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            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/08/33/80e0d4f60e84a1ddd9a03f340be1065a2a363c47ce65c4bd3bae65ce9631/websocket_client-0.58.0-py2.py3-none-any.whl (61kB)\n",
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            "  Created wheel for prometheus-flask-exporter: filename=prometheus_flask_exporter-0.18.2-cp37-none-any.whl size=17396 sha256=07e7eac72258feea23926300e813b3cfdacc2a93426bef3ef8ac90993c7e331b\n",
            "  Stored in directory: /root/.cache/pip/wheels/c0/e2/9c/4f3ee23964802940f81a8b476d0b9be6fb6348cb12df2e2226\n",
            "  Building wheel for alembic (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for alembic: filename=alembic-1.4.1-py2.py3-none-any.whl size=158155 sha256=ab5ae2f705d5bb3e3692c2703b24ef487df71b38047cdbbe51e3e17ec7942fc8\n",
            "  Stored in directory: /root/.cache/pip/wheels/84/07/f7/12f7370ca47a66030c2edeedcc23dec26ea0ac22dcb4c4a0f3\n",
            "  Building wheel for databricks-cli (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for databricks-cli: filename=databricks_cli-0.14.3-cp37-none-any.whl size=100557 sha256=f9fd57157778a1cbe696a0335d47245b09c2699c7319841422b9dc0a316c9910\n",
            "  Stored in directory: /root/.cache/pip/wheels/5b/24/f3/34d8e3964dac4ba849d844273c49a679111b00d5799ebb934a\n",
            "  Building wheel for htmlmin (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for htmlmin: filename=htmlmin-0.1.12-cp37-none-any.whl size=27085 sha256=de15c77e3d787e825eeb9ccbf48213fc697e8a1cd41bb272902b046932eca78d\n",
            "  Stored in directory: /root/.cache/pip/wheels/43/07/ac/7c5a9d708d65247ac1f94066cf1db075540b85716c30255459\n",
            "  Building wheel for phik (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for phik: filename=phik-0.11.2-cp37-none-any.whl size=1107413 sha256=b11c82aab2111e91b7bf8bf34234aa983f75873adaefe38a216662ada486a849\n",
            "  Stored in directory: /root/.cache/pip/wheels/c0/a3/b0/f27b1cfe32ea131a3715169132ff6d85653789e80e966c3bf6\n",
            "  Building wheel for pynndescent (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pynndescent: filename=pynndescent-0.5.2-cp37-none-any.whl size=51351 sha256=98055cfe54b8220b621490c7b55462bc7690f1f196082b5cc53c88ab04b4b970\n",
            "  Stored in directory: /root/.cache/pip/wheels/ba/52/4e/4c28d04d144a28f89e2575fb63628df6e6d49b56c5ddd0c74e\n",
            "Successfully built pyod umap-learn prometheus-flask-exporter alembic databricks-cli htmlmin phik pynndescent\n",
            "\u001b[31mERROR: pandas-profiling 2.11.0 has requirement requests>=2.24.0, but you'll have requests 2.23.0 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: pandas-profiling 2.11.0 has requirement tqdm>=4.48.2, but you'll have tqdm 4.41.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: phik 0.11.2 has requirement scipy>=1.5.2, but you'll have scipy 1.4.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: pyldavis 3.3.1 has requirement numpy>=1.20.0, but you'll have numpy 1.19.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: pyldavis 3.3.1 has requirement pandas>=1.2.0, but you'll have pandas 1.1.5 which is incompatible.\u001b[0m\n",
            "Installing collected packages: threadpoolctl, scikit-learn, pyod, lightgbm, prometheus-flask-exporter, websocket-client, docker, querystring-parser, smmap, gitdb, gitpython, gunicorn, Mako, python-editor, alembic, databricks-cli, mlflow, kmodes, yellowbrick, imbalanced-learn, tangled-up-in-unicode, imagehash, visions, confuse, htmlmin, phik, pandas-profiling, mlxtend, funcy, pyLDAvis, Boruta, scikit-plot, pynndescent, umap-learn, pycaret\n",
            "  Found existing installation: scikit-learn 0.22.2.post1\n",
            "    Uninstalling scikit-learn-0.22.2.post1:\n",
            "      Successfully uninstalled scikit-learn-0.22.2.post1\n",
            "  Found existing installation: lightgbm 2.2.3\n",
            "    Uninstalling lightgbm-2.2.3:\n",
            "      Successfully uninstalled lightgbm-2.2.3\n",
            "  Found existing installation: yellowbrick 0.9.1\n",
            "    Uninstalling yellowbrick-0.9.1:\n",
            "      Successfully uninstalled yellowbrick-0.9.1\n",
            "  Found existing installation: imbalanced-learn 0.4.3\n",
            "    Uninstalling imbalanced-learn-0.4.3:\n",
            "      Successfully uninstalled imbalanced-learn-0.4.3\n",
            "  Found existing installation: pandas-profiling 1.4.1\n",
            "    Uninstalling pandas-profiling-1.4.1:\n",
            "      Successfully uninstalled pandas-profiling-1.4.1\n",
            "  Found existing installation: mlxtend 0.14.0\n",
            "    Uninstalling mlxtend-0.14.0:\n",
            "      Successfully uninstalled mlxtend-0.14.0\n",
