>-2.235500e+10</td>\n",
       "      <td>-1.280800e+10</td>\n",
       "      <td>6.500000e+02</td>\n",
       "      <td>-5.495512e+09</td>\n",
       "      <td>-1.933900e+10</td>\n",
       "      <td>-1.517811e+10</td>\n",
       "      <td>-7.431911e+01</td>\n",
       "      <td>-2.420700e+04</td>\n",
       "      <td>-3.402154e-01</td>\n",
       "      <td>-2.441400e+04</td>\n",
       "      <td>-8.512864e+04</td>\n",
       "      <td>-2.457700e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.139890e+06</td>\n",
       "      <td>1.457615e+05</td>\n",
       "      <td>5.813260e+05</td>\n",
       "      <td>4.721500e+04</td>\n",
       "      <td>4.339095e+05</td>\n",
       "      <td>9.785320e+05</td>\n",
       "      <td>3.327410e+05</td>\n",
       "      <td>8.905800e+04</td>\n",
       "      <td>3.299700e+04</td>\n",
       "      <td>3.062157e-01</td>\n",
       "      <td>9.627987e-02</td>\n",
       "      <td>9.088349e-01</td>\n",
       "      <td>3.008025e-02</td>\n",
       "      <td>3.406980e-02</td>\n",
       "      <td>5.959899e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.137895e+06</td>\n",
       "      <td>4.151730e+05</td>\n",
       "      <td>1.714335e+06</td>\n",
       "      <td>1.509810e+05</td>\n",
       "      <td>1.156882e+06</td>\n",
       "      <td>2.880131e+06</td>\n",
       "      <td>8.824190e+05</td>\n",
       "      <td>2.566250e+05</td>\n",
       "      <td>9.683400e+04</td>\n",
       "      <td>3.884893e-01</td>\n",
       "      <td>1.246826e-01</td>\n",
       "      <td>1.223154e+00</td>\n",
       "      <td>4.646741e-02</td>\n",
       "      <td>5.174280e-02</td>\n",
       "      <td>7.946022e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.912448e+06</td>\n",
       "      <td>1.290068e+06</td>\n",
       "      <td>5.740420e+06</td>\n",
       "      <td>4.860500e+05</td>\n",
       "      <td>3.638321e+06</td>\n",
       "      <td>9.907153e+06</td>\n",
       "      <td>2.783170e+06</td>\n",
       "      <td>8.248990e+05</td>\n",
       "      <td>3.322925e+05</td>\n",
       "      <td>4.718245e-01</td>\n",
       "      <td>1.681742e-01</td>\n",
       "      <td>1.569494e+00</td>\n",
       "      <td>6.835156e-02</td>\n",
       "      <td>7.558525e-02</td>\n",
       "      <td>1.064414e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.487430e+11</td>\n",
       "      <td>8.380600e+10</td>\n",
       "      <td>4.128020e+11</td>\n",
       "      <td>5.953100e+10</td>\n",
       "      <td>1.527570e+11</td>\n",
       "      <td>3.985749e+12</td>\n",
       "      <td>1.298580e+11</td>\n",
       "      <td>7.123000e+10</td>\n",
       "      <td>2.955900e+10</td>\n",
       "      <td>4.253057e+00</td>\n",
       "      <td>1.060404e+03</td>\n",
       "      <td>2.318352e+01</td>\n",
       "      <td>1.056466e+03</td>\n",
       "      <td>1.273217e+02</td>\n",
       "      <td>1.008538e+02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         bq_revenue     bq_ebitda  ...  bq_return_on_assets  bq_return_on_sales\n",
       "count  3.436719e+06  3.436719e+06  ...         3.436719e+06        3.436719e+06\n",
       "mean   5.233856e+07  8.652610e+06  ...         2.800514e-02        5.538686e-02\n",
       "std    1.604305e+09  2.936969e+08  ...         4.630711e+01        1.565567e+01\n",
       "min   -2.008705e+09 -1.519100e+10  ...        -8.512864e+04       -2.457700e+04\n",
       "25%    1.139890e+06  1.457615e+05  ...         3.406980e-02        5.959899e-02\n",
       "50%    3.137895e+06  4.151730e+05  ...         5.174280e-02        7.946022e-02\n",
       "75%    9.912448e+06  1.290068e+06  ...         7.558525e-02        1.064414e-01\n",
       "max    5.487430e+11  8.380600e+10  ...         1.273217e+02        1.008538e+02\n",
       "\n",
       "[8 rows x 15 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "Z36XnB2tcvVe",
    "outputId": "63995799-070a-4927-8445-1c65f5e4a427"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0, 'bq_revenue'),\n",
       " Text(1.5, 0, 'bq_ebitda'),\n",
       " Text(2.5, 0, 'bq_cor'),\n",
       " Text(3.5, 0, 'bq_net_income'),\n",
       " Text(4.5, 0, 'bq_gross_profit'),\n",
       " Text(5.5, 0, 'bq_total_assets'),\n",
       " Text(6.5, 0, 'bq_operating_expenses'),\n",
       " Text(7.5, 0, 'bq_operating_income'),\n",
       " Text(8.5, 0, 'bq_tax_and_interest'),\n",
       " Text(9.5, 0, 'bq_gross_profit_margin'),\n",
       " Text(10.5, 0, 'bq_ebitda_margin'),\n",
       " Text(11.5, 0, 'bq_asset_turnover'),\n",
       " Text(12.5, 0, 'bq_net_profit_margin'),\n",
       " Text(13.5, 0, 'bq_return_on_assets'),\n",
       " Text(14.5, 0, 'bq_return_on_sales')]"
      ]
     },
     "execution_count": 16,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x900 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colormap = plt.cm.coolwarm\n",
    "# mask = np.triu(np.ones_like(corrdata.round(3), dtype=np.bool))\n",
    "plt.figure(figsize=(6*2.5,5*2.5));\n",
    "plt.title('Pearson Correlations Between Financial Features', y=1, size=25);\n",
    "g = sns.heatmap(corrdata.round(3), linewidths=0.1, vmin = -1.0, vmax=1.0, square=True, cmap=colormap, center = 0, linecolor='white', annot=True);\n",
    "g.set_xticklabels(g.get_xticklabels(), rotation=45, horizontalalignment='right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7P6xv_94c1B2",
    "outputId": "2eb6e514-a8ee-4204-9133-c3de6fc86a43"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (58,59,60) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n",
      "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (59) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "companies_feature_list = ['bq_id', 'bq_sector_name', 'bq_company_address1_state','bq_company_name', 'bq_public_indicator']\n",
    "companies_df1 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/companies_1.csv'), companies_feature_list)\n",
    "companies_df2 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/companies_2.csv'), companies_feature_list)\n",
    "companies_df3 = feature_selection(pd.read_csv('/content/drive/MyDrive/BrightQuery_Project/cleaned_data/companies_3.csv'), companies_feature_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 359
    },
    "id": "vO24R-g1c1IH",
    "outputId": "e25860a9-fd1a-4b99-cabe-6ea8214934fe"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_company_name</th>\n",
       "      <th>bq_public_indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>777704001</td>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>NJ</td>\n",
       "      <td>JAY G TRACHTENBERG</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>699258395</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>CA</td>\n",
       "      <td>DARRELL WILLIAMS CHEVRON, INC.</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>298415539</td>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>TN</td>\n",
       "      <td>C2RL, INC. ENGINEERS</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>312414242</td>\n",
       "      <td>Health Care and Social Assistance</td>\n",
       "      <td>PR</td>\n",
       "      <td>ELIASIN MUNOZ/ LAURA MATA</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>289867643</td>\n",
       "      <td>Construction</td>\n",
       "      <td>FL</td>\n",
       "      <td>HI-TECH ROOFING &amp; SHEETMETAL INC.</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>204048886</td>\n",
       "      <td>Information</td>\n",
       "      <td>OH</td>\n",
       "      <td>DYNAMICS ONLINE</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>457397418</td>\n",
       "      <td>Construction</td>\n",
       "      <td>GA</td>\n",
       "      <td>AQS, INC. KOTZE</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>777141037</td>\n",
       "      <td>Construction</td>\n",
       "      <td>KY</td>\n",
       "      <td>RIO GRANDE FENCE COMPANY</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>758186446</td>\n",
       "      <td>Finance and Insurance</td>\n",
       "      <td>WI</td>\n",
       "      <td>ALLIANCE BANK</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>717493456</td>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>DE</td>\n",
       "      <td>ATLANTIC VETERINARY CENTER</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       bq_id  ... bq_public_indicator\n",
       "0  777704001  ...                   0\n",
       "1  699258395  ...                   0\n",
       "2  298415539  ...                   0\n",
       "3  312414242  ...                   0\n",
       "4  289867643  ...                   0\n",
       "5  204048886  ...                   0\n",
       "6  457397418  ...                   0\n",
       "7  777141037  ...                   0\n",
       "8  758186446  ...                   0\n",
       "9  717493456  ...                   0\n",
       "\n",
       "[10 rows x 5 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "companies_df = pd.concat([companies_df1, companies_df2, companies_df3], ignore_index=True)\n",
    "companies_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
    },
    "id": "mBRTjPlgozjs",
    "outputId": "81ebd66a-566d-4829-8235-ed58e464cc80"
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_public_indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13840</th>\n",
       "      <td>131980070</td>\n",
       "      <td>Finance and Insurance</td>\n",
       "      <td>KY</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>17731</th>\n",
       "      <td>983586555</td>\n",
       "      <td>Health Care and Social Assistance</td>\n",
       "      <td>LA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26582</th>\n",
       "      <td>795029135</td>\n",
       "      <td>Arts, Entertainment, and Recreation</td>\n",
       "      <td>PA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32977</th>\n",
       "      <td>351856405</td>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>MA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35636</th>\n",
       "      <td>913785945</td>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749327</th>\n",
       "      <td>786180452</td>\n",
       "      <td>Finance and Insurance</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751249</th>\n",
       "      <td>102840051</td>\n",
       "      <td>Professional, Scientific, and Technical Services</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751664</th>\n",
       "      <td>217055129</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>FL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756256</th>\n",
       "      <td>757247657</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>NC</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758252</th>\n",
       "      <td>286910571</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3490 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            bq_id  ... bq_public_indicator\n",
       "13840   131980070  ...                   1\n",
       "17731   983586555  ...                   1\n",
       "26582   795029135  ...                   1\n",
       "32977   351856405  ...                   1\n",
       "35636   913785945  ...                   1\n",
       "...           ...  ...                 ...\n",
       "749327  786180452  ...                   1\n",
       "751249  102840051  ...                   1\n",
       "751664  217055129  ...                   1\n",
       "756256  757247657  ...                   1\n",
       "758252  286910571  ...                   1\n",
       "\n",
       "[3490 rows x 4 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "public_companies = companies_df[companies_df.bq_public_indicator == 1]\n",
    "public_companies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 439
    },
    "id": "1rSdx_PRohfh",
    "outputId": "9feb64dc-92d6-456e-e754-4b3b29af87e7"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
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       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_public_indicator</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>412416919</td>\n",
       "      <td>2018</td>\n",
       "      <td>4.903160e+08</td>\n",
       "      <td>1.432950e+08</td>\n",
       "      <td>3.370800e+08</td>\n",
       "      <td>56580000.0</td>\n",
       "      <td>1.532360e+08</td>\n",
       "      <td>1.693671e+09</td>\n",
       "      <td>5.839300e+07</td>\n",
       "      <td>9.484300e+07</td>\n",
       "      <td>38263000.0</td>\n",
       "      <td>0.312525</td>\n",
       "      <td>0.292250</td>\n",
       "      <td>0.289499</td>\n",
       "      <td>0.115395</td>\n",
       "      <td>0.033407</td>\n",
       "      <td>0.193432</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>DE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>412416919</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.592440e+08</td>\n",
       "      <td>1.150010e+08</td>\n",
       "      <td>3.394070e+08</td>\n",
       "      <td>41140000.0</td>\n",
       "      <td>1.198370e+08</td>\n",
       "      <td>1.067421e+09</td>\n",
       "      <td>4.207900e+07</td>\n",
       "      <td>7.775800e+07</td>\n",
       "      <td>36618000.0</td>\n",
       "      <td>0.260944</td>\n",
       "      <td>0.250414</td>\n",
       "      <td>0.430237</td>\n",
       "      <td>0.089582</td>\n",
       "      <td>0.038541</td>\n",
       "      <td>0.169317</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>DE</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>412416919</td>\n",
       "      <td>2016</td>\n",
       "      <td>4.988600e+08</td>\n",
       "      <td>1.231480e+08</td>\n",
       "      <td>3.661180e+08</td>\n",
       "      <td>44675000.0</td>\n",
       "      <td>1.327420e+08</td>\n",
       "      <td>1.229219e+09</td>\n",
       "      <td>4.675900e+07</td>\n",
       "      <td>8.598300e+07</td>\n",
       "      <td>41308000.0</td>\n",
       "      <td>0.266091</td>\n",
       "      <td>0.246859</td>\n",
       "      <td>0.405835</td>\n",
       "      <td>0.089554</td>\n",
       "      <td>0.036344</td>\n",
       "      <td>0.172359</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>DE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>412416919</td>\n",
       "      <td>2020</td>\n",
       "      <td>4.831540e+08</td>\n",
       "      <td>1.786940e+08</td>\n",
       "      <td>3.007940e+08</td>\n",
       "      <td>71711000.0</td>\n",
       "      <td>1.823600e+08</td>\n",
       "      <td>1.888088e+09</td>\n",
       "      <td>7.522100e+07</td>\n",
       "      <td>1.071390e+08</td>\n",
       "      <td>35428000.0</td>\n",
       "      <td>0.377437</td>\n",
       "      <td>0.369849</td>\n",
       "      <td>0.255896</td>\n",
       "      <td>0.148423</td>\n",
       "      <td>0.037981</td>\n",
       "      <td>0.221749</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>DE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412416919</td>\n",
       "      <td>2017</td>\n",
       "      <td>4.496460e+08</td>\n",
       "      <td>1.300450e+08</td>\n",
       "      <td>3.068390e+08</td>\n",
       "      <td>58124000.0</td>\n",
       "      <td>1.428070e+08</td>\n",
       "      <td>1.414934e+09</td>\n",
       "      <td>5.307700e+07</td>\n",
       "      <td>8.973000e+07</td>\n",
       "      <td>31606000.0</td>\n",
       "      <td>0.317599</td>\n",
       "      <td>0.289216</td>\n",
       "      <td>0.317786</td>\n",
       "      <td>0.129266</td>\n",
       "      <td>0.041079</td>\n",
       "      <td>0.199557</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>DE</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18682</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2019</td>\n",
       "      <td>8.005000e+09</td>\n",
       "      <td>8.400000e+08</td>\n",
       "      <td>5.462000e+09</td>\n",
       "      <td>491000000.0</td>\n",
       "      <td>2.543000e+09</td>\n",
       "      <td>6.589000e+09</td>\n",
       "      <td>1.882000e+09</td>\n",
       "      <td>6.610000e+08</td>\n",
       "      <td>170000000.0</td>\n",
       "      <td>0.317676</td>\n",
       "      <td>0.104934</td>\n",
       "      <td>1.214904</td>\n",
       "      <td>0.061337</td>\n",
       "      <td>0.074518</td>\n",
       "      <td>0.082573</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18683</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.939000e+09</td>\n",
       "      <td>8.820000e+08</td>\n",
       "      <td>5.411000e+09</td>\n",
       "      <td>541000000.0</td>\n",
       "      <td>2.528000e+09</td>\n",
       "      <td>3.820000e+09</td>\n",
       "      <td>1.824000e+09</td>\n",
       "      <td>7.040000e+08</td>\n",
       "      <td>163000000.0</td>\n",
       "      <td>0.318428</td>\n",
       "      <td>0.111097</td>\n",
       "      <td>2.078272</td>\n",
       "      <td>0.068145</td>\n",
       "      <td>0.141623</td>\n",
       "      <td>0.088676</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18684</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2015</td>\n",
       "      <td>7.412000e+09</td>\n",
       "      <td>9.890000e+08</td>\n",
       "      <td>4.907000e+09</td>\n",
       "      <td>541000000.0</td>\n",
       "      <td>2.505000e+09</td>\n",
       "      <td>3.775000e+09</td>\n",
       "      <td>1.668000e+09</td>\n",
       "      <td>8.370000e+08</td>\n",
       "      <td>296000000.0</td>\n",
       "      <td>0.337965</td>\n",
       "      <td>0.133432</td>\n",
       "      <td>1.963444</td>\n",
       "      <td>0.072990</td>\n",
       "      <td>0.143311</td>\n",
       "      <td>0.112925</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18685</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2016</td>\n",
       "      <td>7.766000e+09</td>\n",
       "      <td>1.164000e+09</td>\n",
       "      <td>5.130000e+09</td>\n",
       "      <td>664000000.0</td>\n",
       "      <td>2.636000e+09</td>\n",
       "      <td>3.840000e+09</td>\n",
       "      <td>1.636000e+09</td>\n",
       "      <td>1.000000e+09</td>\n",
       "      <td>336000000.0</td>\n",
       "      <td>0.339428</td>\n",
       "      <td>0.149884</td>\n",
       "      <td>2.022396</td>\n",
       "      <td>0.085501</td>\n",
       "      <td>0.172917</td>\n",
       "      <td>0.128766</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18686</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2020</td>\n",
       "      <td>7.580000e+09</td>\n",
