UdA - Correlation Matrix.ipynb

uda-correlation-matrix.ipynb

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      "source": [
        "# UDA Professor Joan-Marc Fisa Gol\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "data = {'REB':\t[9,\t6,\t11,\t7,\t3,\t2,\t2,\t5,\t4,\t0,\t6,\t14,\t3,\t7,\t2,\t8,\t0,\t0,\t7,\t1],\n",
        "         'AST':\t[3,\t2,\t0,\t7,\t2,\t4,\t0,\t0,\t2,\t0,\t8,\t5,\t1,\t0,\t2,\t0,\t3,\t1,\t1,\t0],\n",
        "         'STL':\t[2,\t0,\t1,\t0,\t1,\t1,\t1,\t0,\t0,\t1,\t0,\t1,\t1,\t1,\t1,\t0,\t0,\t0,\t3,\t0],\n",
        "         'BLK':\t[0,\t0,\t2,\t1,\t0,\t0,\t0,\t0,\t0,\t0,\t0,\t4,\t1,\t0,\t0,\t0,\t0,\t0,\t0,\t0],\n",
        "         'PTS':\t[25,\t8,\t15,\t16,\t5,\t14,\t2,\t11,\t4,\t0,\t19,\t36,\t10,\t11,\t6,\t7,\t2,\t5,\t9,\t0]\n",
        "         }\n",
        "\n",
        "df = pd.DataFrame(data)\n",
        "\n",
        "corr_matrix = df.corr()\n",
        "corr_matrix"
      ],
      "execution_count": null,
      "outputs": [
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              "          REB       AST       STL       BLK       PTS\n",
              "REB  1.000000  0.248223  0.257187  0.675054  0.812710\n",
              "AST  0.248223  1.000000 -0.157799  0.258695  0.575392\n",
              "STL  0.257187 -0.157799  1.000000  0.092442  0.239947\n",
              "BLK  0.675054  0.258695  0.092442  1.000000  0.701803\n",
              "PTS  0.812710  0.575392  0.239947  0.701803  1.000000"
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              "summary": "{\n  \"name\": \"corr_matrix\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"REB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3362055211595806,\n        \"min\": 0.2482234170220413,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.2482234170220413,\n          0.8127097863395851,\n          0.25718721529979216\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AST\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.43120919105242034,\n        \"min\": -0.15779910871293637,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1.0,\n          0.5753915703591082,\n          -0.15779910871293637\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"STL\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.432194622797293,\n        \"min\": -0.15779910871293637,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          -0.15779910871293637,\n          0.2399471663270931,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BLK\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.365822211210099,\n        \"min\": 0.09244197078723257,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.25869537842277696,\n          0.7018030680912354,\n          0.09244197078723257\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PTS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2846456223491831,\n        \"min\": 0.2399471663270931,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.5753915703591082,\n          1.0,\n          0.2399471663270931\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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        "id": "2Do2wHxrbq10",
        "outputId": "1466e4d9-11ab-4e70-8404-8681840d02ca"
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      "source": [
        "import seaborn as sns\n",
        "plt.figure(figsize=(8,6))\n",
        "ax = sns.heatmap(corr_matrix, annot=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 528
        },
        "id": "vrHV6l6Adovg",
        "outputId": "b17f161c-9ee3-42ff-d7fa-0f2d005469e8"
      },
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "ax = sns.heatmap(corr_matrix, cmap=\"YlGnBu\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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WeTwezZkzx+/2IwAAACFnSLMVKgEncSkpKWrevLm++eYbTZgwQVu2bPE9vQEAAACnV8BJ3CeffKK///3vGjx4MM9IBQAA4WfITXlDJeAk7osvvtCePXvUvn17JSQk6OWXX9b27dtDWRsAAACOI+Am7vLLL9ekSZP022+/6d5779X06dPVsGFDlZaWauHChdqzZ08o6wQAAPDnCuFiANtlRkdH684779QXX3yhb7/9Vv/4xz/09NNPq169erruuutCUSMAAAD+okK9ZvPmzTVu3Dj98ssveu+994JVEwAAwMmF4sH3RxcDBCUwjIiIUJ8+ffThhx8GY3cAAAA4CVv3iQMAAKg0HH6fOJo4AABgJoc3cYbMvwAAAKi8srOzFR8fr6ioKCUkJGjFihUn3H7Xrl0aMmSIGjRoILfbrWbNmmnevHm2jkkSBwAAjOStJBMQZsyYofT0dE2cOFEJCQmaMGGCkpOT9f3336tevXplti8uLlaPHj1Ur149ffDBB2rUqJE2b96smjVr2jouTRwAAEAFjB8/XoMGDVJaWpokaeLEiZo7d65ycnI0cuTIMtvn5ORox44dWrZsmapWrSpJio+Pt31chlMBAICZQnizX4/Ho6KiIr/F4/GUKaG4uFirVq1SUlLSn2W5XEpKStLy5cvLLfvDDz9UYmKihgwZori4OF1yySUaO3asSkpKbJ8+AAAAjpGVlaXY2Fi/JSsrq8x227dvV0lJieLi4vzWx8XFqaCgoNx9b9iwQR988IFKSko0b948Pfroo3ruuef05JNP2qqR4VQAAGCmEF4Tl5GRofT0dL91brc7KPsuLS1VvXr19PrrrysiIkLt27fXr7/+qn/961/KzMwMeD80cQAAAH/hdrsDatrq1KmjiIgIFRYW+q0vLCxU/fr1y/1MgwYNVLVqVUVERPjWXXTRRSooKFBxcbEiIyMDqpHhVAAAYCaXFbolQJGRkWrfvr1yc3N960pLS5Wbm6vExMRyP9OpUyf99NNPKi0t9a374Ycf1KBBg4AbOIkmDgAAoELS09M1adIkvfnmm/rvf/+rwYMHa9++fb7ZqgMGDFBGRoZv+8GDB2vHjh0aNmyYfvjhB82dO1djx47VkCFDbB2X4VQAAGCmSvLEhr59+2rbtm0aPXq0CgoK1LZtW82fP9832SE/P18u15+5WePGjbVgwQINHz5crVu3VqNGjTRs2DA99NBDto5LEwcAAMxUOXo4SdLQoUM1dOjQct9bvHhxmXWJiYn68ssvK3RMhlMBAAAMRBIHAACM5K0kw6nhQhIHAABgIJI4AABgphDe7NcEJHEAAAAGIokDAABm4po4AAAAmIYkDgAAmMnZQRxNHAAAMJPL4eOJDj99AAAAM5HEAQAAIzn8DiMkcQAAACYiiQMAAEYiiQMAAIBxSOIAAICRLIdHcSRxAAAABiKJAwAARnJ4EEcTBwAAzEQTV0kcKg13BTjqQP6YcJeAI6o1yQx3CTji33m3h7sEHCO6pzfcJQBhV2maOAAAADssh1/Z7/DTBwAAMBNJHAAAMJLTr4kjiQMAADAQSRwAADCSiyQOAAAApiGJAwAARnL6NXE0cQAAwEhOb+IYTgUAADAQSRwAADCS5fAojiQOAADAQCRxAADASDx2CwAAAMYhiQMAAEZy+CVxJHEAAAAmIokDAABGcnoSRxMHAACM5PQmjuFUAAAAA5HEAQAAI7lI4gAAAGAakjgAAGAkrokDAACAcUjiAACAkUjiAAAAYBySOAAAYCTL4dNTaeIAAICRGE4FAACAcUjiAACAkUjiAAAAYBySOAAAYCSSOAAAABiHJA4AABjJ4XcYIYkDAAAwEUkcAAAwktOviaOJAwAARrIcPp4Y1NNft26dmjVrFsxdAgAAoBxBTeI8Ho/Wr18fzF0CAACUy+nDqQ4PIgEAAMzENXEAAMBIlsOjOJI4AAAAA9lK4mrVqnXCrvfw4cMVLggAACAQDg/i7DVxEyZMCFEZAAAAsMNWE9e0aVNdccUVqlKFS+kAAEB4OT2Js3VNXLdu3bRjx45Q1QIAABAwywrdYgJbkZrX6w3KQT0ejzwej9+6w8XFqhIZGZT9AwAAnOlsz04NxnTerKwsxcbG+i2LJk+v8H4BAIBzuKzQLSawfXHbwIED5Xa7T7jNrFmzTvh+RkaG0tPT/da9/MPndksBAABwLNtNXI0aNVStWrUKHdTtdpdpBBlKBQAAdpiSmIWK7SbuxRdfVL169UJRCwAAAAJk65o4pz/eAgAAVB4uyxuyxa7s7GzFx8crKipKCQkJWrFiRUCfmz59uizLUp8+fWwf01YTF6zZqQAAAGeKGTNmKD09XZmZmVq9erXatGmj5ORkbd269YSf27Rpk/75z3+qc+fOp3RcW03ck08+WaazfOutt9S0aVPVq1dP99xzT5lbhwAAAIRCZZmdOn78eA0aNEhpaWlq2bKlJk6cqOrVqysnJ+e4nykpKdHtt9+uMWPG6Lzzzju187ez8dKlS7V27Vrf62+//VZ33XWXkpKSNHLkSH300UfKyso6pUIAAADscIVwCVRxcbFWrVqlpKSkP+tyuZSUlKTly5cf93OPP/646tWrp7vuusvG0fzZmtjw9ddf68knn/S9nj59uhISEjRp0iRJUuPGjZWZmanHHnvslAsCAAAIt/IeTFDe3TW2b9+ukpISxcXF+a2Pi4vTunXryt33F198ocmTJysvL69CNdpK4nbu3OlX5JIlS3TNNdf4Xl922WX6+eefK1QQAABAIEI5saG8BxMEY7Rxz549uuOOOzRp0iTVqVOnQvuylcTFxcVp48aNaty4sYqLi7V69WqNGTPGr7CqVatWqCAAAIBwK+/BBOU97KBOnTqKiIhQYWGh3/rCwkLVr1+/zPbr16/Xpk2blJKS4ltXWloqSapSpYq+//57nX/++QHVaKuJ69Wrl0aOHKlnnnlGc+bMUfXq1f1mVHzzzTcBHxgAAKAiQnmz3/KGTssTGRmp9u3bKzc313ebkNLSUuXm5mro0KFltm/RooW+/fZbv3WjRo3Snj179MILL6hx48YB12iriXviiSf0P//zP+rSpYtiYmL05ptvKvKYJy3k5OTo6quvtrNLAAAAo6Wnpys1NVUdOnRQx44dNWHCBO3bt09paWmSpAEDBqhRo0bKyspSVFSULrnkEr/P16xZU5LKrD8ZW01cnTp1tHTpUu3evVsxMTGKiIjwe3/mzJmKiYmxVQAAAMCpsHVhfwj17dtX27Zt0+jRo1VQUKC2bdtq/vz5vnkE+fn5crmCX63tx25JUmxsbLnra9euXaFiAAAATDR06NByh08lafHixSf87NSpU0/pmKfUxAEAAIRbKK+JM0FlSSIBAABgA0kcAAAwknUKD6o/k9DEAQAAIzGcCgAAAOOQxAEAACM5PYly+vkDAAAYiSQOAAAYyeXwiQ0kcQAAAAYiiQMAAEZidioAAACMQxIHAACM5PQkiiYOAAAYieFUAAAAGIckDgAAGIlbjAAAAMA4JHEAAMBIXBMHAAAA45DEAQAAIzk9iXL6+QMAABiJJA4AABjJ6bNTaeIAAICRmNgAAAAA45DEAQAAI5HEAQAAwDgkcQAAwEhOT6Kcfv4AAABGIokDAABGcvotRkjiAAAADEQSBwAAjOT02ak0cQAAwEhOH06sNE3cxNf2hLsEHFF6z+Zwl4Aj/p13e7hLwBEJbaeFuwQco+FVN4S7BBxx/5RwV+BclaaJAwAAsMPpw6lOTyIBAACMRBIHAACMZHGLEQAAAJiGJA4AABiJa+IAAABgHJI4AABgJKcnUTRxAADASDw7FQAAAMYhiQMAAEZiYgMAAACMQxIHAACMRBIHAAAA45DEAQAAI0WEu4AwI4kDAAAwEEkcAAAwktPvE0cTBwAAjMTEBgAAABiHJA4AABiJJA4AAADGIYkDAABGiiCJAwAAgGlI4gAAgJG4Jg4AAADGIYkDAABG4ma/AAAABmI4FQAAAMYhiQMAAEaKCHcBYUYSBwAAYCCSOAAAYCSuiQMAAIBxSOIAAICRnH6LEZI4AAAAA5HEAQAAI0U4/Jo4mjgAAGAkJjbYsGfPnpNus2TJklMuBgAAAIGx1cSlpKTI4/Ec9/0lS5bo2muvrXBRAAAAJ+OyQreYwFYT9/vvv+uWW25RaWlpmfeWLl2q3r17a+DAgcGqDQAAwAjZ2dmKj49XVFSUEhIStGLFiuNuO2nSJHXu3Fm1atVSrVq1lJSUdMLtj8dWE7dgwQKtWbOmTKP2+eef69prr1Vqaqpeeukl20UAAADYVVmSuBkzZig9PV2ZmZlavXq12rRpo+TkZG3durXc7RcvXqx+/fpp0aJFWr58uRo3bqyrr75av/76q73zt7Nxw4YN9emnn+qzzz7TsGHDJElffPGFevXqpdtuu03Z2dm2Dg4AAGC68ePHa9CgQUpLS1PLli01ceJEVa9eXTk5OeVuP23aNP3tb39T27Zt1aJFC73xxhsqLS1Vbm6urePanp16/vnna/78+eratat2796t2bNnq1+/fpo4caLdXQEAAJyyiEpws9/i4mKtWrVKGRkZvnUul0tJSUlavnx5QPvYv3+/Dh06pNq1a9s6tq0mrqioSJIUHx+vadOm6YYbblCfPn30r3/9y/eeJJ111lm2igAAAKhMPB5Pmcmcbrdbbrfbb9327dtVUlKiuLg4v/VxcXFat25dQMd66KGH1LBhQyUlJdmq0dZwas2aNX0X4V177bUqLi7W+++/r9q1a6tWrVq+9wEAAELNFcIlKytLsbGxfktWVlbQz+Hpp5/W9OnTNXv2bEVFRdn6rK0kbtGiRbZ2DgAAYKKMjAylp6f7rftrCidJderUUUREhAoLC/3WFxYWqn79+ic8xrPPPqunn35an332mVq3bm27RltNXJcuXU74/v79+5WXl2e7CAAAALtCeT+38oZOyxMZGan27dsrNzdXffr0kSTfJIWhQ4ce93Pjxo3TU089pQULFqhDhw6nVGNQH7v1448/qnPnziopKTnhduWNM3tLDsmKqBrMcgAAwBmsstyUNz09XampqerQoYM6duyoCRMmaN++fUpLS5MkDRgwQI0aNfINxz7zzDMaPXq03n33XcXHx6ugoECSFBMTo5iYmICPa+uauGApb5x516pZ4SgFAACgQvr27atnn31Wo0ePVtu2bZWXl6f58+f7Jjvk5+frt99+823/6quvqri4WDfddJMaNGjgW5599llbx7W8Xm/Q5ud+/fXXuvTSS08piWsz4hOSuErinntqhLsEHNGr8fEfc4fTK6HttHCXgGM0vOqGcJeAI9ZPuSVsx5696ZOQ7fuG+GtCtu9gCepwaqDKG2emgQMAAAicrSbuww8/POH7GzdurFAxAAAAgaos18SFi60m7uisixOxLIf/RAEAAE4DW01caWlpqOoAAACwhSTuFPz+++86++yzJUk///yzJk2apIMHDyolJUWdO3cOaoEAAAAoy9YtRr799lvFx8erXr16atGihfLy8nTZZZfp+eef12uvvaZu3bppzpw5ISoVAADgTy4rdIsJbDVxI0aMUKtWrbR06VJ17dpV1157rXr37q3du3dr586duvfee/X000+HqlYAAACfCCt0iwlsDaf+5z//0f/+7/+qdevWatOmjV5//XX97W9/k8v1Ry94//336/LLLw9JoQAAAPiTrSZux44dvoe5xsTEKDo6WrVq1fK9X6tWLe3Zsye4FQIAAJTDZQXteQVGsv3Yrb/eQoRbigAAAJx+tmenDhw40Pe0hYMHD+q+++5TdHS0JJV5lBYAAECohOUB8JWIrSYuNTXV73X//v3LbDNgwICKVQQAAICTstXETZkyJVR1AAAA2GLKrUBCxelJJAAAgJFO6YkNAAAA4WbK/dxChSYOAAAYiVuMAAAAwDgkcQAAwEhMbAAAAIBxSOIAAICRSOIAAABgHJI4AABgJKcnUU4/fwAAACORxAEAACNZDr8mjiYOAAAYyeE9HMOpAAAAJiKJAwAARnL6cCpJHAAAgIFI4gAAgJGcnkQ5/fwBAACMRBIHAACMZFnecJcQViRxAAAABiKJAwAARnL45FSaOAAAYCZuMQIAAADjkMQBAAAjOTyII4kDAAAwEUkcAAAwksvhURxJHAAAgIFI4gAAgJEcHsSRxAEAAJiIJA4AABjJ6feJo4kDAABGcngPx3AqAACAiSpNEhfx3e/hLgFHvJJbK9wl4Ijont5wl4AjGl51Q7hLwDG25M4OdwnwuSVsRyaJAwAAgHEqTRIHAABgBzf7BQAAgHFI4gAAgJEcHsSRxAEAAJiIJA4AABjJspw9g58mDgAAGInhVAAAABiHJA4AABjJ6c9OJYkDAAAwEEkcAAAwktOTKKefPwAAgJFI4gAAgJG4Jg4AAADGIYkDAABGcngQRxMHAADMxHAqAAAAjEMSBwAAjOTwII4kDgAAwEQkcQAAwEguh0dxJHEAAAAGIokDAABGcngQRxIHAABgIpI4AABgJMvyhruEsCKJAwAAqKDs7GzFx8crKipKCQkJWrFixQm3nzlzplq0aKGoqCi1atVK8+bNs31MmjgAAGAkK4SLHTNmzFB6eroyMzO1evVqtWnTRsnJydq6dWu52y9btkz9+vXTXXfdpa+++kp9+vRRnz59tGbNGlvHpYkDAABGsqzQLXaMHz9egwYNUlpamlq2bKmJEyeqevXqysnJKXf7F154QT179tSDDz6oiy66SE888YQuvfRSvfzyy7aOSxMHAADwFx6PR0VFRX6Lx+Mps11xcbFWrVqlpKQk3zqXy6WkpCQtX7683H0vX77cb3tJSk5OPu72x0MTBwAAjBTK4dSsrCzFxsb6LVlZWWVq2L59u0pKShQXF+e3Pi4uTgUFBeXWXVBQYGv742F2KgAAwF9kZGQoPT3db53b7Q5TNeWjiQMAAEYK5XCi2+0OqGmrU6eOIiIiVFhY6Le+sLBQ9evXL/cz9evXt7X98TCcCgAAcIoiIyPVvn175ebm+taVlpYqNzdXiYmJ5X4mMTHRb3tJWrhw4XG3Px6SOAAAYCS7s0hDJT09XampqerQoYM6duyoCRMmaN++fUpLS5MkDRgwQI0aNfJdUzds2DB16dJFzz33nHr37q3p06dr5cqVev31120dlyYOAACgAvr27att27Zp9OjRKigoUNu2bTV//nzf5IX8/Hy5XH8Ofl5xxRV69913NWrUKD388MO68MILNWfOHF1yySW2jmt5vd5K8cyKC7tNCncJOMKTckG4S8ARD/Y8FO4ScMSEf+0Kdwk4xpbc2eEuAUccyH8vbMfe4fkoZPuu7U4J2b6DhSQOAAAYybL9bIUzi62JDT/88EOZZ4Hl5uaqW7du6tixo8aOHRvU4gAAAFA+W03cQw89pI8//tj3euPGjUpJSVFkZKQSExOVlZWlCRMmBLtGAACAMizLFbLFBLaGU1euXKkRI0b4Xk+bNk3NmjXTggULJEmtW7fWSy+9pAceeCCoRQIAAMCfrVZz+/btOuecc3yvFy1apJSUPy/869q1qzZt2hS04gAAAI4vlA/eqvxsNXG1a9fWb7/9JumPG9mtXLlSl19+ue/94uJiVZLJrgAAAGc0W01c165d9cQTT+jnn3/WhAkTVFpaqq5du/re/+677xQfHx/kEgEAAMqyQvg/E9i6Ju7JJ59Ujx49dO655yoiIkIvvviioqOjfe+//fbb6t69e9CLBAAAgD9bTVzTpk21bt06rV27VnXr1lXDhg393h8zZozfNXMAAAChY0ZiFiq2mrjzzjtP//nPf9SmTZty3z/e+r/yeDzyeDx+67ylh2S5qtopBwAAOJgptwIJFVtnv2nTJpWUlFT4oFlZWYqNjfVbdmz+pML7BQAAcIqwtLAZGRnavXu331L73GvCUQoAADCWs28xYvvZqQsWLFBsbOwJt7nuuutO+L7b7Zbb7fZbx1AqAABA4Gw3campqSd837KsoAy5AgAAnIgptwIJFdvDqQUFBSotLT3uQgMHAAAQeraTOAAAgMqAJA4AAADGsdXE3X777XrttdfUqVMnXXbZZRo5cqQOHDgQqtoAAABOwBXCpfKzVWWzZs302GOPKSYmRo0aNdILL7ygIUOGhKo2AACA47IsK2SLCWw1cW+//bZeeeUVLViwQHPmzNFHH32kadOmqbS0NFT1AQAAoBy2mrjNmzerV69evtdJSUmyLEtbtmwJemEAAAAn5uyb/dpq4g4fPqyoqCi/dVWrVtWhQ4eCWhQAAABOzNYtRrxerwYOHOj3tIWDBw/qvvvuU3R0tG/drFmzglchAABAOZx+ixFbTVx5T2vo379/0IoBAABAYGw1cVOmTAlVHQAAADaZcSuQUHH22QMAABiKx24BAAAjcU0cAACAgUy5KW+oMJwKAABgIJI4AABgKJI4AAAAGIYkDgAAGMlyeBbl7LMHAAAwFEkcAAAwFNfEAQAAwDAkcQAAwEhOv08cTRwAADCUs5s4hlMBAAAMRBIHAACMxC1GAAAAYBySOAAAYCiuiQMAAIBhSOIAAICRLJI4AAAAmIYkDgAAGImb/QIAABjJ2QOKzj57AAAAQ5HEAQAAIzGxAQAAAMYhiQMAAIYiiQMAAIBhSOIAAICRnH6LEZI4AAAAA5HEAQAAQzk7i6KJAwAARuIWIwAAADCO5fV6veEu4kzg8XiUlZWljIwMud3ucJfjeHwflQffReXBd1F58F0gGGjigqSoqEixsbHavXu3zjrrrHCX43h8H5UH30XlwXdRefBdIBgYTgUAADAQTRwAAICBaOIAAAAMRBMXJG63W5mZmVygWknwfVQefBeVB99F5cF3gWBgYgMAAICBSOIAAAAMRBMHAABgIJo4AAAAA9HEAQAAGIgm7gQGDhwoy7JkWZaqVq2qpk2basSIETp48KBvm6Pv/3WZPn26JGnx4sV+66tVq6aLL75Yr7/+erhOy2jLly9XRESEevfuXea92bNn6/LLL1dsbKxq1Kihiy++WA888IAkqWvXrsf9rizLUteuXU/viZwBtm3bpsGDB6tJkyZyu92qX7++kpOT9dRTT53wZ21ZlhYvXqypU6eqZs2a4T4N4x37e8qyLJ199tnq2bOnvvnmG982lmVpzpw55X7+6O+oXbt2+dZt2bJFrVq10pVXXqndu3eH+AzOLMd+H5GRkbrgggv0+OOPq3///if8NxEfHy9J2rhxo2677TY1bNhQUVFROuecc3T99ddr3bp14T0xVEpVwl1AZdezZ09NmTJFhw4d0qpVq5SamirLsvTMM8/4tpkyZYp69uzp97m//nH6/vvvddZZZ+nAgQP66KOPNHjwYJ1//vm66qqrTsdpnDEmT56s+++/X5MnT9aWLVvUsGFDSVJubq769u2rp556Stddd50sy9J3332nhQsXSpJmzZql4uJiSdLPP/+sjh076rPPPtPFF18sSYqMjAzPCRnsxhtvVHFxsd58802dd955KiwsVG5uri6++GL99ttvvu2GDRumoqIiTZkyxbeudu3a2rRpUxiqPjMd/T0lSQUFBRo1apSuvfZa5efn297X+vXr1aNHD7Vs2VIzZ85UtWrVgl3uGe/o9+HxeDRv3jwNGTJEmZmZfv8uGjRo4Pe3IyIiQocOHVKPHj3UvHlzzZo1Sw0aNNAvv/yiTz75xK/JBo6iiTuJowmDJDVu3FhJSUlauHChXxNXs2ZN3zbHU69ePV9j9/e//10vvviiVq9eTRNnw969ezVjxgytXLlSBQUFmjp1qh5++GFJ0kcffaROnTrpwQcf9G3frFkz9enTR9IfTcNRR5PUs88++6TfG8q3a9cuff7551q8eLG6dOkiSTr33HPVsWPHMttWq1ZNHo+Hn3UIHft7qn79+ho5cqQ6d+6sbdu2qW7dugHv55tvvlFycrK6d++uN998U1Wq8CfiVBz7fQwePFizZ8/W/PnzlZmZ6bfdX/925OXlaf369crNzdW5554r6Y9/V506dTp9xcMoDKfasGbNGi1btqxCqY3X69X8+fOVn5+vhISEIFZ35nv//ffVokULNW/eXP3791dOTo6O3uawfv36Wrt2rdasWRPmKp0hJiZGMTExmjNnjjweT7jLwTH27t2rd955RxdccIHOPvvsgD+3bNkydenSRTfeeKPeeecdGrggqlatmm8k4ETq1q0rl8ulDz74QCUlJaehMpiOJu4kPv