            "Successfully installed Boruta-0.3 Mako-1.1.4 alembic-1.4.1 confuse-1.4.0 databricks-cli-0.14.3 docker-5.0.0 funcy-1.15 gitdb-4.0.7 gitpython-3.1.14 gunicorn-20.1.0 htmlmin-0.1.12 imagehash-4.2.0 imbalanced-learn-0.7.0 kmodes-0.11.0 lightgbm-3.2.1 mlflow-1.16.0 mlxtend-0.18.0 pandas-profiling-2.11.0 phik-0.11.2 prometheus-flask-exporter-0.18.2 pyLDAvis-3.3.1 pycaret-2.3.1 pynndescent-0.5.2 pyod-0.8.8 python-editor-1.0.4 querystring-parser-1.2.4 scikit-learn-0.23.2 scikit-plot-0.3.7 smmap-4.0.0 tangled-up-in-unicode-0.0.7 threadpoolctl-2.1.0 umap-learn-0.5.1 visions-0.6.0 websocket-client-0.58.0 yellowbrick-1.3.post1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gqj7ClcdBMuH"
      },
      "source": [
        "import pandas as pd\n",
        "data = pd.read_csv('delaware_anomaly.csv')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "n586qSfbBMum",
        "outputId": "2f44cd20-6d64-4368-cd56-180b98a03799"
      },
      "source": [
        "data.head()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>FISCAL_YEAR</th>\n",
              "      <th>FISCAL_PERIOD</th>\n",
              "      <th>DEPT_NAME</th>\n",
              "      <th>DIV_NAME</th>\n",
              "      <th>MERCHANT</th>\n",
              "      <th>CAT_DESCR</th>\n",
              "      <th>TRANS_DT</th>\n",
              "      <th>MERCHANDISE_AMT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>DOUBLETREE HOTELS WASHING</td>\n",
              "      <td>LODGING</td>\n",
              "      <td>6/3/2014</td>\n",
              "      <td>-5.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>18.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>21.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>22.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>5.44</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   FISCAL_YEAR  FISCAL_PERIOD  ...   TRANS_DT MERCHANDISE_AMT\n",
              "0         2015              1  ...   6/3/2014           -5.50\n",
              "1         2015              1  ...  6/26/2014           18.31\n",
              "2         2015              1  ...  6/26/2014           21.61\n",
              "3         2015              1  ...  6/26/2014           22.39\n",
              "4         2015              1  ...  6/26/2014            5.44\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zbOVPFeqkX5n",
        "outputId": "48f56cf8-ca88-4479-b188-e8046d5dc571"
      },
      "source": [
        "data['CAT_DESCR'].value_counts()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Eating Places Restaurants                            1544\n",
              "EATING PLACES RESTAURANTS                             986\n",
              "Stationery-Office Supplies-Printing Writing Pap       909\n",
              "Lodging                                               889\n",
              "Airline                                               604\n",
              "                                                     ... \n",
              "MISCELLANEOUS REPAIR SHOPS AND RELATED SERVICES         1\n",
              "Schools Correspondence                                  1\n",
              "Attorneys Legal Services                                1\n",
              "MOTION PICTURE-VIDEO TAPE PRODUCTION-DISTRIBUTION       1\n",
              "Glass Paint Wallpaper Stores                            1\n",
              "Name: CAT_DESCR, Length: 208, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YKrUKvAeVjoo",
        "outputId": "b06b1bc7-a1c9-4a80-f653-4db806e8b0b3"
      },
      "source": [
        "data['DEPT_NAME'].value_counts() #drop this unnecessary feaure"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DEPT OF EDUCATION    15156\n",
              "Name: DEPT_NAME, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1pcOEtVpBMup",
        "scrolled": false,
        "outputId": "119d9e26-1728-4940-97da-283fefa2c943"
      },
      "source": [
        "data['MERCHANT'].value_counts()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "WB MASON                  293\n",
              "AMAZON.COM                211\n",
              "VZWRLSS*IVR VB            166\n",
              "AMAZON MKTPLACE PMTS      163\n",
              "USPS PO 0917600901        157\n",
              "                         ... \n",
              "YOURMEMBER-CAREERS          1\n",
              "UPS*ADJ00159559992581       1\n",
              "STAPLES ACCOUN00687632      1\n",
              "STAPLS0161449820000001      1\n",
              "STAPLS7151217681000001      1\n",
              "Name: MERCHANT, Length: 5802, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SwBETC83VVoP",
        "outputId": "1fc66980-fed3-4e36-fb69-f8c81bb6f788"
      },
      "source": [
        "data['DIV_NAME'].value_counts()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DEPARTMENT OF EDUCATION           4675\n",
              "Department of Education           4020\n",
              "Office of the Secretary           1081\n",
              "Special Needs Programs            1019\n",
              "Operations Support                 693\n",