       "      <td>6.960000e+08</td>\n",
       "      <td>5.421000e+09</td>\n",
       "      <td>334000000.0</td>\n",
       "      <td>2.159000e+09</td>\n",
       "      <td>7.018000e+09</td>\n",
       "      <td>1.632000e+09</td>\n",
       "      <td>5.270000e+08</td>\n",
       "      <td>193000000.0</td>\n",
       "      <td>0.284828</td>\n",
       "      <td>0.091821</td>\n",
       "      <td>1.080080</td>\n",
       "      <td>0.044063</td>\n",
       "      <td>0.047592</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18687 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           bq_id  bq_year  ...  bq_company_address1_state  bq_public_indicator\n",
       "0      412416919     2018  ...                         DE                    1\n",
       "1      412416919     2015  ...                         DE                    1\n",
       "2      412416919     2016  ...                         DE                    1\n",
       "3      412416919     2020  ...                         DE                    1\n",
       "4      412416919     2017  ...                         DE                    1\n",
       "...          ...      ...  ...                        ...                  ...\n",
       "18682  950199378     2019  ...                         NY                    1\n",
       "18683  950199378     2018  ...                         NY                    1\n",
       "18684  950199378     2015  ...                         NY                    1\n",
       "18685  950199378     2016  ...                         NY                    1\n",
       "18686  950199378     2020  ...                         NY                    1\n",
       "\n",
       "[18687 rows x 20 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = company_variables_ts_df.merge(public_companies, how='inner', on='bq_id')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
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    },
    "id": "Q5s_XuLhohpQ",
    "outputId": "9c45c836-955c-4574-9112-611b93315a53"
   },
   "outputs": [
    {
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       "      <td>0.169317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.988600e+08</td>\n",
       "      <td>1.231480e+08</td>\n",
       "      <td>3.661180e+08</td>\n",
       "      <td>44675000.0</td>\n",
       "      <td>1.327420e+08</td>\n",
       "      <td>1.229219e+09</td>\n",
       "      <td>4.675900e+07</td>\n",
       "      <td>8.598300e+07</td>\n",
       "      <td>41308000.0</td>\n",
       "      <td>0.266091</td>\n",
       "      <td>0.246859</td>\n",
       "      <td>0.405835</td>\n",
       "      <td>0.089554</td>\n",
       "      <td>0.036344</td>\n",
       "      <td>0.172359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.831540e+08</td>\n",
       "      <td>1.786940e+08</td>\n",
       "      <td>3.007940e+08</td>\n",
       "      <td>71711000.0</td>\n",
       "      <td>1.823600e+08</td>\n",
       "      <td>1.888088e+09</td>\n",
       "      <td>7.522100e+07</td>\n",
       "      <td>1.071390e+08</td>\n",
       "      <td>35428000.0</td>\n",
       "      <td>0.377437</td>\n",
       "      <td>0.369849</td>\n",
       "      <td>0.255896</td>\n",
       "      <td>0.148423</td>\n",
       "      <td>0.037981</td>\n",
       "      <td>0.221749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.496460e+08</td>\n",
       "      <td>1.300450e+08</td>\n",
       "      <td>3.068390e+08</td>\n",
       "      <td>58124000.0</td>\n",
       "      <td>1.428070e+08</td>\n",
       "      <td>1.414934e+09</td>\n",
       "      <td>5.307700e+07</td>\n",
       "      <td>8.973000e+07</td>\n",
       "      <td>31606000.0</td>\n",
       "      <td>0.317599</td>\n",
       "      <td>0.289216</td>\n",
       "      <td>0.317786</td>\n",
       "      <td>0.129266</td>\n",
       "      <td>0.041079</td>\n",
       "      <td>0.199557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18682</th>\n",
       "      <td>8.005000e+09</td>\n",
       "      <td>8.400000e+08</td>\n",
       "      <td>5.462000e+09</td>\n",
       "      <td>491000000.0</td>\n",
       "      <td>2.543000e+09</td>\n",
       "      <td>6.589000e+09</td>\n",
       "      <td>1.882000e+09</td>\n",
       "      <td>6.610000e+08</td>\n",
       "      <td>170000000.0</td>\n",
       "      <td>0.317676</td>\n",
       "      <td>0.104934</td>\n",
       "      <td>1.214904</td>\n",
       "      <td>0.061337</td>\n",
       "      <td>0.074518</td>\n",
       "      <td>0.082573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18683</th>\n",
       "      <td>7.939000e+09</td>\n",
       "      <td>8.820000e+08</td>\n",
       "      <td>5.411000e+09</td>\n",
       "      <td>541000000.0</td>\n",
       "      <td>2.528000e+09</td>\n",
       "      <td>3.820000e+09</td>\n",
       "      <td>1.824000e+09</td>\n",
       "      <td>7.040000e+08</td>\n",
       "      <td>163000000.0</td>\n",
       "      <td>0.318428</td>\n",
       "      <td>0.111097</td>\n",
       "      <td>2.078272</td>\n",
       "      <td>0.068145</td>\n",
       "      <td>0.141623</td>\n",
       "      <td>0.088676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18684</th>\n",
       "      <td>7.412000e+09</td>\n",
       "      <td>9.890000e+08</td>\n",
       "      <td>4.907000e+09</td>\n",
       "      <td>541000000.0</td>\n",
       "      <td>2.505000e+09</td>\n",
       "      <td>3.775000e+09</td>\n",
       "      <td>1.668000e+09</td>\n",
       "      <td>8.370000e+08</td>\n",
       "      <td>296000000.0</td>\n",
       "      <td>0.337965</td>\n",
       "      <td>0.133432</td>\n",
       "      <td>1.963444</td>\n",
       "      <td>0.072990</td>\n",
       "      <td>0.143311</td>\n",
       "      <td>0.112925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18685</th>\n",
       "      <td>7.766000e+09</td>\n",
       "      <td>1.164000e+09</td>\n",
       "      <td>5.130000e+09</td>\n",
       "      <td>664000000.0</td>\n",
       "      <td>2.636000e+09</td>\n",
       "      <td>3.840000e+09</td>\n",
       "      <td>1.636000e+09</td>\n",
       "      <td>1.000000e+09</td>\n",
       "      <td>336000000.0</td>\n",
       "      <td>0.339428</td>\n",
       "      <td>0.149884</td>\n",
       "      <td>2.022396</td>\n",
       "      <td>0.085501</td>\n",
       "      <td>0.172917</td>\n",
       "      <td>0.128766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18686</th>\n",
       "      <td>7.580000e+09</td>\n",
       "      <td>6.960000e+08</td>\n",
       "      <td>5.421000e+09</td>\n",
       "      <td>334000000.0</td>\n",
       "      <td>2.159000e+09</td>\n",
       "      <td>7.018000e+09</td>\n",
       "      <td>1.632000e+09</td>\n",
       "      <td>5.270000e+08</td>\n",
       "      <td>193000000.0</td>\n",
       "      <td>0.284828</td>\n",
       "      <td>0.091821</td>\n",
       "      <td>1.080080</td>\n",
       "      <td>0.044063</td>\n",
       "      <td>0.047592</td>\n",
       "      <td>0.069525</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18687 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         bq_revenue     bq_ebitda  ...  bq_return_on_assets  bq_return_on_sales\n",
       "0      4.903160e+08  1.432950e+08  ...             0.033407            0.193432\n",
       "1      4.592440e+08  1.150010e+08  ...             0.038541            0.169317\n",
       "2      4.988600e+08  1.231480e+08  ...             0.036344            0.172359\n",
       "3      4.831540e+08  1.786940e+08  ...             0.037981            0.221749\n",
       "4      4.496460e+08  1.300450e+08  ...             0.041079            0.199557\n",
       "...             ...           ...  ...                  ...                 ...\n",
       "18682  8.005000e+09  8.400000e+08  ...             0.074518            0.082573\n",
       "18683  7.939000e+09  8.820000e+08  ...             0.141623            0.088676\n",
       "18684  7.412000e+09  9.890000e+08  ...             0.143311            0.112925\n",
       "18685  7.766000e+09  1.164000e+09  ...             0.172917            0.128766\n",
       "18686  7.580000e+09  6.960000e+08  ...             0.047592            0.069525\n",
       "\n",
       "[18687 rows x 15 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "public_dataset = df.drop(['bq_id', 'bq_year', 'bq_sector_name', 'bq_company_address1_state','bq_public_indicator'], axis=1)\n",
    "public_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "e7E-Vb8nohwT"
   },
   "outputs": [],
   "source": [
    "public_corr = public_dataset.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "w0q5IwhZp_8C",
    "outputId": "2a3a5a31-c861-434f-8e12-2cec6e21cb49"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0, 'bq_revenue'),\n",
       " Text(1.5, 0, 'bq_ebitda'),\n",
       " Text(2.5, 0, 'bq_cor'),\n",
       " Text(3.5, 0, 'bq_net_income'),\n",
       " Text(4.5, 0, 'bq_gross_profit'),\n",
       " Text(5.5, 0, 'bq_total_assets'),\n",
       " Text(6.5, 0, 'bq_operating_expenses'),\n",
       " Text(7.5, 0, 'bq_operating_income'),\n",
       " Text(8.5, 0, 'bq_tax_and_interest'),\n",
       " Text(9.5, 0, 'bq_gross_profit_margin'),\n",
       " Text(10.5, 0, 'bq_ebitda_margin'),\n",
       " Text(11.5, 0, 'bq_asset_turnover'),\n",
       " Text(12.5, 0, 'bq_net_profit_margin'),\n",
       " Text(13.5, 0, 'bq_return_on_assets'),\n",
       " Text(14.5, 0, 'bq_return_on_sales')]"
      ]
     },
     "execution_count": 29,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x900 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colormap = plt.cm.coolwarm\n",
    "# mask = np.triu(np.ones_like(public_corr.round(3), dtype=np.bool))\n",
    "plt.figure(figsize=(6*2.5,5*2.5));\n",
    "plt.title('Pearson Correlations Between Financial Features', y=1, size=24);\n",
    "g = sns.heatmap(public_corr.round(3), linewidths=0.1, vmin = -1.0, vmax=1.0, square=True, cmap=colormap, center=0, linecolor='white', annot=True);\n",
    "g.set_xticklabels(g.get_xticklabels(), rotation=45, horizontalalignment='right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "385vnukdmGH0"
   },
   "source": [
    "## Ebitda Differs In Sectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 439
    },
    "id": "BKCCBHGeqACG",
    "outputId": "819ba1dc-56c2-4233-b29d-786d39be2203"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <th>bq_total_assets</th>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_public_indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>827530042</td>\n",
       "      <td>2018</td>\n",
       "      <td>3.811000e+09</td>\n",
       "      <td>1.773000e+09</td>\n",
       "      <td>1.634000e+09</td>\n",
       "      <td>957000000.0</td>\n",
       "      <td>2.177000e+09</td>\n",
       "      <td>1.219747e+10</td>\n",
       "      <td>522000000.0</td>\n",
       "      <td>1.655000e+09</td>\n",
       "      <td>6.980000e+08</td>\n",
       "      <td>0.571241</td>\n",
       "      <td>0.465232</td>\n",
       "      <td>0.312442</td>\n",
       "      <td>0.251115</td>\n",
       "      <td>0.078459</td>\n",
       "      <td>0.434269</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>OH</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>827530042</td>\n",
       "      <td>2020</td>\n",
       "      <td>5.103000e+09</td>\n",
       "      <td>2.098000e+09</td>\n",
       "      <td>2.456000e+09</td>\n",
       "      <td>699000000.0</td>\n",
       "      <td>2.647000e+09</td>\n",
       "      <td>1.839500e+10</td>\n",
       "      <td>896000000.0</td>\n",
       "      <td>1.751000e+09</td>\n",
       "      <td>1.052000e+09</td>\n",
       "      <td>0.518714</td>\n",
       "      <td>0.411131</td>\n",
       "      <td>0.277412</td>\n",
       "      <td>0.136978</td>\n",
       "      <td>0.037999</td>\n",
       "      <td>0.343131</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>OH</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>827530042</td>\n",
       "      <td>2016</td>\n",
       "      <td>3.171411e+09</td>\n",
       "      <td>1.370636e+09</td>\n",
       "      <td>1.443348e+09</td>\n",
       "      <td>583414000.0</td>\n",
       "      <td>1.728063e+09</td>\n",
       "      <td>1.072628e+10</td>\n",
       "      <td>460303000.0</td>\n",
       "      <td>1.267760e+09</td>\n",
       "      <td>6.843460e+08</td>\n",
       "      <td>0.544888</td>\n",
       "      <td>0.432185</td>\n",
       "      <td>0.295667</td>\n",
       "      <td>0.183960</td>\n",
       "      <td>0.054391</td>\n",
       "      <td>0.399746</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>OH</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>827530042</td>\n",
       "      <td>2015</td>\n",
       "      <td>2.707115e+09</td>\n",
       "      <td>1.145907e+09</td>\n",
       "      <td>1.257270e+09</td>\n",
       "      <td>443847000.0</td>\n",
       "      <td>1.449845e+09</td>\n",
       "      <td>8.303935e+09</td>\n",
       "      <td>375843000.0</td>\n",
       "      <td>1.074002e+09</td>\n",
       "      <td>6.301550e+08</td>\n",
       "      <td>0.535568</td>\n",
       "      <td>0.423295</td>\n",
       "      <td>0.326004</td>\n",
       "      <td>0.163956</td>\n",
       "      <td>0.053450</td>\n",
       "      <td>0.396733</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>OH</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>827530042</td>\n",
       "      <td>2017</td>\n",
       "      <td>3.504286e+09</td>\n",
       "      <td>1.549390e+09</td>\n",
       "      <td>1.519659e+09</td>\n",
       "      <td>596887000.0</td>\n",
       "      <td>1.984627e+09</td>\n",
       "      <td>9.975661e+09</td>\n",
       "      <td>501781000.0</td>\n",
       "      <td>1.482846e+09</td>\n",
       "      <td>8.859590e+08</td>\n",
       "      <td>0.566343</td>\n",
       "      <td>0.442141</td>\n",
       "      <td>0.351284</td>\n",
       "      <td>0.170331</td>\n",
       "      <td>0.059834</td>\n",
       "      <td>0.423152</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>OH</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18671</th>\n",
       "      <td>318270525</td>\n",
       "      <td>2019</td>\n",
       "      <td>9.366200e+07</td>\n",
       "      <td>4.805000e+06</td>\n",
       "      <td>7.151300e+07</td>\n",
       "      <td>453000.0</td>\n",
       "      <td>2.214900e+07</td>\n",
       "      <td>5.698700e+07</td>\n",
       "      <td>24082000.0</td>\n",
       "      <td>-1.933000e+06</td>\n",
       "      <td>-2.386000e+06</td>\n",
       "      <td>0.236478</td>\n",
       "      <td>0.051301</td>\n",
       "      <td>1.643568</td>\n",
       "      <td>0.004837</td>\n",
       "      <td>0.007949</td>\n",
       "      <td>-0.020638</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>IL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18672</th>\n",
       "      <td>318270525</td>\n",
       "      <td>2018</td>\n",
       "      <td>1.033500e+08</td>\n",
       "      <td>4.370000e+05</td>\n",
       "      <td>7.749200e+07</td>\n",
       "      <td>-3086000.0</td>\n",
       "      <td>2.585800e+07</td>\n",
       "      <td>5.680700e+07</td>\n",
       "      <td>28968000.0</td>\n",
       "      <td>-3.110000e+06</td>\n",
       "      <td>-2.400000e+04</td>\n",
       "      <td>0.250198</td>\n",
       "      <td>0.004228</td>\n",
       "      <td>1.819318</td>\n",
       "      <td>-0.029860</td>\n",
       "      <td>-0.054324</td>\n",
       "      <td>-0.030092</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>IL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18673</th>\n",
       "      <td>318270525</td>\n",
       "      <td>2020</td>\n",
       "      <td>9.960600e+07</td>\n",
       "      <td>9.589000e+06</td>\n",
       "      <td>7.399400e+07</td>\n",
       "      <td>4006000.0</td>\n",
       "      <td>2.561200e+07</td>\n",
       "      <td>5.989600e+07</td>\n",
       "      <td>22530000.0</td>\n",
       "      <td>3.082000e+06</td>\n",
       "      <td>-9.240000e+05</td>\n",
       "      <td>0.257133</td>\n",
       "      <td>0.096269</td>\n",
       "      <td>1.662983</td>\n",
       "      <td>0.040218</td>\n",
       "      <td>0.066883</td>\n",
       "      <td>0.030942</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>IL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18674</th>\n",
       "      <td>318270525</td>\n",
       "      <td>2016</td>\n",
       "      <td>1.238790e+08</td>\n",
       "      <td>8.877000e+06</td>\n",
       "      <td>8.884700e+07</td>\n",
       "      <td>3479000.0</td>\n",
       "      <td>3.503200e+07</td>\n",
       "      <td>6.521400e+07</td>\n",
       "      <td>28947000.0</td>\n",
       "      <td>6.085000e+06</td>\n",
       "      <td>2.606000e+06</td>\n",
       "      <td>0.282792</td>\n",
       "      <td>0.071659</td>\n",
       "      <td>1.899577</td>\n",
       "      <td>0.028084</td>\n",
       "      <td>0.053347</td>\n",
       "      <td>0.049121</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>IL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18675</th>\n",
       "      <td>318270525</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.185870e+08</td>\n",
       "      <td>7.357000e+06</td>\n",
       "      <td>8.870500e+07</td>\n",
       "      <td>1972000.0</td>\n",
       "      <td>2.988200e+07</td>\n",
       "      <td>6.491800e+07</td>\n",
       "      <td>25479000.0</td>\n",
       "      <td>4.403000e+06</td>\n",
       "      <td>2.431000e+06</td>\n",
       "      <td>0.251984</td>\n",
       "      <td>0.062039</td>\n",
       "      <td>1.826720</td>\n",
       "      <td>0.016629</td>\n",
       "      <td>0.030377</td>\n",
       "      <td>0.037129</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>IL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5690 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           bq_id  bq_year  ...  bq_company_address1_state  bq_public_indicator\n",
       "67     827530042     2018  ...                         OH                    1\n",
       "68     827530042     2020  ...                         OH                    1\n",
       "69     827530042     2016  ...                         OH                    1\n",
       "70     827530042     2015  ...                         OH                    1\n",
       "71     827530042     2017  ...                         OH                    1\n",