74Y8XExCgqKkqtWrXS1q1b/dIeSerXr5/vj9rR5a/DGOecc45iYmIUGRmp3r17KzMzU1deeeXpPBXjTZ48Wf3795f0x3DF7t27tWTJEknS/fffr8suu0ytWrVSfHy8br31VuXk5NBghEiVKlU0depUvfnmm6pZs6Y6deqkhx9+2O86LJw+R39PxcTEqEaNGvrwww81Y8YMuVyB/4q/4YYblJKSopdfflmWZYWwWufwer367LPPtGDBAnXv3v2k2zdq1EgvvviiRo8erVq1aql79+564okntGHDhtNQLUxEE3cS3bp1U15env79738rNTVVaWlpuvHGG/22ef7555WXl+e3HL1W66jPP//c994bb7yhsWPH6tVXXz2dp2K077//XitWrFC/fv0k/dFE9O3bV5MnT5YkRUdHa+7cufrpp580atQoxcTE6B//+Ic6duyo/fv3h7P0M9aNN96oLVu26MMPP1TPnj21ePFiXXrppZo6dWq4S3Oco7+n8vLytGLFCiUnJ+uaa67R5s2bA97H9ddfr9mzZ+vzzz8PYaXOcOx//F9zzTXq27evHnvssYA+O2TIEBUUFGjatGlKTEzUzJkzdfHFF/uu7wX8eHFcqamp3uuvv973uqSkxHvJJZd433jjDd86Sd7Zs2cfdx+LFi3ySvLu3LnTb/29997rbdSoUZArPnM9+OCDXkneiIgI3+JyubzVqlXz7tq1q9zPbNiwwVulShVvTk6O3/qNGzd6JXm/+uqr01C5s9x1113eJk2a+K3767+jo6ZMmeKNjY09PYWdwcr7+R4+fNgbHR3tfeSRR7xe74l/Tx39HbVjxw7v3Xff7Y2OjvYuWbIkxFWfuVJTU71JSUneH3/80bt582bvoUOHyt3uZH87jiotLfX26NHDe+WVVwa5UpwJSOJscLlcevjhhzVq1CgdOHCgQvuKiIio8D6c4vDhw3rrrbf03HPP+aWdX3/9tRo2bKj33nuv3M/Fx8erevXq2rdv32mu2LlatmzJz7sSsCxLLpfL1u8Yy7L0+uuv6/bbb1evXr18lyrAvujoaF1wwQVq0qRJha8ttCxLLVq04N8VysWVqzbdfPPNevDBB5Wdna1//vOfkv6YqVdQUOC3XY0aNRQdHe17vXXrVh08eFAej0crVqzQ22+/rZtuuum01m6qjz/+WDt37tRdd92l2NhYv/duvPFGTZ48WQUFBdq/f7969eqlc889V7t27dKLL77om7KP4Pr999918803684771Tr1q1Vo0YNrVy5UuPGjdP1118f8H5KSkqUl5fnt87tduuiiy4KcsVnNo/H4/sdtHPnTr388svau3evUlJSfNts3LixzM/6wgsv9HttWZYmTpyoiIgI9erVS3PnzuUeiqdRXl6eMjMzdccdd6hly5aKjIzUkiVLlJOTo4ceeijc5aESoomzqUqVKho6dKjGjRunwYMHS5LS0tLKbJeVlaWRI0f6Xjdv3tz3+caNG+vee+8N+BoJp5s8ebKSkpLKNHDSH03cuHHj1L9/f61Zs0YDBgxQYWGhatWqpXbt2unTTz/1/ewRPDExMUpISNDzzz+v9evX69ChQ2rcuLEGDRrku+1LIPbu3at27dr5rTv//PP1008/BbvkM9r8+fPVoEEDSX/8B2SLFi00c+ZMvwYsPT29zOfKu/7NsixlZ2fL5XKpd+/e+vjjj9WtW7eQ1Y4/nXPOOYqPj9eYMWO0adMm302Ax4wZo+HDh4e7PFRCltd75B4NAAAAMAbXxAEAABiIJg4AAMBANHEAAAAGookDAAAwEE0cAACAgWjiAAAADEQTBwAAYCCaOAAAAAPRxAEAABiIJg4AAMBANHEAAAAGookDAAAw0P8HLEuFLjN2ghYAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "CL2O8CBKFp93"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}