              "SPECIAL NEEDS PROGRAMS             692\n",
              "Education Block Grants             581\n",
              "EDUCATION BLOCK GRANTS             445\n",
              "Academic Support                   431\n",
              "Student Support                    332\n",
              "Other Items                        255\n",
              "Office of Early Learning           253\n",
              "E Education Block Grants           204\n",
              "Educator Support                   181\n",
              "ADVISORY COUNCIL                   128\n",
              "TRANSPORTATION                      44\n",
              "Public School Transportation        27\n",
              "Transportation                      25\n",
              "Driver Training                     23\n",
              "State Board of Education            22\n",
              "DRIVER TRAINING                      9\n",
              "Professional Standards Board         6\n",
              "Adult Education and Work Force       6\n",
              "E Transportation                     3\n",
              "OTHER ITEMS                          1\n",
              "Name: DIV_NAME, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TNULr6Z6BMuq",
        "outputId": "a864429f-bc6a-4d0b-8516-506512f30647"
      },
      "source": [
        "data.shape"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(15156, 8)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DH3bVPvTBMus",
        "scrolled": true,
        "outputId": "a53a0782-1d8a-4852-811d-3bf993bed01d"
      },
      "source": [
        "data.dtypes"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "FISCAL_YEAR          int64\n",
              "FISCAL_PERIOD        int64\n",
              "DEPT_NAME           object\n",
              "DIV_NAME            object\n",
              "MERCHANT            object\n",
              "CAT_DESCR           object\n",
              "TRANS_DT            object\n",
              "MERCHANDISE_AMT    float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0ECAndkEBMuu"
      },
      "source": [
        "from pycaret.anomaly import *\n"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "0a0dea7218f247348ce3eebcbf776d3d",
            "2b0e609cc03a4eb5922401de06a6abf3",
            "f0b1814155c949b1aa4d821657f9d698",
            "e619aae19beb4bac8fecd314aa5aca0d",
            "fd0275d2d7f843aaa72c3fbd89547b73",
            "5bcb767431dc4794a38908881c8cce33"
          ]
        },
        "id": "TGS1NdBSkofx",
        "outputId": "c5d87b68-7379-422b-ffd9-b962a5f36cad"
      },
      "source": [
        "setup(data, session_id = 123)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "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>Description</th>\n",
              "      <th>Value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>session_id</td>\n",
              "      <td>123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Original Data</td>\n",
              "      <td>(15156, 8)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Missing Values</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Numeric Features</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Categorical Features</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Ordinal Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>High Cardinality Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>High Cardinality Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Transformed Data</td>\n",
              "      <td>(15156, 6078)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>CPU Jobs</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Use GPU</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Log Experiment</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Experiment Name</td>\n",
              "      <td>anomaly-default-name</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>USI</td>\n",
              "      <td>8237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Imputation Type</td>\n",
              "      <td>simple</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Iterative Imputation Iteration</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Numeric Imputer</td>\n",
              "      <td>mean</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Iterative Imputation Numeric Model</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Categorical Imputer</td>\n",
              "      <td>mode</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Iterative Imputation Categorical Model</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Unknown Categoricals Handling</td>\n",