       "...          ...      ...  ...                        ...                  ...\n",
       "18671  318270525     2019  ...                         IL                    1\n",
       "18672  318270525     2018  ...                         IL                    1\n",
       "18673  318270525     2020  ...                         IL                    1\n",
       "18674  318270525     2016  ...                         IL                    1\n",
       "18675  318270525     2015  ...                         IL                    1\n",
       "\n",
       "[5690 rows x 20 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Manufacturing = df[(df.bq_sector_name == \"Manufacturing\")]\n",
    "Manufacturing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 439
    },
    "id": "b7iOXUoFtAlU",
    "outputId": "78a0a550-1628-4aff-e585-b5bb935b40af"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <th>bq_total_assets</th>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_public_indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>921955386</td>\n",
       "      <td>2018</td>\n",
       "      <td>1.521710e+08</td>\n",
       "      <td>1.151440e+08</td>\n",
       "      <td>3.732400e+07</td>\n",
       "      <td>81970000.0</td>\n",
       "      <td>1.148470e+08</td>\n",
       "      <td>1.835552e+09</td>\n",
       "      <td>5.652000e+06</td>\n",
       "      <td>1.091950e+08</td>\n",
       "      <td>27225000.0</td>\n",
       "      <td>0.754723</td>\n",
       "      <td>0.756675</td>\n",
       "      <td>0.082902</td>\n",
       "      <td>0.538670</td>\n",
       "      <td>0.044657</td>\n",
       "      <td>0.717581</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>921955386</td>\n",
       "      <td>2016</td>\n",
       "      <td>1.278710e+08</td>\n",
       "      <td>9.726100e+07</td>\n",
       "      <td>2.928600e+07</td>\n",
       "      <td>69204000.0</td>\n",
       "      <td>9.858500e+07</td>\n",
       "      <td>1.756509e+09</td>\n",
       "      <td>5.548000e+06</td>\n",
       "      <td>9.303700e+07</td>\n",
       "      <td>23833000.0</td>\n",
       "      <td>0.770972</td>\n",
       "      <td>0.760618</td>\n",
       "      <td>0.072798</td>\n",
       "      <td>0.541202</td>\n",
       "      <td>0.039399</td>\n",
       "      <td>0.727585</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>921955386</td>\n",
       "      <td>2020</td>\n",
       "      <td>2.989530e+08</td>\n",
       "      <td>1.297300e+08</td>\n",
       "      <td>7.307400e+07</td>\n",
       "      <td>54872000.0</td>\n",
       "      <td>2.258790e+08</td>\n",
       "      <td>4.444284e+09</td>\n",
       "      <td>1.196200e+07</td>\n",
       "      <td>2.139170e+08</td>\n",
       "      <td>159045000.0</td>\n",
       "      <td>0.755567</td>\n",
       "      <td>0.433948</td>\n",
       "      <td>0.067267</td>\n",
       "      <td>0.183547</td>\n",
       "      <td>0.012347</td>\n",
       "      <td>0.715554</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>921955386</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.199680e+08</td>\n",
       "      <td>9.530100e+07</td>\n",
       "      <td>3.055600e+07</td>\n",
       "      <td>70791000.0</td>\n",
       "      <td>8.941200e+07</td>\n",
       "      <td>1.633426e+09</td>\n",
       "      <td>5.905000e+06</td>\n",
       "      <td>8.350700e+07</td>\n",
       "      <td>12716000.0</td>\n",
       "      <td>0.745299</td>\n",
       "      <td>0.794387</td>\n",
       "      <td>0.073446</td>\n",
       "      <td>0.590082</td>\n",
       "      <td>0.043339</td>\n",
       "      <td>0.696077</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>921955386</td>\n",
       "      <td>2017</td>\n",
       "      <td>1.377640e+08</td>\n",
       "      <td>1.138390e+08</td>\n",
       "      <td>3.137500e+07</td>\n",
       "      <td>82288000.0</td>\n",
       "      <td>1.063890e+08</td>\n",
       "      <td>1.754176e+09</td>\n",
       "      <td>5.292000e+06</td>\n",
       "      <td>1.010970e+08</td>\n",
       "      <td>18809000.0</td>\n",
       "      <td>0.772255</td>\n",
       "      <td>0.826333</td>\n",
       "      <td>0.078535</td>\n",
       "      <td>0.597311</td>\n",
       "      <td>0.046910</td>\n",
       "      <td>0.733842</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18682</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2019</td>\n",
       "      <td>8.005000e+09</td>\n",
       "      <td>8.400000e+08</td>\n",
       "      <td>5.462000e+09</td>\n",
       "      <td>491000000.0</td>\n",
       "      <td>2.543000e+09</td>\n",
       "      <td>6.589000e+09</td>\n",
       "      <td>1.882000e+09</td>\n",
       "      <td>6.610000e+08</td>\n",
       "      <td>170000000.0</td>\n",
       "      <td>0.317676</td>\n",
       "      <td>0.104934</td>\n",
       "      <td>1.214904</td>\n",
       "      <td>0.061337</td>\n",
       "      <td>0.074518</td>\n",
       "      <td>0.082573</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18683</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.939000e+09</td>\n",
       "      <td>8.820000e+08</td>\n",
       "      <td>5.411000e+09</td>\n",
       "      <td>541000000.0</td>\n",
       "      <td>2.528000e+09</td>\n",
       "      <td>3.820000e+09</td>\n",
       "      <td>1.824000e+09</td>\n",
       "      <td>7.040000e+08</td>\n",
       "      <td>163000000.0</td>\n",
       "      <td>0.318428</td>\n",
       "      <td>0.111097</td>\n",
       "      <td>2.078272</td>\n",
       "      <td>0.068145</td>\n",
       "      <td>0.141623</td>\n",
       "      <td>0.088676</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18684</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2015</td>\n",
       "      <td>7.412000e+09</td>\n",
       "      <td>9.890000e+08</td>\n",
       "      <td>4.907000e+09</td>\n",
       "      <td>541000000.0</td>\n",
       "      <td>2.505000e+09</td>\n",
       "      <td>3.775000e+09</td>\n",
       "      <td>1.668000e+09</td>\n",
       "      <td>8.370000e+08</td>\n",
       "      <td>296000000.0</td>\n",
       "      <td>0.337965</td>\n",
       "      <td>0.133432</td>\n",
       "      <td>1.963444</td>\n",
       "      <td>0.072990</td>\n",
       "      <td>0.143311</td>\n",
       "      <td>0.112925</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18685</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2016</td>\n",
       "      <td>7.766000e+09</td>\n",
       "      <td>1.164000e+09</td>\n",
       "      <td>5.130000e+09</td>\n",
       "      <td>664000000.0</td>\n",
       "      <td>2.636000e+09</td>\n",
       "      <td>3.840000e+09</td>\n",
       "      <td>1.636000e+09</td>\n",
       "      <td>1.000000e+09</td>\n",
       "      <td>336000000.0</td>\n",
       "      <td>0.339428</td>\n",
       "      <td>0.149884</td>\n",
       "      <td>2.022396</td>\n",
       "      <td>0.085501</td>\n",
       "      <td>0.172917</td>\n",
       "      <td>0.128766</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18686</th>\n",
       "      <td>950199378</td>\n",
       "      <td>2020</td>\n",
       "      <td>7.580000e+09</td>\n",
       "      <td>6.960000e+08</td>\n",
       "      <td>5.421000e+09</td>\n",
       "      <td>334000000.0</td>\n",
       "      <td>2.159000e+09</td>\n",
       "      <td>7.018000e+09</td>\n",
       "      <td>1.632000e+09</td>\n",
       "      <td>5.270000e+08</td>\n",
       "      <td>193000000.0</td>\n",
       "      <td>0.284828</td>\n",
       "      <td>0.091821</td>\n",
       "      <td>1.080080</td>\n",
       "      <td>0.044063</td>\n",
       "      <td>0.047592</td>\n",
       "      <td>0.069525</td>\n",
       "      <td>Retail Trade</td>\n",
       "      <td>NY</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>789 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           bq_id  bq_year  ...  bq_company_address1_state  bq_public_indicator\n",
       "103    921955386     2018  ...                         NY                    1\n",
       "104    921955386     2016  ...                         NY                    1\n",
       "105    921955386     2020  ...                         NY                    1\n",
       "106    921955386     2015  ...                         NY                    1\n",
       "107    921955386     2017  ...                         NY                    1\n",
       "...          ...      ...  ...                        ...                  ...\n",
       "18682  950199378     2019  ...                         NY                    1\n",
       "18683  950199378     2018  ...                         NY                    1\n",
       "18684  950199378     2015  ...                         NY                    1\n",
       "18685  950199378     2016  ...                         NY                    1\n",
       "18686  950199378     2020  ...                         NY                    1\n",
       "\n",
       "[789 rows x 20 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RetailTrade = df[(df.bq_sector_name == \"Retail Trade\")]\n",
    "RetailTrade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 439
    },
    "id": "9nRJPydAtAyt",
    "outputId": "ae3a9f32-8933-42c7-e6d8-6a69bb057196"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
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       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_public_indicator</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>740196293</td>\n",
       "      <td>2020</td>\n",
       "      <td>2.172000e+09</td>\n",
       "      <td>-1.462000e+09</td>\n",
       "      <td>7.330000e+08</td>\n",
       "      <td>-2.163000e+09</td>\n",
       "      <td>1.439000e+09</td>\n",
       "      <td>4.856000e+09</td>\n",
       "      <td>3.094000e+09</td>\n",
       "      <td>-1.655000e+09</td>\n",
       "      <td>5.080000e+08</td>\n",
       "      <td>0.662523</td>\n",
       "      <td>-0.673112</td>\n",
       "      <td>0.447282</td>\n",
       "      <td>-0.995856</td>\n",
       "      <td>-0.445428</td>\n",
       "      <td>-0.761971</td>\n",
       "      <td>Mining</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>740196293</td>\n",
       "      <td>2018</td>\n",
       "      <td>3.064000e+09</td>\n",
       "      <td>1.209000e+09</td>\n",
       "      <td>9.120000e+08</td>\n",
       "      <td>3.280000e+08</td>\n",
       "      <td>2.152000e+09</td>\n",
       "      <td>7.158000e+09</td>\n",
       "      <td>1.383000e+09</td>\n",
       "      <td>7.690000e+08</td>\n",
       "      <td>4.410000e+08</td>\n",
       "      <td>0.702350</td>\n",
       "      <td>0.394582</td>\n",
       "      <td>0.428053</td>\n",
       "      <td>0.107050</td>\n",
       "      <td>0.045823</td>\n",
       "      <td>0.250979</td>\n",
       "      <td>Mining</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>740196293</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.634000e+09</td>\n",
       "      <td>8.270000e+08</td>\n",
       "      <td>8.950000e+08</td>\n",
       "      <td>-2.800000e+07</td>\n",
       "      <td>1.739000e+09</td>\n",
       "      <td>6.958000e+09</td>\n",
       "      <td>1.310000e+09</td>\n",
       "      <td>4.290000e+08</td>\n",
       "      <td>4.570000e+08</td>\n",
       "      <td>0.660213</td>\n",
       "      <td>0.313971</td>\n",
       "      <td>0.378557</td>\n",
       "      <td>-0.010630</td>\n",
       "      <td>-0.004024</td>\n",
       "      <td>0.162870</td>\n",
       "      <td>Mining</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>740196293</td>\n",
       "      <td>2017</td>\n",
       "      <td>2.006000e+09</td>\n",
       "      <td>6.210000e+08</td>\n",
       "      <td>8.760000e+08</td>\n",
       "      <td>-2.660000e+08</td>\n",
       "      <td>1.130000e+09</td>\n",
       "      <td>6.207000e+09</td>\n",
       "      <td>1.057000e+09</td>\n",
       "      <td>7.300000e+07</td>\n",
       "      <td>3.390000e+08</td>\n",
       "      <td>0.563310</td>\n",
       "      <td>0.309571</td>\n",
       "      <td>0.323184</td>\n",
       "      <td>-0.132602</td>\n",
       "      <td>-0.042855</td>\n",
       "      <td>0.036391</td>\n",
       "      <td>Mining</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>787069145</td>\n",
       "      <td>2019</td>\n",
       "      <td>8.372810e+08</td>\n",
       "      <td>-3.191000e+06</td>\n",
       "      <td>2.840190e+08</td>\n",
       "      <td>-3.424590e+08</td>\n",
       "      <td>5.532620e+08</td>\n",
       "      <td>2.264437e+09</td>\n",
       "      <td>9.618530e+08</td>\n",
       "      <td>-4.085910e+08</td>\n",
       "      <td>-6.613200e+07</td>\n",
       "      <td>0.660784</td>\n",
       "      <td>-0.003811</td>\n",
       "      <td>0.369752</td>\n",
       "      <td>-0.409013</td>\n",
       "      <td>-0.151234</td>\n",
       "      <td>-0.487997</td>\n",
       "      <td>Mining</td>\n",
       "      <td>OK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18629</th>\n",
       "      <td>141018875</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.843448e+10</td>\n",
       "      <td>2.499655e+10</td>\n",
       "      <td>6.393333e+10</td>\n",
       "      <td>4.742529e+09</td>\n",
       "      <td>2.450115e+10</td>\n",
       "      <td>1.360609e+11</td>\n",
       "      <td>1.302644e+10</td>\n",
       "      <td>1.147471e+10</td>\n",
       "      <td>6.732184e+09</td>\n",
       "      <td>0.277054</td>\n",
       "      <td>0.282656</td>\n",
       "      <td>0.649962</td>\n",
       "      <td>0.053628</td>\n",
       "      <td>0.034856</td>\n",
       "      <td>0.129754</td>\n",
       "      <td>Mining</td>\n",
       "      <td>TX</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18630</th>\n",
       "      <td>141018875</td>\n",
       "      <td>2016</td>\n",
       "      <td>5.967684e+10</td>\n",
       "      <td>1.502105e+10</td>\n",
       "      <td>4.555579e+10</td>\n",
       "      <td>-1.533684e+09</td>\n",
       "      <td>1.412105e+10</td>\n",
       "      <td>1.311000e+11</td>\n",
       "      <td>1.185053e+10</td>\n",
       "      <td>2.270526e+09</td>\n",
       "      <td>3.804211e+09</td>\n",
       "      <td>0.236625</td>\n",
       "      <td>0.251707</td>\n",
       "      <td>0.455201</td>\n",
       "      <td>-0.025700</td>\n",
       "      <td>-0.011699</td>\n",
       "      <td>0.038047</td>\n",
       "      <td>Mining</td>\n",
       "      <td>TX</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18631</th>\n",
       "      <td>141018875</td>\n",
       "      <td>2015</td>\n",
       "      <td>7.984582e+10</td>\n",
       "      <td>1.389034e+10</td>\n",
       "      <td>6.172421e+10</td>\n",
       "      <td>-1.017698e+10</td>\n",
       "      <td>1.812161e+10</td>\n",
       "      <td>1.509240e+11</td>\n",
       "      <td>2.146145e+10</td>\n",
       "      <td>-3.339848e+09</td>\n",
       "      <td>6.837134e+09</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.173964</td>\n",
       "      <td>0.529047</td>\n",
       "      <td>-0.127458</td>\n",
       "      <td>-0.067431</td>\n",
       "      <td>-0.041829</td>\n",
       "      <td>Mining</td>\n",
       "      <td>TX</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>141018875</td>\n",
       "      <td>2017</td>\n",
       "      <td>8.520648e+10</td>\n",
       "      <td>2.426170e+10</td>\n",
       "      <td>6.188235e+10</td>\n",
       "      <td>4.050420e+09</td>\n",
       "      <td>2.332413e+10</td>\n",
       "      <td>1.379688e+11</td>\n",
       "      <td>1.370588e+10</td>\n",
       "      <td>9.618247e+09</td>\n",
       "      <td>5.567827e+09</td>\n",
       "      <td>0.273737</td>\n",
       "      <td>0.284740</td>\n",
       "      <td>0.617578</td>\n",
       "      <td>0.047537</td>\n",
       "      <td>0.029358</td>\n",
       "      <td>0.112882</td>\n",
       "      <td>Mining</td>\n",
       "      <td>TX</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18633</th>\n",
       "      <td>141018875</td>\n",
       "      <td>2019</td>\n",
       "      <td>7.982135e+10</td>\n",
       "      <td>2.013933e+10</td>\n",
       "      <td>5.716180e+10</td>\n",
       "      <td>1.662921e+08</td>\n",
       "      <td>2.265955e+10</td>\n",
       "      <td>1.386966e+11</td>\n",
       "      <td>1.543258e+10</td>\n",
       "      <td>7.226966e+09</td>\n",
       "      <td>7.060674e+09</td>\n",
       "      <td>0.283878</td>\n",
       "      <td>0.252305</td>\n",
       "      <td>0.575510</td>\n",
       "      <td>0.002083</td>\n",
       "      <td>0.001199</td>\n",
       "      <td>0.090539</td>\n",
       "      <td>Mining</td>\n",
       "      <td>TX</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>575 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           bq_id  bq_year  ...  bq_company_address1_state  bq_public_indicator\n",
       "238    740196293     2020  ...                         CA                    1\n",
       "239    740196293     2018  ...                         CA                    1\n",
       "240    740196293     2019  ...                         CA                    1\n",
       "241    740196293     2017  ...                         CA                    1\n",
       "371    787069145     2019  ...                         OK                    1\n",
       "...          ...      ...  ...                        ...                  ...\n",
       "18629  141018875     2018  ...                         TX                    1\n",
       "18630  141018875     2016  ...                         TX                    1\n",
       "18631  141018875     2015  ...                         TX                    1\n",
       "18632  141018875     2017  ...                         TX                    1\n",
       "18633  141018875     2019  ...                         TX                    1\n",
       "\n",
       "[575 rows x 20 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mining = df[(df.bq_sector_name == \"Mining\")]\n",
    "Mining"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 439
    },
    "id": "qbFxtNzvtBKE",
    "outputId": "c8652aae-d51b-49c9-93dd-2f2c56e5ed36"
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <th>bq_total_assets</th>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <th>bq_sector_name</th>\n",
       "      <th>bq_company_address1_state</th>\n",
       "      <th>bq_public_indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>657</th>\n",
       "      <td>967622468</td>\n",
       "      <td>2016</td>\n",
       "      <td>7.199410e+08</td>\n",
       "      <td>164622000.0</td>\n",
       "      <td>1.395350e+08</td>\n",
       "      <td>77877000.0</td>\n",
       "      <td>580406000.0</td>\n",
       "      <td>1.128632e+09</td>\n",
       "      <td>419930000.0</td>\n",
       "      <td>160476000.0</td>\n",
       "      <td>82599000.0</td>\n",
       "      <td>0.806186</td>\n",
       "      <td>0.228660</td>\n",
       "      <td>0.637888</td>\n",
       "      <td>0.108171</td>\n",
       "      <td>0.069001</td>\n",
       "      <td>0.222902</td>\n",
       "      <td>Construction</td>\n",
       "      <td>FL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>967622468</td>\n",
       "      <td>2020</td>\n",
       "      <td>5.402760e+08</td>\n",
       "      <td>69405000.0</td>\n",
       "      <td>1.473850e+08</td>\n",
       "      <td>11826000.0</td>\n",
       "      <td>392891000.0</td>\n",
       "      <td>1.213804e+09</td>\n",
       "      <td>336517000.0</td>\n",
       "      <td>56374000.0</td>\n",
       "      <td>44548000.0</td>\n",
       "      <td>0.727204</td>\n",
       "      <td>0.128462</td>\n",
       "      <td>0.445110</td>\n",
       "      <td>0.021889</td>\n",
       "      <td>0.009743</td>\n",
       "      <td>0.104343</td>\n",
       "      <td>Construction</td>\n",
       "      <td>FL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>659</th>\n",
       "      <td>967622468</td>\n",
       "      <td>2015</td>\n",
       "      <td>6.176480e+08</td>\n",
       "      <td>163175000.0</td>\n",
       "      <td>8.382600e+07</td>\n",
       "      <td>70304000.0</td>\n",
       "      <td>533822000.0</td>\n",
       "      <td>1.083151e+09</td>\n",
       "      <td>373804000.0</td>\n",
       "      <td>160018000.0</td>\n",
       "      <td>89714000.0</td>\n",
       "      <td>0.864282</td>\n",
       "      <td>0.264188</td>\n",
       "      <td>0.570233</td>\n",
       "      <td>0.113825</td>\n",
       "      <td>0.064907</td>\n",
       "      <td>0.259076</td>\n",
       "      <td>Construction</td>\n",
       "      <td>FL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>660</th>\n",
       "      <td>967622468</td>\n",
       "      <td>2018</td>\n",
       "      <td>7.383200e+08</td>\n",
       "      <td>167816000.0</td>\n",
       "      <td>1.593150e+08</td>\n",
       "      <td>87962000.0</td>\n",
       "      <td>579005000.0</td>\n",
       "      <td>1.346467e+09</td>\n",
       "      <td>415403000.0</td>\n",
       "      <td>163602000.0</td>\n",
       "      <td>75640000.0</td>\n",
       "      <td>0.784220</td>\n",
       "      <td>0.227294</td>\n",
       "      <td>0.548339</td>\n",
       "      <td>0.119138</td>\n",
       "      <td>0.065328</td>\n",
       "      <td>0.221587</td>\n",
       "      <td>Construction</td>\n",
       "      <td>FL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>661</th>\n",
       "      <td>967622468</td>\n",
       "      <td>2019</td>\n",
       "      <td>7.402420e+08</td>\n",
       "      <td>105521000.0</td>\n",
       "      <td>1.726740e+08</td>\n",
       "      <td>34851000.0</td>\n",
       "      <td>567568000.0</td>\n",
       "      <td>1.360018e+09</td>\n",
       "      <td>469766000.0</td>\n",
       "      <td>97802000.0</td>\n",
       "      <td>62951000.0</td>\n",
       "      <td>0.766733</td>\n",
       "      <td>0.142549</td>\n",
       "      <td>0.544288</td>\n",
       "      <td>0.047081</td>\n",
       "      <td>0.025625</td>\n",
       "      <td>0.132122</td>\n",
       "      <td>Construction</td>\n",
       "      <td>FL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18051</th>\n",
       "      <td>806999469</td>\n",
       "      <td>2020</td>\n",
       "      <td>5.146972e+09</td>\n",
       "      <td>145933000.0</td>\n",
       "      <td>4.855927e+09</td>\n",
       "      <td>-13218000.0</td>\n",
       "      <td>291045000.0</td>\n",
       "      <td>5.042256e+09</td>\n",
       "      <td>197247000.0</td>\n",
       "      <td>93798000.0</td>\n",
       "      <td>107016000.0</td>\n",
       "      <td>0.056547</td>\n",
       "      <td>0.028353</td>\n",
       "      <td>1.020768</td>\n",
       "      <td>-0.002568</td>\n",
       "      <td>-0.002621</td>\n",
       "      <td>0.018224</td>\n",
       "      <td>Construction</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18052</th>\n",
       "      <td>806999469</td>\n",
       "      <td>2016</td>\n",
       "      <td>4.973076e+09</td>\n",
       "      <td>276199000.0</td>\n",
       "      <td>4.515886e+09</td>\n",
       "      <td>95822000.0</td>\n",
       "      <td>457190000.0</td>\n",
       "      <td>4.038620e+09</td>\n",
       "      <td>255270000.0</td>\n",
       "      <td>201920000.0</td>\n",
       "      <td>106098000.0</td>\n",
       "      <td>0.091933</td>\n",
       "      <td>0.055539</td>\n",
       "      <td>1.231380</td>\n",
       "      <td>0.019268</td>\n",
       "      <td>0.023726</td>\n",
       "      <td>0.040603</td>\n",
       "      <td>Construction</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18053</th>\n",
       "      <td>806999469</td>\n",
       "      <td>2018</td>\n",
       "      <td>4.454662e+09</td>\n",
       "      <td>229054000.0</td>\n",
       "      <td>4.000209e+09</td>\n",
       "      <td>83436000.0</td>\n",
       "      <td>454453000.0</td>\n",
       "      <td>4.387752e+09</td>\n",
       "      <td>262577000.0</td>\n",
       "      <td>191876000.0</td>\n",
       "      <td>108440000.0</td>\n",
       "      <td>0.102017</td>\n",
       "      <td>0.051419</td>\n",
       "      <td>1.015249</td>\n",
       "      <td>0.018730</td>\n",
       "      <td>0.019016</td>\n",
       "      <td>0.043073</td>\n",
       "      <td>Construction</td>\n",
       "      <td>CA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18495</th>\n",
       "      <td>220248046</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.204000e+09</td>\n",
       "      <td>398900000.0</td>\n",
       "      <td>1.338200e+09</td>\n",
       "      <td>222700000.0</td>\n",
       "      <td>865800000.0</td>\n",
       "      <td>4.640300e+09</td>\n",
       "      <td>563700000.0</td>\n",
       "      <td>302100000.0</td>\n",
       "      <td>79400000.0</td>\n",
       "      <td>0.392831</td>\n",
       "      <td>0.180989</td>\n",
       "      <td>0.474969</td>\n",
       "      <td>0.101044</td>\n",
       "      <td>0.047993</td>\n",
       "      <td>0.137069</td>\n",
       "      <td>Construction</td>\n",
       "      <td>MN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18496</th>\n",
       "      <td>220248046</td>\n",
       "      <td>2020</td>\n",
       "      <td>2.044100e+09</td>\n",
       "      <td>118100000.0</td>\n",
       "      <td>1.272100e+09</td>\n",
       "      <td>-48800000.0</td>\n",
       "      <td>772000000.0</td>\n",
       "      <td>4.410600e+09</td>\n",
       "      <td>755900000.0</td>\n",
       "      <td>16100000.0</td>\n",
       "      <td>64900000.0</td>\n",
       "      <td>0.377672</td>\n",
       "      <td>0.057776</td>\n",
       "      <td>0.463452</td>\n",
       "      <td>-0.023874</td>\n",
       "      <td>-0.011064</td>\n",
       "      <td>0.007876</td>\n",
       "      <td>Construction</td>\n",
       "      <td>MN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>263 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           bq_id  bq_year  ...  bq_company_address1_state  bq_public_indicator\n",
       "657    967622468     2016  ...                         FL                    1\n",
       "658    967622468     2020  ...                         FL                    1\n",
       "659    967622468     2015  ...                         FL                    1\n",
       "660    967622468     2018  ...                         FL                    1\n",
       "661    967622468     2019  ...                         FL                    1\n",
       "...          ...      ...  ...                        ...                  ...\n",
       "18051  806999469     2020  ...                         CA                    1\n",
       "18052  806999469     2016  ...                         CA                    1\n",
       "18053  806999469     2018  ...                         CA                    1\n",
       "18495  220248046     2019  ...                         MN                    1\n",
       "18496  220248046     2020  ...                         MN                    1\n",
       "\n",
       "[263 rows x 20 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Construction = df[(df.bq_sector_name == \"Construction\")]\n",
    "Construction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 609
    },
    "id": "hmHOYNeMtTUk",
    "outputId": "a892f552-0b28-4074-9d79-e7e105832229"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
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       "      <th>bq_net_profit_margin</th>\n",
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       "      <th>bq_return_on_sales</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1694</th>\n",
       "      <td>467200091</td>\n",
       "      <td>2019</td>\n",
       "      <td>3.250326e+09</td>\n",
       "      <td>1.502500e+09</td>\n",
       "      <td>2.671557e+09</td>\n",
       "      <td>938484000.0</td>\n",
       "      <td>578769000.0</td>\n",
       "      <td>6.496423e+09</td>\n",
       "      <td>243427000.0</td>\n",
       "      <td>335342000.0</td>\n",
       "      <td>-603142000.0</td>\n",
       "      <td>0.178065</td>\n",
       "      <td>0.462261</td>\n",
       "      <td>0.500325</td>\n",
       "      <td>0.288735</td>\n",
       "      <td>0.144462</td>\n",
       "      <td>0.103172</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>MD</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1695</th>\n",
       "      <td>467200091</td>\n",
       "      <td>2017</td>\n",
       "      <td>3.333073e+09</td>\n",
       "      <td>5.981180e+08</td>\n",
       "      <td>2.775326e+09</td>\n",
       "      <td>91465000.0</td>\n",
       "      <td>557747000.0</td>\n",
       "      <td>7.391285e+09</td>\n",
       "      <td>324484000.0</td>\n",
       "      <td>233263000.0</td>\n",
       "      <td>141798000.0</td>\n",
       "      <td>0.167337</td>\n",
       "      <td>0.179449</td>\n",
       "      <td>0.450946</td>\n",
       "      <td>0.027442</td>\n",
       "      <td>0.012375</td>\n",
       "      <td>0.069984</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>MD</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1696</th>\n",
       "      <td>467200091</td>\n",
       "      <td>2020</td>\n",
       "      <td>2.416787e+09</td>\n",
       "      <td>-8.281000e+08</td>\n",
       "      <td>1.972163e+09</td>\n",
       "      <td>-931775000.0</td>\n",
       "      <td>444624000.0</td>\n",
       "      <td>5.175149e+09</td>\n",
       "      <td>982630000.0</td>\n",
       "      <td>-538006000.0</td>\n",
       "      <td>393769000.0</td>\n",
       "      <td>0.183973</td>\n",
       "      <td>-0.342645</td>\n",
       "      <td>0.466999</td>\n",
       "      <td>-0.385543</td>\n",
       "      <td>-0.180048</td>\n",
       "      <td>-0.222612</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>MD</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1697</th>\n",
       "      <td>467200091</td>\n",
       "      <td>2016</td>\n",
       "      <td>3.301864e+09</td>\n",
       "      <td>1.061557e+09</td>\n",
       "      <td>2.788691e+09</td>\n",
       "      <td>371847000.0</td>\n",
       "      <td>513173000.0</td>\n",
       "      <td>7.062470e+09</td>\n",
       "      <td>222039000.0</td>\n",
       "      <td>291134000.0</td>\n",
       "      <td>-80713000.0</td>\n",
       "      <td>0.155419</td>\n",
       "      <td>0.321502</td>\n",
       "      <td>0.467523</td>\n",
       "      <td>0.112617</td>\n",
       "      <td>0.052651</td>\n",
       "      <td>0.088173</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>MD</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1698</th>\n",
       "      <td>467200091</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.291659e+09</td>\n",
       "      <td>4.824700e+08</td>\n",
       "      <td>3.760016e+09</td>\n",
       "      <td>-316248000.0</td>\n",
       "      <td>531643000.0</td>\n",
       "      <td>7.439116e+09</td>\n",
       "      <td>194491000.0</td>\n",
       "      <td>337152000.0</td>\n",
       "      <td>653400000.0</td>\n",
       "      <td>0.123878</td>\n",
       "      <td>0.112420</td>\n",
       "      <td>0.576904</td>\n",
       "      <td>-0.073689</td>\n",
       "      <td>-0.042512</td>\n",
       "      <td>0.078560</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>MD</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>13553</th>\n",
       "      <td>312139456</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.862700e+08</td>\n",
       "      <td>3.079600e+07</td>\n",
       "      <td>1.119160e+08</td>\n",
       "      <td>10013000.0</td>\n",
       "      <td>174354000.0</td>\n",
       "      <td>3.548970e+08</td>\n",
       "      <td>161598000.0</td>\n",
       "      <td>12756000.0</td>\n",
       "      <td>2743000.0</td>\n",
       "      <td>0.609054</td>\n",
       "      <td>0.107577</td>\n",
       "      <td>0.806628</td>\n",
       "      <td>0.034977</td>\n",
       "      <td>0.028214</td>\n",
       "      <td>0.044559</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>WV</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15034</th>\n",
       "      <td>909876598</td>\n",
       "      <td>2017</td>\n",
       "      <td>7.066300e+07</td>\n",
       "      <td>3.350000e+05</td>\n",
       "      <td>4.029800e+07</td>\n",
       "      <td>-2137000.0</td>\n",
       "      <td>30365000.0</td>\n",
       "      <td>2.626300e+07</td>\n",
       "      <td>31700000.0</td>\n",
       "      <td>-1335000.0</td>\n",
       "      <td>802000.0</td>\n",
       "      <td>0.429716</td>\n",
       "      <td>0.004741</td>\n",
       "      <td>2.690591</td>\n",
       "      <td>-0.030242</td>\n",
       "      <td>-0.081369</td>\n",
       "      <td>-0.018892</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>VA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15035</th>\n",
       "      <td>909876598</td>\n",
       "      <td>2018</td>\n",
       "      <td>6.431800e+07</td>\n",
       "      <td>-4.970000e+05</td>\n",
       "      <td>3.664200e+07</td>\n",
       "      <td>-2059000.0</td>\n",
       "      <td>27676000.0</td>\n",
       "      <td>2.264800e+07</td>\n",
       "      <td>29662000.0</td>\n",
       "      <td>-1986000.0</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>0.430299</td>\n",
       "      <td>-0.007727</td>\n",
       "      <td>2.839898</td>\n",
       "      <td>-0.032013</td>\n",
       "      <td>-0.090913</td>\n",
       "      <td>-0.030878</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>VA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15036</th>\n",
       "      <td>909876598</td>\n",
       "      <td>2015</td>\n",
       "      <td>9.488400e+07</td>\n",
       "      <td>-7.788000e+06</td>\n",
       "      <td>5.580900e+07</td>\n",
       "      <td>-12573000.0</td>\n",
       "      <td>39075000.0</td>\n",
       "      <td>4.392100e+07</td>\n",
       "      <td>48770000.0</td>\n",
       "      <td>-9695000.0</td>\n",
       "      <td>2878000.0</td>\n",
       "      <td>0.411819</td>\n",
       "      <td>-0.082079</td>\n",
       "      <td>2.160333</td>\n",
       "      <td>-0.132509</td>\n",
       "      <td>-0.286264</td>\n",
       "      <td>-0.102177</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>VA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15037</th>\n",
       "      <td>909876598</td>\n",
       "      <td>2016</td>\n",
       "      <td>8.158700e+07</td>\n",
       "      <td>-9.459000e+06</td>\n",
       "      <td>5.016300e+07</td>\n",
       "      <td>-12696000.0</td>\n",
       "      <td>31424000.0</td>\n",
       "      <td>3.160700e+07</td>\n",
       "      <td>43925000.0</td>\n",
       "      <td>-12501000.0</td>\n",
       "      <td>195000.0</td>\n",
       "      <td>0.385159</td>\n",
       "      <td>-0.115938</td>\n",
       "      <td>2.581295</td>\n",
       "      <td>-0.155613</td>\n",
       "      <td>-0.401683</td>\n",
       "      <td>-0.153223</td>\n",
       "      <td>Educational Services</td>\n",
       "      <td>VA</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           bq_id  bq_year  ...  bq_company_address1_state  bq_public_indicator\n",
       "1694   467200091     2019  ...                         MD                    1\n",
       "1695   467200091     2017  ...                         MD                    1\n",
       "1696   467200091     2020  ...                         MD                    1\n",
       "1697   467200091     2016  ...                         MD                    1\n",
       "1698   467200091     2015  ...                         MD                    1\n",
       "...          ...      ...  ...                        ...                  ...\n",
       "13553  312139456     2019  ...                         WV                    1\n",
       "15034  909876598     2017  ...                         VA                    1\n",
       "15035  909876598     2018  ...                         VA                    1\n",
       "15036  909876598     2015  ...                         VA                    1\n",
       "15037  909876598     2016  ...                         VA                    1\n",
       "\n",
       "[80 rows x 20 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EducationalServices = df[(df.bq_sector_name == \"Educational Services\")]\n",
    "EducationalServices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "T1uz7u4VtTdZ",
    "outputId": "4653c8af-e6f8-4cc0-9cd2-0ad281f4c7bd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.095602\n",
       "1    0.146908\n",
       "2    0.123741\n",
       "3    0.157851\n",
       "4    0.237549\n",
       "5    0.059427\n",
       "Name: bq_ebitda, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EducationalServices_avg = EducationalServices.groupby([\"bq_year\"]).mean().reset_index()\n",