              "      <td>least_frequent</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Normalize</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Normalize Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Transformation</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Transformation Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>PCA</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>PCA Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>PCA Components</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Ignore Low Variance</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Combine Rare Levels</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Rare Level Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Numeric Binning</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Remove Outliers</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Outliers Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Remove Multicollinearity</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>Multicollinearity Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Clustering</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>Clustering Iteration</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Polynomial Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Polynomial Degree</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Trignometry Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>Polynomial Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Group Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>Feature Selection</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Feature Selection Method</td>\n",
              "      <td>classic</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Features Selection Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Feature Interaction</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>Feature Ratio</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Interaction Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                               Description                 Value\n",
              "0                               session_id                   123\n",
              "1                            Original Data            (15156, 8)\n",
              "2                           Missing Values                 False\n",
              "3                         Numeric Features                     1\n",
              "4                     Categorical Features                     6\n",
              "5                         Ordinal Features                 False\n",
              "6                High Cardinality Features                 False\n",
              "7                  High Cardinality Method                  None\n",
              "8                         Transformed Data         (15156, 6078)\n",
              "9                                 CPU Jobs                    -1\n",
              "10                                 Use GPU                 False\n",
              "11                          Log Experiment                 False\n",
              "12                         Experiment Name  anomaly-default-name\n",
              "13                                     USI                  8237\n",
              "14                         Imputation Type                simple\n",
              "15          Iterative Imputation Iteration                  None\n",
              "16                         Numeric Imputer                  mean\n",
              "17      Iterative Imputation Numeric Model                  None\n",
              "18                     Categorical Imputer                  mode\n",
              "19  Iterative Imputation Categorical Model                  None\n",
              "20           Unknown Categoricals Handling        least_frequent\n",
              "21                               Normalize                 False\n",
              "22                        Normalize Method                  None\n",
              "23                          Transformation                 False\n",
              "24                   Transformation Method                  None\n",
              "25                                     PCA                 False\n",
              "26                              PCA Method                  None\n",
              "27                          PCA Components                  None\n",
              "28                     Ignore Low Variance                 False\n",
              "29                     Combine Rare Levels                 False\n",
              "30                    Rare Level Threshold                  None\n",
              "31                         Numeric Binning                 False\n",
              "32                         Remove Outliers                 False\n",
              "33                      Outliers Threshold                  None\n",
              "34                Remove Multicollinearity                 False\n",
              "35             Multicollinearity Threshold                  None\n",
              "36                              Clustering                 False\n",
              "37                    Clustering Iteration                  None\n",