    "EducationalServices_avg[\"bq_ebitda\"]/1000000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "eH79vC_-vc3B",
    "outputId": "a82098d2-c597-445f-f802-e16a4ff5e5ce"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.327093\n",
       "1    0.320964\n",
       "2    0.338672\n",
       "3    0.426147\n",
       "4    0.417530\n",
       "5    0.473176\n",
       "Name: bq_ebitda, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Construction_avg = Construction.groupby([\"bq_year\"]).mean().reset_index()\n",
    "Construction_avg[\"bq_ebitda\"]/1000000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "R6GDdE2evc-q",
    "outputId": "1cfe30ad-534c-4bad-82ae-f2beeb5cf782"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.067515\n",
       "1    0.818534\n",
       "2    1.429832\n",
       "3    1.864839\n",
       "4    1.541920\n",
       "5   -0.097118\n",
       "Name: bq_ebitda, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mining_avg = Mining.groupby([\"bq_year\"]).mean().reset_index()\n",
    "Mining_avg[\"bq_ebitda\"]/1000000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "fEhJppp-vdEb",
    "outputId": "f89e4767-2af9-4337-c37a-9d83716273ff"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.375589\n",
       "1    1.372222\n",
       "2    1.310665\n",
       "3    1.332772\n",
       "4    1.539365\n",
       "5    1.608696\n",
       "Name: bq_ebitda, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RetailTrade_avg = RetailTrade.groupby([\"bq_year\"]).mean().reset_index()\n",
    "RetailTrade_avg[\"bq_ebitda\"]/1000000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "aNnCXY9VvdIc",
    "outputId": "d79e6148-df13-4c69-ac1a-d28f6acb105e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.109430\n",
       "1    1.049739\n",
       "2    1.139253\n",
       "3    1.228498\n",
       "4    1.166490\n",
       "5    0.915905\n",
       "Name: bq_ebitda, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Manufacturing_avg = Manufacturing.groupby([\"bq_year\"]).mean().reset_index()\n",
    "Manufacturing_avg[\"bq_ebitda\"]/1000000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 255
    },
    "id": "k0ooA6hz1tlB",
    "outputId": "40e0866d-b460-46af-f60b-fe9d1c664d8f"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_id</th>\n",
       "      <th>bq_revenue</th>\n",
       "      <th>bq_ebitda</th>\n",
       "      <th>bq_cor</th>\n",
       "      <th>bq_net_income</th>\n",
       "      <th>bq_gross_profit</th>\n",
       "      <th>bq_total_assets</th>\n",
       "      <th>bq_operating_expenses</th>\n",
       "      <th>bq_operating_income</th>\n",
       "      <th>bq_tax_and_interest</th>\n",
       "      <th>bq_gross_profit_margin</th>\n",
       "      <th>bq_ebitda_margin</th>\n",
       "      <th>bq_asset_turnover</th>\n",
       "      <th>bq_net_profit_margin</th>\n",
       "      <th>bq_return_on_assets</th>\n",
       "      <th>bq_return_on_sales</th>\n",
       "      <th>bq_public_indicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>5.575933e+08</td>\n",
       "      <td>6.284151e+09</td>\n",
       "      <td>1.109430e+09</td>\n",
       "      <td>4.288128e+09</td>\n",
       "      <td>5.091820e+08</td>\n",
       "      <td>1.996023e+09</td>\n",
       "      <td>9.538485e+09</td>\n",
       "      <td>1.286275e+09</td>\n",
       "      <td>7.097482e+08</td>\n",
       "      <td>2.005662e+08</td>\n",
       "      <td>0.371899</td>\n",
       "      <td>-4.180077</td>\n",
       "      <td>0.949161</td>\n",
       "      <td>-4.492613</td>\n",
       "      <td>-0.043438</td>\n",
       "      <td>-4.451932</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>5.565230e+08</td>\n",
       "      <td>6.000278e+09</td>\n",
       "      <td>1.049739e+09</td>\n",
       "      <td>4.064935e+09</td>\n",
       "      <td>4.582679e+08</td>\n",
       "      <td>1.935343e+09</td>\n",
       "      <td>9.766468e+09</td>\n",
       "      <td>1.280683e+09</td>\n",
       "      <td>6.546607e+08</td>\n",
       "      <td>1.963928e+08</td>\n",
       "      <td>0.358665</td>\n",
       "      <td>-4.733823</td>\n",
       "      <td>0.904770</td>\n",
       "      <td>-4.930622</td>\n",
       "      <td>-0.063192</td>\n",
       "      <td>-5.016988</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>5.579295e+08</td>\n",
       "      <td>6.375720e+09</td>\n",
       "      <td>1.139253e+09</td>\n",
       "      <td>4.317706e+09</td>\n",
       "      <td>4.717407e+08</td>\n",
       "      <td>2.058015e+09</td>\n",
       "      <td>1.028998e+10</td>\n",
       "      <td>1.346551e+09</td>\n",
       "      <td>7.114636e+08</td>\n",
       "      <td>2.397228e+08</td>\n",
       "      <td>0.371864</td>\n",
       "      <td>-1.697933</td>\n",
       "      <td>0.893176</td>\n",
       "      <td>-1.938998</td>\n",
       "      <td>-0.062113</td>\n",
       "      <td>-2.351701</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>5.576706e+08</td>\n",
       "      <td>6.867711e+09</td>\n",
       "      <td>1.228498e+09</td>\n",
       "      <td>4.669632e+09</td>\n",
       "      <td>5.943659e+08</td>\n",
       "      <td>2.198078e+09</td>\n",
       "      <td>1.039765e+10</td>\n",
       "      <td>1.402568e+09</td>\n",
       "      <td>7.955106e+08</td>\n",
       "      <td>2.011447e+08</td>\n",
       "      <td>0.371153</td>\n",
       "      <td>-0.954172</td>\n",
       "      <td>0.915073</td>\n",
       "      <td>-1.092808</td>\n",
       "      <td>-0.062806</td>\n",
       "      <td>-1.025172</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019</td>\n",
       "      <td>5.560720e+08</td>\n",
       "      <td>6.758965e+09</td>\n",
       "      <td>1.166490e+09</td>\n",
       "      <td>4.609460e+09</td>\n",
       "      <td>5.301636e+08</td>\n",
       "      <td>2.149505e+09</td>\n",
       "      <td>1.054967e+10</td>\n",
       "      <td>1.439493e+09</td>\n",
       "      <td>7.100124e+08</td>\n",
       "      <td>1.798488e+08</td>\n",
       "      <td>0.374034</td>\n",
       "      <td>-5.869985</td>\n",
       "      <td>0.851020</td>\n",
       "      <td>-6.411237</td>\n",
       "      <td>-0.062956</td>\n",
       "      <td>-7.634931</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020</td>\n",
       "      <td>5.566872e+08</td>\n",
       "      <td>5.649802e+09</td>\n",
       "      <td>9.159047e+08</td>\n",
       "      <td>3.826836e+09</td>\n",
       "      <td>3.694098e+08</td>\n",
       "      <td>1.822966e+09</td>\n",
       "      <td>9.627785e+09</td>\n",
       "      <td>1.329001e+09</td>\n",
       "      <td>4.939647e+08</td>\n",
       "      <td>1.245549e+08</td>\n",
       "      <td>0.368326</td>\n",
       "      <td>-7.266977</td>\n",
       "      <td>0.770416</td>\n",
       "      <td>-7.853438</td>\n",
       "      <td>-0.073594</td>\n",
       "      <td>-5.989369</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bq_year         bq_id  ...  bq_return_on_sales  bq_public_indicator\n",
       "0     2015  5.575933e+08  ...           -4.451932                  1.0\n",
       "1     2016  5.565230e+08  ...           -5.016988                  1.0\n",
       "2     2017  5.579295e+08  ...           -2.351701                  1.0\n",
       "3     2018  5.576706e+08  ...           -1.025172                  1.0\n",
       "4     2019  5.560720e+08  ...           -7.634931                  1.0\n",
       "5     2020  5.566872e+08  ...           -5.989369                  1.0\n",
       "\n",
       "[6 rows x 18 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Manufacturing_avg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "I7Mbkt3_vdMU",
    "outputId": "01c69803-d0b8-4771-e5b7-c5cd0059e547"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2015\n",
       "1    2016\n",
       "2    2017\n",
       "3    2018\n",
       "4    2019\n",
       "5    2020\n",
       "Name: bq_year, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year = Manufacturing_avg[\"bq_year\"]\n",
    "year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ZYvXbXbRy7xT"
   },
   "outputs": [],
   "source": [
    "df_lines = pd.concat([year, Manufacturing_avg[\"bq_ebitda\"]/1000000000, RetailTrade_avg[\"bq_ebitda\"]/1000000000, Mining_avg[\"bq_ebitda\"]/1000000000,\n",
    "                       Construction_avg[\"bq_ebitda\"]/1000000000, EducationalServices_avg[\"bq_ebitda\"]/1000000000], axis=1, \n",
    "                      keys=[\"YEAR\", \"Manufacturing\", \"Retail Trade\", \"Mining\", \"Construction\", \"Educational Services\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 235
    },
    "id": "kg5IetytwWtv",
    "outputId": "d54441ad-fd18-4c21-8a14-31a81958c819"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YEAR</th>\n",
       "      <th>Manufacturing</th>\n",
       "      <th>Retail Trade</th>\n",
       "      <th>Mining</th>\n",
       "      <th>Construction</th>\n",
       "      <th>Educational Services</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>1.109430</td>\n",
       "      <td>1.375589</td>\n",
       "      <td>0.067515</td>\n",
       "      <td>0.327093</td>\n",
       "      <td>0.095602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>1.049739</td>\n",
       "      <td>1.372222</td>\n",
       "      <td>0.818534</td>\n",
       "      <td>0.320964</td>\n",
       "      <td>0.146908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>1.139253</td>\n",
       "      <td>1.310665</td>\n",
       "      <td>1.429832</td>\n",
       "      <td>0.338672</td>\n",
       "      <td>0.123741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>1.228498</td>\n",
       "      <td>1.332772</td>\n",
       "      <td>1.864839</td>\n",
       "      <td>0.426147</td>\n",
       "      <td>0.157851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019</td>\n",
       "      <td>1.166490</td>\n",
       "      <td>1.539365</td>\n",
       "      <td>1.541920</td>\n",
       "      <td>0.417530</td>\n",
       "      <td>0.237549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020</td>\n",
       "      <td>0.915905</td>\n",
       "      <td>1.608696</td>\n",
       "      <td>-0.097118</td>\n",
       "      <td>0.473176</td>\n",
       "      <td>0.059427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YEAR  Manufacturing  ...  Construction  Educational Services\n",
       "0  2015       1.109430  ...      0.327093              0.095602\n",
       "1  2016       1.049739  ...      0.320964              0.146908\n",
       "2  2017       1.139253  ...      0.338672              0.123741\n",
       "3  2018       1.228498  ...      0.426147              0.157851\n",
       "4  2019       1.166490  ...      0.417530              0.237549\n",
       "5  2020       0.915905  ...      0.473176              0.059427\n",
       "\n",
       "[6 rows x 6 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 574
    },
    "id": "45IRRyhb1_hT",
    "outputId": "a5b223fe-9a1c-4302-9799-dbf17260ee5a"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8))\n",
    "fig.suptitle(\"Ebitda Differs In Sectors\",fontsize=20, x=0.47,\n",
    "y=1.00, fontweight =\"bold\")\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"Manufacturing\"], color =\n",
    "\"dodgerblue\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"Retail Trade\"], color =\n",
    "\"red\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"Mining\"], color = \"purple\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"Construction\"], color = \"darkorange\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"Educational Services\"], color = \"green\", lw = 2)\n",
    "#ax.set_title(\"Ebitda Avg In Billions, by year\", loc='left', fontsize=18)\n",
    "ax.grid()\n",
    "ax.set_facecolor('#F2F2F2')\n",
    "ax.annotate(\"Manufacturing\", xy=(2015,1.15), color=\"dodgerblue\" , fontsize=14)\n",
    "ax.annotate(\"Retail Trade\", xy=(2015.5, 1.4), color=\"red\", fontsize=14)\n",
    "ax.annotate(\"Mining\", xy=(2018,1.9), color=\"purple\", fontsize=14) \n",
    "ax.annotate(\"Educational Services\", xy=(2018, 0.25), color=\"green\", fontsize=14)\n",
    "ax.annotate(\"Construction\", xy=(2016,0.4), color=\"darkorange\", fontsize=14)\n",
    "ax.set(xlim=(2015, 2020), ylim=(-0.1, 2.0))\n",
    "ax.set_xlabel(\"Year\",fontsize=16)\n",
    "ax.set_ylabel(\"Avg Ebita in Billions of Dollars\",fontsize=16)\n",
    "# xlabels = [\"2000\", \"' 04\", \"' 08\",\"' 12\"]\n",
    "# ylabels = [\"0\", \"25\", \"50\", \"75\", \"100%\"]\n",
    "# ax.set_xticklabels(xlabels)\n",
    "# ax.set_yticklabels(ylabels)\n",
    "ax.tick_params(labelsize=13)\n",
    "ax.set_frame_on(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fIuBUBZll_f_"
   },
   "source": [
    "## Ebitda Differs In States"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "CeZo8Uz-1_oR"
   },
   "outputs": [],
   "source": [
    "CA = df[(df.bq_company_address1_state == \"CA\")]\n",
    "NY = df[(df.bq_company_address1_state == \"NY\")]\n",
    "TX = df[(df.bq_company_address1_state == \"TX\")]\n",
    "WI = df[(df.bq_company_address1_state == \"WI\")]\n",
    "WV = df[(df.bq_company_address1_state == \"WV\")]\n",
    "WA = df[(df.bq_company_address1_state == \"WA\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "89GtMPGn8TW_"
   },
   "outputs": [],
   "source": [
    "CA_avg = CA.groupby([\"bq_year\"]).mean().reset_index()\n",
    "NY_avg = NY.groupby([\"bq_year\"]).mean().reset_index()\n",
    "TX_avg = TX.groupby([\"bq_year\"]).mean().reset_index()\n",
    "WI_avg = WI.groupby([\"bq_year\"]).mean().reset_index()\n",
    "WV_avg = WV.groupby([\"bq_year\"]).mean().reset_index()\n",
    "WA_avg = WA.groupby([\"bq_year\"]).mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 235
    },
    "id": "I8PyrvSTAUaf",
    "outputId": "7205331e-e5b6-4a6f-ec25-652562911da7"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YEAR</th>\n",
       "      <th>CA</th>\n",
       "      <th>NY</th>\n",
       "      <th>TX</th>\n",
       "      <th>WI</th>\n",
       "      <th>WV</th>\n",
       "      <th>WA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>0.902807</td>\n",
       "      <td>1.119902</td>\n",
       "      <td>1.161626</td>\n",
       "      <td>0.461432</td>\n",
       "      <td>-0.015067</td>\n",
       "      <td>1.396313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>0.868823</td>\n",
       "      <td>1.142462</td>\n",
       "      <td>1.222060</td>\n",
       "      <td>0.523962</td>\n",
       "      <td>0.080754</td>\n",
       "      <td>1.538768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>0.909801</td>\n",
       "      <td>1.285251</td>\n",
       "      <td>1.402535</td>\n",
       "      <td>0.604107</td>\n",
       "      <td>0.100934</td>\n",
       "      <td>1.760866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>0.966766</td>\n",
       "      <td>1.204322</td>\n",
       "      <td>1.756768</td>\n",
       "      <td>0.612220</td>\n",
       "      <td>0.141180</td>\n",
       "      <td>2.086717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019</td>\n",
       "      <td>0.983844</td>\n",
       "      <td>1.145483</td>\n",
       "      <td>1.569819</td>\n",
       "      <td>0.676404</td>\n",
       "      <td>0.132520</td>\n",
       "      <td>2.133538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020</td>\n",
       "      <td>0.972052</td>\n",
       "      <td>0.694673</td>\n",
       "      <td>0.632719</td>\n",
       "      <td>0.534572</td>\n",
       "      <td>0.056614</td>\n",
       "      <td>2.293020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YEAR        CA        NY        TX        WI        WV        WA\n",
       "0  2015  0.902807  1.119902  1.161626  0.461432 -0.015067  1.396313\n",
       "1  2016  0.868823  1.142462  1.222060  0.523962  0.080754  1.538768\n",
       "2  2017  0.909801  1.285251  1.402535  0.604107  0.100934  1.760866\n",
       "3  2018  0.966766  1.204322  1.756768  0.612220  0.141180  2.086717\n",
       "4  2019  0.983844  1.145483  1.569819  0.676404  0.132520  2.133538\n",
       "5  2020  0.972052  0.694673  0.632719  0.534572  0.056614  2.293020"
      ]
     },
     "execution_count": 36,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lines = pd.concat([year, CA_avg[\"bq_ebitda\"]/1000000000, NY_avg[\"bq_ebitda\"]/1000000000, TX_avg[\"bq_ebitda\"]/1000000000,\n",
    "                       WI_avg[\"bq_ebitda\"]/1000000000, WV_avg[\"bq_ebitda\"]/1000000000, WA_avg[\"bq_ebitda\"]/1000000000], axis=1, \n",
    "                      keys=[\"YEAR\", \"CA\", \"NY\", \"TX\", \"WI\", \"WV\",\"WA\"])\n",
    "\n",
    "df_lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 574
    },
    "id": "gLRdUUW8B_95",
    "outputId": "bcc26c21-28c2-4944-afff-b93aca181798"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8))\n",
    "fig.suptitle(\"Ebitda Differs In States\",fontsize=20, x=0.47,\n",
    "y=1.00, fontweight =\"bold\")\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"CA\"], color =\n",
    "\"dodgerblue\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"NY\"], color =\n",
    "\"red\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"TX\"], color = \"purple\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"WI\"], color = \"darkorange\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"WV\"], color = \"green\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"WA\"], color = \"darkcyan\", lw = 2)\n",
    "#ax.set_title(\"Ebitda Avg In Billions, by year\", loc='left', fontsize=18)\n",
    "ax.grid()\n",
    "#ax.set_facecolor('#F2F2F2')\n",
    "ax.annotate(\"California\", xy=(2015.3,0.92), color=\"dodgerblue\" , fontsize=14)\n",
    "ax.annotate(\"New York\", xy=(2018, 1.25), color=\"red\", fontsize=14)\n",
    "ax.annotate(\"Texas\", xy=(2018,1.8), color=\"purple\", fontsize=14) \n",
    "ax.annotate(\"West Virginia\", xy=(2018, 0.2), color=\"green\", fontsize=14)\n",
    "ax.annotate(\"Wisconsin\", xy=(2016,0.6), color=\"darkorange\", fontsize=14)\n",
    "ax.annotate(\"Washington\", xy=(2018.2,2.2), color=\"darkcyan\", fontsize=14)\n",
    "ax.set(xlim=(2015, 2020), ylim=(-0.1, 2.5))\n",
    "ax.set_xlabel(\"Year\",fontsize=16)\n",
    "ax.set_ylabel(\"Avg Ebita in Billions of Dollars\",fontsize=16)\n",
    "# xlabels = [\"2000\", \"' 04\", \"' 08\",\"' 12\"]\n",
    "# ylabels = [\"0\", \"25\", \"50\", \"75\", \"100%\"]\n",
    "# ax.set_xticklabels(xlabels)\n",
    "# ax.set_yticklabels(ylabels)\n",
    "ax.tick_params(labelsize=13)\n",
    "ax.set_frame_on(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C30iDrGgl0NP"
   },
   "source": [
    "## Aggregation of Statistics in U.S. Public Companies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 284
    },
    "id": "tMj_Lldz8TrJ",
    "outputId": "4a5e6d66-b521-41bc-974e-20df7d5f8d89"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_number_of_companies_in_us_ts</th>\n",
       "      <th>bq_number_of_companies_in_us_ts_pub</th>\n",
       "      <th>bq_return_on_assets_us_med</th>\n",
       "      <th>bq_return_on_assets_us_stdev</th>\n",
       "      <th>bq_return_on_assets_us_avg</th>\n",
       "      <th>bq_return_on_assets_us_tot</th>\n",
       "      <th>bq_return_on_assets_us_pub_med</th>\n",
       "      <th>bq_return_on_assets_us_pub_stdev</th>\n",
       "      <th>bq_return_on_assets_us_pub_avg</th>\n",
       "      <th>bq_return_on_assets_us_pub_tot</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_med</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_stdev</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_avg</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_tot</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_pub_med</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_pub_stdev</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_pub_avg</th>\n",
       "      <th>bq_growth_total_assets_1yr_us_pub_tot</th>\n",
       "      <th>bq_gross_profit_margin_us_med</th>\n",
       "      <th>bq_gross_profit_margin_us_stdev</th>\n",
       "      <th>bq_gross_profit_margin_us_avg</th>\n",
       "      <th>bq_gross_profit_margin_us_tot</th>\n",
       "      <th>bq_gross_profit_margin_us_pub_med</th>\n",
       "      <th>bq_gross_profit_margin_us_pub_stdev</th>\n",
       "      <th>bq_gross_profit_margin_us_pub_avg</th>\n",
       "      <th>bq_gross_profit_margin_us_pub_tot</th>\n",
       "      <th>bq_no_profit_sharing_ind_us_avg</th>\n",
       "      <th>bq_no_profit_sharing_ind_us_tot</th>\n",
       "      <th>bq_no_profit_sharing_ind_us_pub_avg</th>\n",
       "      <th>bq_no_profit_sharing_ind_us_pub_tot</th>\n",
       "      <th>bq_money_purchase_plan_ind_us_avg</th>\n",
       "      <th>bq_money_purchase_plan_ind_us_tot</th>\n",
       "      <th>bq_money_purchase_plan_ind_us_pub_avg</th>\n",
       "      <th>bq_money_purchase_plan_ind_us_pub_tot</th>\n",
       "      <th>bq_tax_and_interest_us_med</th>\n",
       "      <th>bq_tax_and_interest_us_stdev</th>\n",
       "      <th>bq_tax_and_interest_us_avg</th>\n",
       "      <th>bq_tax_and_interest_us_tot</th>\n",
       "      <th>bq_tax_and_interest_us_pub_med</th>\n",
       "      <th>...</th>\n",
       "      <th>bq_growth_welfare_score_1yr_us_pub_stdev</th>\n",
       "      <th>bq_growth_welfare_score_1yr_us_pub_avg</th>\n",
       "      <th>bq_growth_welfare_score_1yr_us_pub_tot</th>\n",
       "      <th>bq_stock_bonus_ind_us_avg</th>\n",
       "      <th>bq_stock_bonus_ind_us_tot</th>\n",
       "      <th>bq_stock_bonus_ind_us_pub_avg</th>\n",
       "      <th>bq_stock_bonus_ind_us_pub_tot</th>\n",
       "      <th>bq_tot_plans_ct_us_med</th>\n",
       "      <th>bq_tot_plans_ct_us_stdev</th>\n",
       "      <th>bq_tot_plans_ct_us_avg</th>\n",
       "      <th>bq_tot_plans_ct_us_tot</th>\n",
       "      <th>bq_tot_plans_ct_us_pub_med</th>\n",
       "      <th>bq_tot_plans_ct_us_pub_stdev</th>\n",
       "      <th>bq_tot_plans_ct_us_pub_avg</th>\n",
       "      <th>bq_tot_plans_ct_us_pub_tot</th>\n",
       "      <th>bq_profit_plan_no_co_contribs_ind_us_avg</th>\n",
       "      <th>bq_profit_plan_no_co_contribs_ind_us_tot</th>\n",
       "      <th>bq_profit_plan_no_co_contribs_ind_us_pub_avg</th>\n",
       "      <th>bq_profit_plan_no_co_contribs_ind_us_pub_tot</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_med</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_stdev</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_avg</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_tot</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_pub_med</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_pub_stdev</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_pub_avg</th>\n",
       "      <th>bq_partic_curr_welf_eoy_ct_us_pub_tot</th>\n",
       "      <th>bq_revenue_us_med</th>\n",
       "      <th>bq_revenue_us_stdev</th>\n",
       "      <th>bq_revenue_us_avg</th>\n",
       "      <th>bq_revenue_us_tot</th>\n",
       "      <th>bq_revenue_us_pub_med</th>\n",
       "      <th>bq_revenue_us_pub_stdev</th>\n",
       "      <th>bq_revenue_us_pub_avg</th>\n",
       "      <th>bq_revenue_us_pub_tot</th>\n",
       "      <th>bq_vision_insurance_ind_us_avg</th>\n",
       "      <th>bq_vision_insurance_ind_us_tot</th>\n",
       "      <th>bq_vision_insurance_ind_us_pub_avg</th>\n",
       "      <th>bq_vision_insurance_ind_us_pub_tot</th>\n",
       "      <th>bq_company_fgn_address1_cntry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015</td>\n",
       "      <td>778754</td>\n",
       "      <td>3238</td>\n",
       "      <td>0.050562</td>\n",
       "      <td>0.786973</td>\n",
       "      <td>0.055031</td>\n",
       "      <td>39487.0</td>\n",
       "      <td>0.016266</td>\n",
       "      <td>12.002355</td>\n",
       "      <td>-0.318515</td>\n",
       "      <td>-979.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.400025</td>\n",
       "      <td>0.205012</td>\n",
       "      <td>0.425001</td>\n",
       "      <td>304924.0</td>\n",
       "      <td>0.470292</td>\n",
       "      <td>1.451701</td>\n",
       "      <td>0.489417</td>\n",
       "      <td>1466.0</td>\n",
       "      <td>0.228340</td>\n",
       "      <td>177821</td>\n",
       "      <td>0.097900</td>\n",
       "      <td>317</td>\n",
       "      <td>0.014219</td>\n",
       "      <td>11073</td>\n",
       "      <td>0.013589</td>\n",
       "      <td>44</td>\n",
       "      <td>75244.0</td>\n",
       "      <td>7.050783e+07</td>\n",
       "      <td>1.778172e+06</td>\n",
       "      <td>1.275963e+12</td>\n",
       "      <td>16982000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.314731</td>\n",
       "      <td>0.191987</td>\n",
       "      <td>604.0</td>\n",
       "      <td>0.004957</td>\n",
       "      <td>3860</td>\n",
       "      <td>0.053428</td>\n",
       "      <td>173</td>\n",
       "      <td>1</td>\n",
       "      <td>1.609801</td>\n",
       "      <td>1.207935</td>\n",
       "      <td>940684</td>\n",
       "      <td>2</td>\n",
       "      <td>4.849761</td>\n",
       "      <td>3.789376</td>\n",
       "      <td>12270</td>\n",
       "      <td>0.202597</td>\n",
       "      <td>157773</td>\n",
       "      <td>0.116430</td>\n",
       "      <td>377</td>\n",
       "      <td>0</td>\n",
       "      <td>2969.484286</td>\n",
       "      <td>86.350058</td>\n",
       "      <td>67245453</td>\n",
       "      <td>585.0</td>\n",
       "      <td>33525.259130</td>\n",
       "      <td>6086.380482</td>\n",
       "      <td>19707700</td>\n",
       "      <td>2022560.0</td>\n",
       "      <td>1.305583e+09</td>\n",
       "      <td>3.896115e+07</td>\n",
       "      <td>2.795735e+13</td>\n",
       "      <td>524206000.0</td>\n",
       "      <td>1.894770e+10</td>\n",
       "      <td>4.973084e+09</td>\n",
       "      <td>1.541159e+13</td>\n",
       "      <td>0.043933</td>\n",
       "      <td>34213</td>\n",
       "      <td>0.630327</td>\n",
       "      <td>2041</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016</td>\n",
       "      <td>788523</td>\n",
       "      <td>3317</td>\n",
       "      <td>0.050134</td>\n",
       "      <td>0.390611</td>\n",
       "      <td>0.054490</td>\n",
       "      <td>39576.0</td>\n",
       "      <td>0.013697</td>\n",
       "      <td>5.849778</td>\n",
       "      <td>-0.167882</td>\n",
       "      <td>-538.0</td>\n",
       "      <td>0.004713</td>\n",
       "      <td>3.354893</td>\n",
       "      <td>0.096750</td>\n",
       "      <td>65633.0</td>\n",
       "      <td>0.040524</td>\n",
       "      <td>2.177125</td>\n",
       "      <td>0.160444</td>\n",
       "      <td>488.0</td>\n",
       "      <td>0.397344</td>\n",
       "      <td>0.183048</td>\n",
       "      <td>0.422142</td>\n",
       "      <td>306558.0</td>\n",
       "      <td>0.471860</td>\n",
       "      <td>0.636714</td>\n",
       "      <td>0.513559</td>\n",
       "      <td>1599.0</td>\n",
       "      <td>0.225783</td>\n",
       "      <td>178035</td>\n",
       "      <td>0.100392</td>\n",
       "      <td>333</td>\n",
       "      <td>0.012515</td>\n",
       "      <td>9868</td>\n",
       "      <td>0.013265</td>\n",
       "      <td>44</td>\n",
       "      <td>84732.0</td>\n",
       "      <td>6.908025e+07</td>\n",
       "      <td>1.872364e+06</td>\n",
       "      <td>1.359904e+12</td>\n",
       "      <td>17638000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.513824</td>\n",
       "      <td>0.249798</td>\n",
       "      <td>804.0</td>\n",
       "      <td>0.004935</td>\n",
       "      <td>3891</td>\n",
       "      <td>0.053361</td>\n",
       "      <td>177</td>\n",
       "      <td>1</td>\n",
       "      <td>1.484814</td>\n",
       "      <td>1.230579</td>\n",
       "      <td>970340</td>\n",
       "      <td>2</td>\n",
       "      <td>4.698921</td>\n",
       "      <td>3.684052</td>\n",
       "      <td>12220</td>\n",
       "      <td>0.194495</td>\n",
       "      <td>153364</td>\n",
       "      <td>0.097980</td>\n",
       "      <td>325</td>\n",
       "      <td>0</td>\n",
       "      <td>3007.341935</td>\n",
       "      <td>87.676590</td>\n",
       "      <td>69135008</td>\n",
       "      <td>598.0</td>\n",
       "      <td>34315.532345</td>\n",
       "      <td>6082.536328</td>\n",
       "      <td>20175773</td>\n",
       "      <td>2075381.0</td>\n",
       "      <td>1.286325e+09</td>\n",
       "      <td>3.925231e+07</td>\n",
       "      <td>2.850907e+13</td>\n",
       "      <td>515874256.0</td>\n",
       "      <td>1.840288e+10</td>\n",
       "      <td>4.876621e+09</td>\n",
       "      <td>1.569784e+13</td>\n",
       "      <td>0.047385</td>\n",
       "      <td>37364</td>\n",
       "      <td>0.649985</td>\n",
       "      <td>2156</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017</td>\n",
       "      <td>792867</td>\n",
       "      <td>3381</td>\n",
       "      <td>0.049207</td>\n",
       "      <td>0.064632</td>\n",
       "      <td>0.053024</td>\n",
       "      <td>38723.0</td>\n",
       "      <td>0.015189</td>\n",
       "      <td>0.788652</td>\n",
       "      <td>-0.108298</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>0.008815</td>\n",
       "      <td>1.998283</td>\n",
       "      <td>0.080587</td>\n",
       "      <td>55233.0</td>\n",
       "      <td>0.059990</td>\n",
       "      <td>12.565437</td>\n",
       "      <td>0.565685</td>\n",
       "      <td>1793.0</td>\n",
       "      <td>0.389893</td>\n",
       "      <td>0.183086</td>\n",
       "      <td>0.417532</td>\n",
       "      <td>304871.0</td>\n",
       "      <td>0.476610</td>\n",
       "      <td>0.802993</td>\n",
       "      <td>0.502606</td>\n",
       "      <td>1601.0</td>\n",
       "      <td>0.218576</td>\n",
       "      <td>173302</td>\n",
       "      <td>0.101449</td>\n",
       "      <td>343</td>\n",
       "      <td>0.011088</td>\n",
       "      <td>8791</td>\n",
       "      <td>0.010944</td>\n",
       "      <td>37</td>\n",
       "      <td>87401.5</td>\n",
       "      <td>9.275169e+07</td>\n",
       "      <td>2.087895e+06</td>\n",
       "      <td>1.524781e+12</td>\n",
       "      <td>12906000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.406702</td>\n",
       "      <td>0.215088</td>\n",
       "      <td>709.0</td>\n",
       "      <td>0.004925</td>\n",
       "      <td>3905</td>\n",
       "      <td>0.049689</td>\n",
       "      <td>168</td>\n",
       "      <td>1</td>\n",
       "      <td>1.550245</td>\n",
       "      <td>1.207645</td>\n",
       "      <td>957502</td>\n",
       "      <td>2</td>\n",
       "      <td>4.571133</td>\n",
       "      <td>3.555457</td>\n",
       "      <td>12021</td>\n",
       "      <td>0.188685</td>\n",
       "      <td>149602</td>\n",
       "      <td>0.099083</td>\n",
       "      <td>335</td>\n",
       "      <td>0</td>\n",
       "      <td>3043.521948</td>\n",
       "      <td>89.089755</td>\n",
       "      <td>70636327</td>\n",
       "      <td>603.0</td>\n",
       "      <td>34617.239920</td>\n",
       "      <td>6112.218574</td>\n",
       "      <td>20665411</td>\n",
       "      <td>2145422.5</td>\n",
       "      <td>1.391974e+09</td>\n",
       "      <td>4.185284e+07</td>\n",
       "      <td>3.056496e+13</td>\n",
       "      <td>540942274.5</td>\n",
       "      <td>1.972016e+10</td>\n",
       "      <td>5.177442e+09</td>\n",
       "      <td>1.712698e+13</td>\n",
       "      <td>0.050681</td>\n",
       "      <td>40183</td>\n",
       "      <td>0.668441</td>\n",
       "      <td>2260</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>691814</td>\n",
       "      <td>3418</td>\n",
       "      <td>0.056541</td>\n",
       "      <td>0.131408</td>\n",
       "      <td>0.060626</td>\n",
       "      <td>38347.0</td>\n",
       "      <td>0.016110</td>\n",
       "      <td>1.714976</td>\n",
       "      <td>-0.156485</td>\n",
       "      <td>-528.0</td>\n",
       "      <td>-0.001259</td>\n",
       "      <td>3.382706</td>\n",
       "      <td>0.084757</td>\n",
       "      <td>49681.0</td>\n",
       "      <td>0.038956</td>\n",
       "      <td>1.217867</td>\n",
       "      <td>0.206191</td>\n",
       "      <td>676.0</td>\n",
       "      <td>0.383951</td>\n",
       "      <td>0.182785</td>\n",
       "      <td>0.411290</td>\n",
       "      <td>260097.0</td>\n",
       "      <td>0.474122</td>\n",
       "      <td>0.731017</td>\n",
       "      <td>0.509714</td>\n",
       "      <td>1652.0</td>\n",
       "      <td>0.093529</td>\n",
       "      <td>64705</td>\n",
       "      <td>0.106495</td>\n",
       "      <td>364</td>\n",
       "      <td>0.011198</td>\n",
       "      <td>7747</td>\n",
       "      <td>0.009362</td>\n",
       "      <td>32</td>\n",
       "      <td>83277.0</td>\n",
       "      <td>7.621480e+07</td>\n",
       "      <td>2.018727e+06</td>\n",
       "      <td>1.276891e+12</td>\n",
       "      <td>14244000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.136086</td>\n",
       "      <td>0.139149</td>\n",
       "      <td>469.0</td>\n",
       "      <td>0.005701</td>\n",
       "      <td>3944</td>\n",
       "      <td>0.049444</td>\n",
       "      <td>169</td>\n",
       "      <td>1</td>\n",
       "      <td>1.693979</td>\n",
       "      <td>1.202890</td>\n",
       "      <td>832176</td>\n",
       "      <td>2</td>\n",
       "      <td>4.390427</td>\n",
       "      <td>3.420421</td>\n",
       "      <td>11691</td>\n",
       "      <td>0.213186</td>\n",
       "      <td>147485</td>\n",
       "      <td>0.096255</td>\n",
       "      <td>329</td>\n",
       "      <td>0</td>\n",
       "      <td>2877.815320</td>\n",
       "      <td>102.030606</td>\n",
       "      <td>70586202</td>\n",
       "      <td>626.0</td>\n",
       "      <td>34187.257891</td>\n",
       "      <td>6095.829725</td>\n",
       "      <td>20835546</td>\n",
       "      <td>2942721.0</td>\n",
       "      <td>1.624445e+09</td>\n",
       "      <td>5.121388e+07</td>\n",
       "      <td>3.239396e+13</td>\n",
       "      <td>587268000.0</td>\n",
       "      <td>2.127018e+10</td>\n",
       "      <td>5.487047e+09</td>\n",
       "      <td>1.849684e+13</td>\n",
       "      <td>0.061827</td>\n",
       "      <td>42773</td>\n",
       "      <td>0.684026</td>\n",
       "      <td>2338</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019</td>\n",
       "      <td>704829</td>\n",
       "      <td>3441</td>\n",
       "      <td>0.051910</td>\n",
       "      <td>13.790914</td>\n",
       "      <td>0.038715</td>\n",
       "      <td>24956.0</td>\n",
       "      <td>0.013230</td>\n",
       "      <td>190.364971</td>\n",
       "      <td>-3.388381</td>\n",
       "      <td>-11460.0</td>\n",
       "      <td>0.059656</td>\n",
       "      <td>12.341295</td>\n",
       "      <td>0.192362</td>\n",
       "      <td>114483.0</td>\n",
       "      <td>0.070391</td>\n",
       "      <td>2.182397</td>\n",
       "      <td>0.257610</td>\n",
       "      <td>857.0</td>\n",
       "      <td>0.384888</td>\n",
       "      <td>0.174021</td>\n",
       "      <td>0.408350</td>\n",
       "      <td>263179.0</td>\n",
       "      <td>0.476289</td>\n",
       "      <td>0.515008</td>\n",
       "      <td>0.514135</td>\n",
       "      <td>1672.0</td>\n",
       "      <td>0.092747</td>\n",
       "      <td>65371</td>\n",
       "      <td>0.108689</td>\n",
       "      <td>374</td>\n",
       "      <td>0.009842</td>\n",
       "      <td>6937</td>\n",
       "      <td>0.008718</td>\n",
       "      <td>30</td>\n",
       "      <td>79396.0</td>\n",
       "      <td>7.388367e+07</td>\n",
       "      <td>1.982253e+06</td>\n",
       "      <td>1.277808e+12</td>\n",
       "      <td>16779000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.179368</td>\n",
       "      <td>0.145776</td>\n",
       "      <td>495.0</td>\n",
       "      <td>0.005627</td>\n",
       "      <td>3966</td>\n",
       "      <td>0.048242</td>\n",
       "      <td>166</td>\n",
       "      <td>1</td>\n",
       "      <td>1.717206</td>\n",
       "      <td>1.196426</td>\n",
       "      <td>843276</td>\n",
       "      <td>2</td>\n",
       "      <td>4.193864</td>\n",
       "      <td>3.295263</td>\n",
       "      <td>11339</td>\n",
       "      <td>0.209046</td>\n",
       "      <td>147342</td>\n",
       "      <td>0.086893</td>\n",
       "      <td>299</td>\n",
       "      <td>0</td>\n",
       "      <td>2905.762552</td>\n",
       "      <td>102.366235</td>\n",
       "      <td>72150691</td>\n",
       "      <td>661.0</td>\n",
       "      <td>34647.807288</td>\n",
       "      <td>6258.817204</td>\n",
       "      <td>21536590</td>\n",
       "      <td>3022331.5</td>\n",
       "      <td>1.668502e+09</td>\n",
       "      <td>5.261507e+07</td>\n",
       "      <td>3.391694e+13</td>\n",
       "      <td>636080000.0</td>\n",
       "      <td>2.203899e+10</td>\n",
       "      <td>5.707485e+09</td>\n",
       "      <td>1.930842e+13</td>\n",
       "      <td>0.063859</td>\n",
       "      <td>45010</td>\n",
       "      <td>0.688172</td>\n",
       "      <td>2368</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>768990</td>\n",
       "      <td>3499</td>\n",
       "      <td>0.049781</td>\n",
       "      <td>101.344055</td>\n",
       "      <td>-0.068487</td>\n",
       "      <td>-48324.0</td>\n",
       "      <td>0.006942</td>\n",
       "      <td>1492.564696</td>\n",
       "      <td>-26.276336</td>\n",
       "      <td>-85451.0</td>\n",
       "      <td>-0.000332</td>\n",
       "      <td>7.147079</td>\n",
       "      <td>0.072205</td>\n",
       "      <td>46947.0</td>\n",
       "      <td>0.048099</td>\n",
       "      <td>3.249462</td>\n",
       "      <td>0.253800</td>\n",
       "      <td>825.0</td>\n",
       "      <td>0.383925</td>\n",
       "      <td>0.188916</td>\n",
       "      <td>0.408790</td>\n",
       "      <td>288393.0</td>\n",
       "      <td>0.471205</td>\n",
       "      <td>1.059437</td>\n",
       "      <td>0.490434</td>\n",
       "      <td>1539.0</td>\n",
       "      <td>0.094446</td>\n",
       "      <td>72628</td>\n",
       "      <td>0.106888</td>\n",
       "      <td>374</td>\n",
       "      <td>0.008854</td>\n",
       "      <td>6809</td>\n",
       "      <td>0.008288</td>\n",
       "      <td>29</td>\n",
       "      <td>58622.0</td>\n",
       "      <td>6.340204e+07</td>\n",
       "      <td>1.486242e+06</td>\n",
       "      <td>1.048684e+12</td>\n",
       "      <td>13639500.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.179913</td>\n",
       "      <td>0.152761</td>\n",
       "      <td>527.0</td>\n",
       "      <td>0.005376</td>\n",
       "      <td>4134</td>\n",
       "      <td>0.047442</td>\n",
       "      <td>166</td>\n",
       "      <td>1</td>\n",
       "      <td>1.663037</td>\n",
       "      <td>1.191387</td>\n",
       "      <td>916165</td>\n",
       "      <td>2</td>\n",
       "      <td>4.129009</td>\n",
       "      <td>3.241783</td>\n",
       "      <td>11343</td>\n",
       "      <td>0.224137</td>\n",
       "      <td>172359</td>\n",
       "      <td>0.082595</td>\n",
       "      <td>289</td>\n",
       "      <td>0</td>\n",
       "      <td>2808.890203</td>\n",
       "      <td>97.588263</td>\n",
       "      <td>75044398</td>\n",
       "      <td>687.0</td>\n",
       "      <td>34596.169821</td>\n",
       "      <td>6283.825664</td>\n",
       "      <td>21987106</td>\n",
       "      <td>2766445.0</td>\n",
       "      <td>1.488945e+09</td>\n",
       "      <td>4.416201e+07</td>\n",
       "      <td>3.116045e+13</td>\n",
       "      <td>575584000.0</td>\n",
       "      <td>2.104466e+10</td>\n",
       "      <td>5.072033e+09</td>\n",
       "      <td>1.649425e+13</td>\n",
       "      <td>0.064599</td>\n",
       "      <td>49676</td>\n",
       "      <td>0.698199</td>\n",
       "      <td>2443</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 856 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bq_year  ...  bq_company_fgn_address1_cntry\n",
       "5      2015  ...                  United States\n",
       "6      2016  ...                  United States\n",
       "7      2017  ...                  United States\n",
       "8      2018  ...                  United States\n",
       "9      2019  ...                  United States\n",
       "10     2020  ...                  United States\n",
       "\n",
       "[6 rows x 856 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the statistics_by_us_ts data\n",
    "stats_by_us_ts = pd.read_csv(\"/content/drive/MyDrive/BrightQuery_Project/cleaned_data/statistics_by_us_ts.csv\")\n",
    "stats_by_us_ts = stats_by_us_ts[(stats_by_us_ts.bq_year >= 2015) & (stats_by_us_ts.bq_year <= 2020)]\n",
    "stats_by_us_ts = stats_by_us_ts.drop([stats_by_us_ts.columns[0]], axis = 1)\n",
    "stats_by_us_ts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 623
    },
    "id": "5UuwqX-qFaWf",
    "outputId": "ca0c99c0-0488-4bdc-ed53-6b83654891ac"
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Table name</th>\n",
       "      <th>Field description</th>\n",
       "      <th>Field name</th>\n",
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       "      <th>Data type</th>\n",
       "      <th>Category</th>\n",
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       "      <th>Statistic if aggregated</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Asset Turnover U.S. Public Companies Average</td>\n",
       "      <td>bq_asset_turnover_us_pub_avg</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Float</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Average</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Asset Turnover U.S. Public Companies Median</td>\n",
       "      <td>bq_asset_turnover_us_pub_med</td>\n",
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       "      <td>Float</td>\n",
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       "      <td>Median</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Asset Turnover U.S. Public Companies Total</td>\n",
       "      <td>bq_asset_turnover_us_pub_tot</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Integer</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Total</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Cost of Revenue (COR) Per Employee U.S. Public...</td>\n",
       "      <td>bq_cor_per_emp_us_pub_avg</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Float</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Average</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Cost of Revenue (COR) Per Employee U.S. Public...</td>\n",
       "      <td>bq_cor_per_emp_us_pub_med</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Float</td>\n",
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       "      <td>U.S.</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Total Assets Per Employee U.S. Public Companie...</td>\n",
       "      <td>bq_total_assets_per_emp_us_pub_med</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Float</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Median</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Total Assets Per Employee U.S. Public Companie...</td>\n",
       "      <td>bq_total_assets_per_emp_us_pub_tot</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
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       "      <td>Macro, industry &amp; regional metrics</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Total Assets U.S. Public Companies Average</td>\n",
       "      <td>bq_total_assets_us_pub_avg</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Float</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Average</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Total Assets U.S. Public Companies Median</td>\n",
       "      <td>bq_total_assets_us_pub_med</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Float</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Median</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>statistics_by_us_ts</td>\n",
       "      <td>Total Assets U.S. Public Companies Total</td>\n",
       "      <td>bq_total_assets_us_pub_tot</td>\n",
       "      <td>Annual Time Series (TS)</td>\n",
       "      <td>Integer</td>\n",
       "      <td>Macro, industry &amp; regional metrics</td>\n",
       "      <td>U.S.</td>\n",
       "      <td>Total</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Table name  ... Public companies only\n",
       "0    statistics_by_us_ts  ...                  True\n",
       "1    statistics_by_us_ts  ...                  True\n",
       "2    statistics_by_us_ts  ...                  True\n",
       "3    statistics_by_us_ts  ...                  True\n",
       "4    statistics_by_us_ts  ...                  True\n",
       "..                   ...  ...                   ...\n",
       "127  statistics_by_us_ts  ...                  True\n",
       "128  statistics_by_us_ts  ...                  True\n",
       "129  statistics_by_us_ts  ...                  True\n",
       "130  statistics_by_us_ts  ...                  True\n",
       "131  statistics_by_us_ts  ...                  True\n",
       "\n",
       "[132 rows x 9 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "financial_stats_features = pd.read_excel(\"/content/drive/MyDrive/BrightQuery_Project/meta-model/Financial_stats_features.xlsx\")\n",
    "financial_stats_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "pV0If7LDFadM"
   },
   "outputs": [],
   "source": [
    "selected_stats_features = [\"bq_year\"]\n",
    "selected_stats_features.extend(list(financial_stats_features[\"Field name\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 284
    },
    "id": "nMHsxTK8Fako",
    "outputId": "521a246d-d007-4f2e-8206-77250356f116"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_asset_turnover_us_pub_avg</th>\n",
       "      <th>bq_asset_turnover_us_pub_med</th>\n",
       "      <th>bq_asset_turnover_us_pub_tot</th>\n",
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       "      <th>bq_ebitda_margin_us_pub_tot</th>\n",
       "      <th>bq_ebitda_per_emp_us_pub_avg</th>\n",
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       "      <th>bq_ebitda_us_pub_avg</th>\n",
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       "      <th>bq_gross_profit_us_pub_med</th>\n",
       "      <th>bq_gross_profit_us_pub_tot</th>\n",
       "      <th>bq_growth_cor_1yr_us_pub_avg</th>\n",
       "      <th>bq_growth_cor_1yr_us_pub_med</th>\n",
       "      <th>bq_growth_cor_1yr_us_pub_tot</th>\n",
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       "      <th>bq_growth_cor_per_emp_1yr_us_pub_med</th>\n",
       "      <th>bq_growth_cor_per_emp_1yr_us_pub_tot</th>\n",
       "      <th>...</th>\n",
       "      <th>bq_net_income_us_pub_tot</th>\n",
       "      <th>bq_net_profit_margin_us_pub_avg</th>\n",
       "      <th>bq_net_profit_margin_us_pub_med</th>\n",
       "      <th>bq_net_profit_margin_us_pub_tot</th>\n",
       "      <th>bq_operating_expenses_per_emp_us_pub_avg</th>\n",
       "      <th>bq_operating_expenses_per_emp_us_pub_med</th>\n",
       "      <th>bq_operating_expenses_per_emp_us_pub_tot</th>\n",
       "      <th>bq_operating_expenses_us_pub_avg</th>\n",
       "      <th>bq_operating_expenses_us_pub_med</th>\n",
       "      <th>bq_operating_expenses_us_pub_tot</th>\n",
       "      <th>bq_operating_income_per_emp_us_pub_avg</th>\n",
       "      <th>bq_operating_income_per_emp_us_pub_med</th>\n",
       "      <th>bq_operating_income_per_emp_us_pub_tot</th>\n",
       "      <th>bq_operating_income_us_pub_avg</th>\n",
       "      <th>bq_operating_income_us_pub_med</th>\n",
       "      <th>bq_operating_income_us_pub_tot</th>\n",
       "      <th>bq_return_on_assets_us_pub_avg</th>\n",
       "      <th>bq_return_on_assets_us_pub_med</th>\n",
       "      <th>bq_return_on_assets_us_pub_tot</th>\n",
       "      <th>bq_return_on_sales_us_pub_avg</th>\n",
       "      <th>bq_return_on_sales_us_pub_med</th>\n",
       "      <th>bq_return_on_sales_us_pub_tot</th>\n",
       "      <th>bq_revenue_per_emp_us_pub_avg</th>\n",
       "      <th>bq_revenue_per_emp_us_pub_med</th>\n",
       "      <th>bq_revenue_per_emp_us_pub_tot</th>\n",
       "      <th>bq_revenue_us_pub_avg</th>\n",
       "      <th>bq_revenue_us_pub_med</th>\n",
       "      <th>bq_revenue_us_pub_tot</th>\n",
       "      <th>bq_tax_and_interest_per_emp_us_pub_avg</th>\n",
       "      <th>bq_tax_and_interest_per_emp_us_pub_med</th>\n",
       "      <th>bq_tax_and_interest_per_emp_us_pub_tot</th>\n",
       "      <th>bq_tax_and_interest_us_pub_avg</th>\n",
       "      <th>bq_tax_and_interest_us_pub_med</th>\n",
       "      <th>bq_tax_and_interest_us_pub_tot</th>\n",
       "      <th>bq_total_assets_per_emp_us_pub_avg</th>\n",
       "      <th>bq_total_assets_per_emp_us_pub_med</th>\n",
       "      <th>bq_total_assets_per_emp_us_pub_tot</th>\n",
       "      <th>bq_total_assets_us_pub_avg</th>\n",
       "      <th>bq_total_assets_us_pub_med</th>\n",
       "      <th>bq_total_assets_us_pub_tot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015</td>\n",
       "      <td>0.773142</td>\n",
       "      <td>0.557700</td>\n",
       "      <td>2376.0</td>\n",
       "      <td>4.196596e+06</td>\n",
       "      <td>210167.0</td>\n",
       "      <td>1.300525e+10</td>\n",
       "      <td>3.035002e+09</td>\n",
       "      <td>173383000.0</td>\n",
       "      <td>9.405472e+12</td>\n",
       "      <td>-7.437107</td>\n",
       "      <td>0.131016</td>\n",
       "      <td>-22274.0</td>\n",
       "      <td>1.347556e+06</td>\n",
       "      <td>57306.0</td>\n",
       "      <td>4.176077e+09</td>\n",
       "      <td>8.659461e+08</td>\n",
       "      <td>68628000.0</td>\n",
       "      <td>2.683567e+12</td>\n",
       "      <td>6810.496294</td>\n",
       "      <td>734.0</td>\n",
       "      <td>22052387</td>\n",
       "      <td>0.198903</td>\n",
       "      <td>0.035054</td>\n",
       "      <td>626.0</td>\n",
       "      <td>0.489417</td>\n",
       "      <td>0.470292</td>\n",
       "      <td>1466.0</td>\n",
       "      <td>2.817245e+06</td>\n",
       "      <td>212190.0</td>\n",
       "      <td>8.730641e+09</td>\n",
       "      <td>1.938082e+09</td>\n",
       "      <td>223000000.0</td>\n",
       "      <td>6.006116e+12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.106445e+12</td>\n",
       "      <td>-7.970074</td>\n",
       "      <td>0.047914</td>\n",
       "      <td>-23870.0</td>\n",
       "      <td>2.127246e+06</td>\n",
       "      <td>203543.0</td>\n",
       "      <td>6.592337e+09</td>\n",
       "      <td>1.375680e+09</td>\n",
       "      <td>172215000.0</td>\n",
       "      <td>4.263233e+12</td>\n",
       "      <td>6.899980e+05</td>\n",
       "      <td>37726.0</td>\n",
       "      <td>2.138304e+09</td>\n",
       "      <td>5.624015e+08</td>\n",
       "      <td>37600000.0</td>\n",
       "      <td>1.742882e+12</td>\n",
       "      <td>-0.318515</td>\n",
       "      <td>0.016266</td>\n",
       "      <td>-979.0</td>\n",
       "      <td>-7.156144</td>\n",
       "      <td>0.084808</td>\n",
       "      <td>-21433.0</td>\n",
       "      <td>7.013841e+06</td>\n",
       "      <td>467218.0</td>\n",
       "      <td>2.173589e+10</td>\n",
       "      <td>4.973084e+09</td>\n",
       "      <td>524206000.0</td>\n",
       "      <td>1.541159e+13</td>\n",
       "      <td>415248.475637</td>\n",
       "      <td>17962.0</td>\n",
       "      <td>1.286855e+09</td>\n",
       "      <td>2.053684e+08</td>\n",
       "      <td>16982000.0</td>\n",
       "      <td>6.364368e+11</td>\n",
       "      <td>3.046506e+07</td>\n",
       "      <td>1118175.0</td>\n",
       "      <td>9.361914e+10</td>\n",
       "      <td>2.068674e+10</td>\n",
       "      <td>1.141151e+09</td>\n",
       "      <td>6.357034e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016</td>\n",
       "      <td>0.748458</td>\n",
       "      <td>0.552340</td>\n",
       "      <td>2398.0</td>\n",
       "      <td>3.097516e+06</td>\n",
       "      <td>204412.0</td>\n",
       "      <td>9.970902e+09</td>\n",
       "      <td>2.953295e+09</td>\n",
       "      <td>180190000.0</td>\n",
       "      <td>9.506658e+12</td>\n",
       "      <td>-7.636221</td>\n",
       "      <td>0.133884</td>\n",
       "      <td>-23772.0</td>\n",
       "      <td>1.352916e+06</td>\n",
       "      <td>61373.0</td>\n",
       "      <td>4.355037e+09</td>\n",
       "      <td>8.762613e+08</td>\n",
       "      <td>70935000.0</td>\n",
       "      <td>2.820685e+12</td>\n",
       "      <td>6819.845342</td>\n",
       "      <td>750.0</td>\n",
       "      <td>22621427</td>\n",
       "      <td>0.247963</td>\n",
       "      <td>0.028607</td>\n",
       "      <td>798.0</td>\n",
       "      <td>0.513559</td>\n",
       "      <td>0.471860</td>\n",
       "      <td>1599.0</td>\n",
       "      <td>2.659376e+06</td>\n",
       "      <td>214916.0</td>\n",
       "      <td>8.560532e+09</td>\n",
       "      <td>1.923325e+09</td>\n",
       "      <td>223849702.0</td>\n",
       "      <td>6.191184e+12</td>\n",
       "      <td>0.160654</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>493.0</td>\n",
       "      <td>0.156551</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>480.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.157216e+12</td>\n",
       "      <td>-7.870528</td>\n",
       "      <td>0.046738</td>\n",
       "      <td>-24501.0</td>\n",
       "      <td>1.889376e+06</td>\n",
       "      <td>205423.0</td>\n",
       "      <td>6.081901e+09</td>\n",
       "      <td>1.353307e+09</td>\n",
       "      <td>173639000.0</td>\n",
       "      <td>4.356296e+12</td>\n",
       "      <td>7.699999e+05</td>\n",
       "      <td>36612.0</td>\n",
       "      <td>2.478630e+09</td>\n",
       "      <td>5.700181e+08</td>\n",
       "      <td>39795000.0</td>\n",
       "      <td>1.834888e+12</td>\n",
       "      <td>-0.167882</td>\n",
       "      <td>0.013697</td>\n",
       "      <td>-538.0</td>\n",
       "      <td>-8.183579</td>\n",
       "      <td>0.081509</td>\n",
       "      <td>-25475.0</td>\n",
       "      <td>5.756892e+06</td>\n",
       "      <td>466867.0</td>\n",
       "      <td>1.853144e+10</td>\n",
       "      <td>4.876621e+09</td>\n",
       "      <td>515874256.0</td>\n",
       "      <td>1.569784e+13</td>\n",
       "      <td>412611.987263</td>\n",
       "      <td>18300.0</td>\n",
       "      <td>1.328198e+09</td>\n",
       "      <td>2.105225e+08</td>\n",
       "      <td>17638000.0</td>\n",
       "      <td>6.776720e+11</td>\n",
       "      <td>3.118176e+07</td>\n",
       "      <td>1117930.0</td>\n",
       "      <td>9.990637e+10</td>\n",
       "      <td>2.089271e+10</td>\n",
       "      <td>1.185226e+09</td>\n",
       "      <td>6.694026e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017</td>\n",
       "      <td>0.732187</td>\n",
       "      <td>0.544263</td>\n",
       "      <td>2415.0</td>\n",
       "      <td>7.238976e+06</td>\n",
       "      <td>206057.0</td>\n",
       "      <td>2.394653e+10</td>\n",
       "      <td>3.140450e+09</td>\n",
       "      <td>185935000.0</td>\n",
       "      <td>1.038861e+13</td>\n",
       "      <td>-10.788804</td>\n",
       "      <td>0.134271</td>\n",
       "      <td>-34362.0</td>\n",
       "      <td>1.454042e+06</td>\n",
       "      <td>63952.0</td>\n",
       "      <td>4.808517e+09</td>\n",
       "      <td>9.500557e+08</td>\n",
       "      <td>79985000.0</td>\n",
       "      <td>3.141834e+12</td>\n",
       "      <td>6850.340728</td>\n",
       "      <td>763.0</td>\n",
       "      <td>23161002</td>\n",
       "      <td>0.129847</td>\n",
       "      <td>0.021322</td>\n",
       "      <td>428.0</td>\n",
       "      <td>0.502606</td>\n",
       "      <td>0.476610</td>\n",
       "      <td>1601.0</td>\n",
       "      <td>3.292683e+06</td>\n",
       "      <td>226790.5</td>\n",
       "      <td>1.089219e+10</td>\n",
       "      <td>2.036992e+09</td>\n",
       "      <td>242232000.0</td>\n",
       "      <td>6.738369e+12</td>\n",
       "      <td>0.338785</td>\n",
       "      <td>0.039522</td>\n",
       "      <td>1079.0</td>\n",
       "      <td>0.344669</td>\n",
       "      <td>0.002749</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.353414e+12</td>\n",
       "      <td>-11.224530</td>\n",
       "      <td>0.050740</td>\n",
       "      <td>-35761.0</td>\n",
       "      <td>2.581310e+06</td>\n",
       "      <td>221586.5</td>\n",
       "      <td>8.538972e+09</td>\n",
       "      <td>1.402129e+09</td>\n",
       "      <td>184107000.0</td>\n",
       "      <td>4.638244e+12</td>\n",
       "      <td>7.113728e+05</td>\n",
       "      <td>38939.5</td>\n",
       "      <td>2.353221e+09</td>\n",
       "      <td>6.348625e+08</td>\n",
       "      <td>43845000.0</td>\n",
       "      <td>2.100125e+12</td>\n",
       "      <td>-0.108298</td>\n",
       "      <td>0.015189</td>\n",
       "      <td>-357.0</td>\n",
       "      <td>-11.410108</td>\n",
       "      <td>0.081647</td>\n",
       "      <td>-36353.0</td>\n",
       "      <td>1.053166e+07</td>\n",
       "      <td>487630.0</td>\n",
       "      <td>3.483873e+10</td>\n",
       "      <td>5.177442e+09</td>\n",
       "      <td>540942274.5</td>\n",
       "      <td>1.712698e+13</td>\n",
       "      <td>323431.850967</td>\n",
       "      <td>17291.5</td>\n",
       "      <td>1.069913e+09</td>\n",
       "      <td>2.257290e+08</td>\n",
       "      <td>12906000.0</td>\n",
       "      <td>7.467114e+11</td>\n",
       "      <td>3.422425e+07</td>\n",
       "      <td>1215090.0</td>\n",
       "      <td>1.128716e+11</td>\n",
       "      <td>2.123642e+10</td>\n",
       "      <td>1.241164e+09</td>\n",
       "      <td>7.003772e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>0.746688</td>\n",
       "      <td>0.553660</td>\n",
       "      <td>2517.0</td>\n",
       "      <td>4.897908e+06</td>\n",
       "      <td>220317.0</td>\n",
       "      <td>1.651085e+10</td>\n",
       "      <td>3.344265e+09</td>\n",
       "      <td>194470000.0</td>\n",
       "      <td>1.127352e+13</td>\n",
       "      <td>-2.265178</td>\n",
       "      <td>0.136128</td>\n",
       "      <td>-7341.0</td>\n",
       "      <td>1.600800e+06</td>\n",
       "      <td>66985.0</td>\n",
       "      <td>5.394694e+09</td>\n",
       "      <td>1.013351e+09</td>\n",
       "      <td>83474500.0</td>\n",
       "      <td>3.414994e+12</td>\n",
       "      <td>6928.751317</td>\n",
       "      <td>795.5</td>\n",
       "      <td>23682472</td>\n",
       "      <td>0.173114</td>\n",
       "      <td>0.026814</td>\n",
       "      <td>584.0</td>\n",
       "      <td>0.509714</td>\n",
       "      <td>0.474122</td>\n",
       "      <td>1652.0</td>\n",
       "      <td>3.336029e+06</td>\n",
       "      <td>235172.0</td>\n",
       "      <td>1.124576e+10</td>\n",
       "      <td>2.142782e+09</td>\n",
       "      <td>266934000.0</td>\n",
       "      <td>7.223317e+12</td>\n",
       "      <td>1.186279</td>\n",
       "      <td>0.047246</td>\n",
       "      <td>3898.0</td>\n",
       "      <td>0.932580</td>\n",
       "      <td>0.006309</td>\n",
       "      <td>3064.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.617513e+12</td>\n",
       "      <td>-2.508816</td>\n",
       "      <td>0.054940</td>\n",
       "      <td>-8131.0</td>\n",
       "      <td>2.318791e+06</td>\n",
       "      <td>230060.0</td>\n",
       "      <td>7.816644e+09</td>\n",
       "      <td>1.472792e+09</td>\n",
       "      <td>197554000.0</td>\n",
       "      <td>4.964782e+12</td>\n",
       "      <td>1.017239e+06</td>\n",
       "      <td>38457.0</td>\n",
       "      <td>3.429111e+09</td>\n",
       "      <td>6.699897e+08</td>\n",
       "      <td>46174000.0</td>\n",
       "      <td>2.258535e+12</td>\n",
       "      <td>-0.156485</td>\n",
       "      <td>0.016110</td>\n",
       "      <td>-528.0</td>\n",
       "      <td>-2.886054</td>\n",
       "      <td>0.080216</td>\n",
       "      <td>-9354.0</td>\n",
       "      <td>8.233938e+06</td>\n",
       "      <td>511164.0</td>\n",
       "      <td>2.775660e+10</td>\n",
       "      <td>5.487047e+09</td>\n",
       "      <td>587268000.0</td>\n",
       "      <td>1.849684e+13</td>\n",
       "      <td>504995.980718</td>\n",
       "      <td>15091.0</td>\n",
       "      <td>1.702341e+09</td>\n",
       "      <td>1.901578e+08</td>\n",
       "      <td>14244000.0</td>\n",
       "      <td>6.410218e+11</td>\n",
       "      <td>3.411456e+07</td>\n",
       "      <td>1245173.0</td>\n",
       "      <td>1.150002e+11</td>\n",
       "      <td>2.126117e+10</td>\n",
       "      <td>1.342401e+09</td>\n",
       "      <td>7.167139e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019</td>\n",
       "      <td>0.688508</td>\n",
       "      <td>0.514972</td>\n",
       "      <td>2329.0</td>\n",
       "      <td>4.501345e+06</td>\n",
       "      <td>223562.0</td>\n",
       "      <td>1.522805e+10</td>\n",
       "      <td>3.493262e+09</td>\n",
       "      <td>212212172.0</td>\n",
       "      <td>1.181771e+13</td>\n",
       "      <td>-5.295241</td>\n",
       "      <td>0.129426</td>\n",
       "      <td>-17220.0</td>\n",
       "      <td>1.491730e+06</td>\n",
       "      <td>64835.0</td>\n",
       "      <td>5.043539e+09</td>\n",
       "      <td>1.025820e+09</td>\n",
       "      <td>79731000.0</td>\n",
       "      <td>3.468298e+12</td>\n",
       "      <td>7084.275501</td>\n",
       "      <td>848.0</td>\n",
       "      <td>24376992</td>\n",
       "      <td>0.237949</td>\n",
       "      <td>0.032761</td>\n",
       "      <td>807.0</td>\n",
       "      <td>0.514135</td>\n",
       "      <td>0.476289</td>\n",
       "      <td>1672.0</td>\n",
       "      <td>2.910865e+06</td>\n",
       "      <td>242302.0</td>\n",
       "      <td>9.847457e+09</td>\n",
       "      <td>2.214223e+09</td>\n",
       "      <td>281935000.0</td>\n",
       "      <td>7.490716e+12</td>\n",
       "      <td>0.175205</td>\n",
       "      <td>0.000167</td>\n",
       "      <td>583.0</td>\n",
       "      <td>0.316253</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.558866e+12</td>\n",
       "      <td>-5.842247</td>\n",
       "      <td>0.046945</td>\n",
       "      <td>-19005.0</td>\n",
       "      <td>2.177330e+06</td>\n",
       "      <td>237800.0</td>\n",
       "      <td>7.365908e+09</td>\n",
       "      <td>1.566340e+09</td>\n",
       "      <td>214558000.0</td>\n",
       "      <td>5.298929e+12</td>\n",
       "      <td>7.335348e+05</td>\n",
       "      <td>37547.0</td>\n",
       "      <td>2.481548e+09</td>\n",
       "      <td>6.478827e+08</td>\n",
       "      <td>41850000.0</td>\n",
       "      <td>2.191787e+12</td>\n",
       "      <td>-3.388381</td>\n",
       "      <td>0.013230</td>\n",
       "      <td>-11460.0</td>\n",
       "      <td>-5.772873</td>\n",
       "      <td>0.077984</td>\n",
       "      <td>-18779.0</td>\n",
       "      <td>7.412211e+06</td>\n",
       "      <td>521794.0</td>\n",
       "      <td>2.507551e+10</td>\n",
       "      <td>5.707485e+09</td>\n",
       "      <td>636080000.0</td>\n",
       "      <td>1.930842e+13</td>\n",
       "      <td>301104.436299</td>\n",
       "      <td>15160.0</td>\n",
       "      <td>1.018636e+09</td>\n",
       "      <td>1.870887e+08</td>\n",
       "      <td>16779000.0</td>\n",
       "      <td>6.329209e+11</td>\n",
       "      <td>3.445747e+07</td>\n",
       "      <td>1285071.0</td>\n",
       "      <td>1.165696e+11</td>\n",
       "      <td>2.265227e+10</td>\n",
       "      <td>1.514589e+09</td>\n",
       "      <td>7.663264e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>0.624325</td>\n",
       "      <td>0.473990</td>\n",
       "      <td>2030.0</td>\n",
       "      <td>2.669936e+06</td>\n",
       "      <td>205898.5</td>\n",
       "      <td>8.682630e+09</td>\n",
       "      <td>3.132414e+09</td>\n",
       "      <td>212335500.0</td>\n",
       "      <td>1.018661e+13</td>\n",
       "      <td>-12.763364</td>\n",
       "      <td>0.106555</td>\n",
       "      <td>-40026.0</td>\n",
       "      <td>4.782803e+05</td>\n",
       "      <td>46644.0</td>\n",
       "      <td>1.552976e+09</td>\n",
       "      <td>7.761998e+08</td>\n",
       "      <td>50078000.0</td>\n",
       "      <td>2.520321e+12</td>\n",
       "      <td>7158.000572</td>\n",
       "      <td>874.0</td>\n",
       "      <td>25045844</td>\n",
       "      <td>0.103040</td>\n",
       "      <td>0.018295</td>\n",
       "      <td>355.0</td>\n",
       "      <td>0.490434</td>\n",
       "      <td>0.471205</td>\n",
       "      <td>1539.0</td>\n",
       "      <td>1.366493e+06</td>\n",
       "      <td>219670.0</td>\n",
       "      <td>4.443837e+09</td>\n",
       "      <td>1.939619e+09</td>\n",
       "      <td>250688500.0</td>\n",
       "      <td>6.307642e+12</td>\n",
       "      <td>0.080415</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>258.0</td>\n",
       "      <td>0.126172</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>405.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.681404e+11</td>\n",
       "      <td>-14.124768</td>\n",
       "      <td>0.027342</td>\n",
       "      <td>-44338.0</td>\n",
       "      <td>1.187971e+06</td>\n",
       "      <td>226674.5</td>\n",
       "      <td>3.863281e+09</td>\n",
       "      <td>1.488933e+09</td>\n",
       "      <td>224067000.0</td>\n",
       "      <td>4.842011e+12</td>\n",
       "      <td>1.785226e+05</td>\n",
       "      <td>20277.5</td>\n",
       "      <td>5.805554e+08</td>\n",
       "      <td>4.506860e+08</td>\n",
       "      <td>19351500.0</td>\n",
       "      <td>1.465631e+12</td>\n",
       "      <td>-26.276336</td>\n",
       "      <td>0.006942</td>\n",
       "      <td>-85451.0</td>\n",
       "      <td>-5.869267</td>\n",
       "      <td>0.052160</td>\n",
       "      <td>-18424.0</td>\n",
       "      <td>4.036429e+06</td>\n",
       "      <td>466071.0</td>\n",
       "      <td>1.312647e+10</td>\n",
       "      <td>5.072033e+09</td>\n",
       "      <td>575584000.0</td>\n",
       "      <td>1.649425e+13</td>\n",
       "      <td>162315.316113</td>\n",
       "      <td>13741.0</td>\n",
       "      <td>5.278494e+08</td>\n",
       "      <td>1.529798e+08</td>\n",
       "      <td>13639500.0</td>\n",
       "      <td>4.974904e+11</td>\n",
       "      <td>2.061630e+07</td>\n",
       "      <td>1315262.0</td>\n",
       "      <td>6.813688e+10</td>\n",
       "      <td>1.866807e+10</td>\n",
       "      <td>1.558178e+09</td>\n",
       "      <td>6.169798e+13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 133 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bq_year  ...  bq_total_assets_us_pub_tot\n",
       "5      2015  ...                6.357034e+13\n",
       "6      2016  ...                6.694026e+13\n",
       "7      2017  ...                7.003772e+13\n",
       "8      2018  ...                7.167139e+13\n",
       "9      2019  ...                7.663264e+13\n",
       "10     2020  ...                6.169798e+13\n",
       "\n",
       "[6 rows x 133 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats_by_us_df = feature_selection(stats_by_us_ts, selected_stats_features)\n",
    "stats_by_us_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 235
    },
    "id": "csIsvF9qHXZT",
    "outputId": "dbdbdf34-916b-4844-b431-21dc50eb98cf"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_year</th>\n",
       "      <th>bq_ebitda_us_pub_tot</th>\n",
       "      <th>bq_gross_profit_us_pub_tot</th>\n",
       "      <th>bq_operating_income_us_pub_tot</th>\n",
       "      <th>bq_net_income_us_pub_tot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015</td>\n",
       "      <td>2.683567e+12</td>\n",
       "      <td>6.006116e+12</td>\n",
       "      <td>1.742882e+12</td>\n",
       "      <td>1.106445e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016</td>\n",
       "      <td>2.820685e+12</td>\n",
       "      <td>6.191184e+12</td>\n",
       "      <td>1.834888e+12</td>\n",
       "      <td>1.157216e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017</td>\n",
       "      <td>3.141834e+12</td>\n",
       "      <td>6.738369e+12</td>\n",
       "      <td>2.100125e+12</td>\n",
       "      <td>1.353414e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>3.414994e+12</td>\n",
       "      <td>7.223317e+12</td>\n",
       "      <td>2.258535e+12</td>\n",
       "      <td>1.617513e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019</td>\n",
       "      <td>3.468298e+12</td>\n",
       "      <td>7.490716e+12</td>\n",
       "      <td>2.191787e+12</td>\n",
       "      <td>1.558866e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>2.520321e+12</td>\n",
       "      <td>6.307642e+12</td>\n",
       "      <td>1.465631e+12</td>\n",
       "      <td>9.681404e+11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    bq_year  ...  bq_net_income_us_pub_tot\n",
       "5      2015  ...              1.106445e+12\n",
       "6      2016  ...              1.157216e+12\n",
       "7      2017  ...              1.353414e+12\n",
       "8      2018  ...              1.617513e+12\n",
       "9      2019  ...              1.558866e+12\n",
       "10     2020  ...              9.681404e+11\n",
       "\n",
       "[6 rows x 5 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_features = ['bq_year','bq_ebitda_us_pub_tot',\n",
    "'bq_gross_profit_us_pub_tot',\n",
    "'bq_operating_income_us_pub_tot',\n",
    "'bq_net_income_us_pub_tot']\n",
    "\n",
    "stats_df = feature_selection(stats_by_us_df, plot_features)\n",
    "stats_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 235
    },
    "id": "raQ-B7sQHXkP",
    "outputId": "d174c674-6026-42ea-c6f2-672728fb2657"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bq_ebitda_us_pub_tot</th>\n",
       "      <th>bq_gross_profit_us_pub_tot</th>\n",
       "      <th>bq_operating_income_us_pub_tot</th>\n",
       "      <th>bq_net_income_us_pub_tot</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.683567</td>\n",
       "      <td>6.006116</td>\n",
       "      <td>1.742882</td>\n",
       "      <td>1.106445</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.820685</td>\n",
       "      <td>6.191184</td>\n",
       "      <td>1.834888</td>\n",
       "      <td>1.157216</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.141834</td>\n",
       "      <td>6.738369</td>\n",
       "      <td>2.100125</td>\n",
       "      <td>1.353414</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3.414994</td>\n",
       "      <td>7.223317</td>\n",
       "      <td>2.258535</td>\n",
       "      <td>1.617513</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3.468298</td>\n",
       "      <td>7.490716</td>\n",
       "      <td>2.191787</td>\n",
       "      <td>1.558866</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.520321</td>\n",
       "      <td>6.307642</td>\n",
       "      <td>1.465631</td>\n",
       "      <td>0.968140</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    bq_ebitda_us_pub_tot  ...  YEAR\n",
       "5               2.683567  ...  2015\n",
       "6               2.820685  ...  2016\n",
       "7               3.141834  ...  2017\n",
       "8               3.414994  ...  2018\n",
       "9               3.468298  ...  2019\n",
       "10              2.520321  ...  2020\n",
       "\n",
       "[6 rows x 5 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trillion = 10**12\n",
    "df_lines = stats_df[['bq_ebitda_us_pub_tot',\n",
    "'bq_gross_profit_us_pub_tot',\n",
    "'bq_operating_income_us_pub_tot',\n",
    "'bq_net_income_us_pub_tot']]/trillion\n",
    "\n",
    "df_lines[\"YEAR\"] = stats_df[\"bq_year\"]\n",
    "\n",
    "df_lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 574
    },
    "id": "wRAi0hr8L9DO",
    "outputId": "2b39bab7-8665-4d92-b84c-2e84cb236947"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(10, 8))\n",
    "fig.suptitle(\"Aggregation of Statistics in U.S. Public Companies\",fontsize=20, x=0.47,\n",
    "y=1.00, fontweight =\"bold\")\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"bq_ebitda_us_pub_tot\"], color =\n",
    "\"dodgerblue\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"bq_gross_profit_us_pub_tot\"], color =\n",
    "\"red\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"bq_operating_income_us_pub_tot\"], color = \"purple\", lw = 2)\n",
    "ax.plot(df_lines[\"YEAR\"], df_lines[\"bq_net_income_us_pub_tot\"], color = \"green\", lw = 2)\n",
    "#ax.set_title(\"Totals In Trillion, by year\", loc='left', fontsize=18)\n",
    "ax.grid()\n",
    "ax.set_facecolor('#F2F2F2')\n",
    "ax.annotate(\"Ebitda\", xy=(2016,3.1), color=\"dodgerblue\" , fontsize=14)\n",
    "ax.annotate(\"Gross Profit\", xy=(2015, 6.25), color=\"red\", fontsize=14)\n",
    "ax.annotate(\"Operating Income\", xy=(2017,2.4), color=\"purple\", fontsize=14) \n",
    "ax.annotate(\"Net Income\", xy=(2018, 1.7), color=\"green\", fontsize=14)\n",
    "ax.set(xlim=(2015, 2020.5), ylim=(-0.1, 8))\n",
    "ax.set_xlabel(\"Year\",fontsize=16)\n",
    "ax.set_ylabel(\"Total Values in Trillions of Dollars\",fontsize=16)\n",
    "ax.tick_params(labelsize=13)\n",
    "ax.set_frame_on(False)"
   ]
  }
 ],
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