              "38                     Polynomial Features                 False\n",
              "39                       Polynomial Degree                  None\n",
              "40                    Trignometry Features                 False\n",
              "41                    Polynomial Threshold                  None\n",
              "42                          Group Features                 False\n",
              "43                       Feature Selection                 False\n",
              "44                Feature Selection Method               classic\n",
              "45            Features Selection Threshold                  None\n",
              "46                     Feature Interaction                 False\n",
              "47                           Feature Ratio                 False\n",
              "48                   Interaction Threshold                  None"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "({'abod': <pycaret.containers.models.anomaly.ABODAnomalyContainer at 0x7efe9317d950>,\n",
              "  'cluster': <pycaret.containers.models.anomaly.CBLOFAnomalyContainer at 0x7efe931836d0>,\n",
              "  'cof': <pycaret.containers.models.anomaly.COFAnomalyContainer at 0x7efe93183650>,\n",
              "  'histogram': <pycaret.containers.models.anomaly.HBOSAnomalyContainer at 0x7efe93183850>,\n",
              "  'iforest': <pycaret.containers.models.anomaly.IForestAnomalyContainer at 0x7efe931837d0>,\n",
              "  'knn': <pycaret.containers.models.anomaly.KNNAnomalyContainer at 0x7efe93183910>,\n",
              "  'lof': <pycaret.containers.models.anomaly.LOFAnomalyContainer at 0x7efe93183a50>,\n",
              "  'mcd': <pycaret.containers.models.anomaly.MCDAnomalyContainer at 0x7efe931838d0>,\n",
              "  'pca': <pycaret.containers.models.anomaly.PCAAnomalyContainer at 0x7efe93183e10>,\n",
              "  'sod': <pycaret.containers.models.anomaly.SODAnomalyContainer at 0x7efe93183f50>,\n",
              "  'sos': <pycaret.containers.models.anomaly.SOSAnomalyContainer at 0x7efe9318d050>,\n",
              "  'svm': <pycaret.containers.models.anomaly.OCSVMAnomalyContainer at 0x7efe93183d90>},\n",
              " None,\n",
              "        MERCHANDISE_AMT  ...  TRANS_DT_is_month_start_1\n",
              " 0            -5.500000  ...                        0.0\n",
              " 1            18.309999  ...                        0.0\n",
              " 2            21.610001  ...                        0.0\n",
              " 3            22.389999  ...                        0.0\n",
              " 4             5.440000  ...                        0.0\n",
              " ...                ...  ...                        ...\n",
              " 15151        52.580002  ...                        0.0\n",
              " 15152        14.910000  ...                        0.0\n",
              " 15153       111.000000  ...                        0.0\n",
              " 15154        99.989998  ...                        0.0\n",
              " 15155        99.989998  ...                        0.0\n",
              " \n",
              " [15156 rows x 6078 columns],\n",
              " '8237',\n",
              " -1,\n",
              " -1,\n",
              " {'tsne': 'Anomaly TSnE (3d)', 'umap': 'UMAP Dimensionality'},\n",
              " None,\n",
              " Pipeline(memory=None,\n",
              "          steps=[('dtypes',\n",
              "                  DataTypes_Auto_infer(categorical_features=[],\n",
              "                                       display_types=True, features_todrop=[],\n",
              "                                       id_columns=[], ml_usecase='regression',\n",
              "                                       numerical_features=[],\n",
              "                                       target='UNSUPERVISED_DUMMY_TARGET',\n",
              "                                       time_features=[])),\n",
              "                 ('imputer',\n",
              "                  Simple_Imputer(categorical_strategy='most frequent',\n",
              "                                 fill_value_categorical=None,\n",
              "                                 fill_value_numerical=None...\n",
              "                 ('scaling', 'passthrough'), ('P_transform', 'passthrough'),\n",
              "                 ('binn', 'passthrough'), ('rem_outliers', 'passthrough'),\n",
              "                 ('cluster_all', 'passthrough'),\n",
              "                 ('dummy', Dummify(target='UNSUPERVISED_DUMMY_TARGET')),\n",
              "                 ('fix_perfect', 'passthrough'),\n",
              "                 ('clean_names', Clean_Colum_Names()),\n",
              "                 ('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),\n",
              "                 ('dfs', 'passthrough'), ('pca', 'passthrough')],\n",
              "          verbose=False),\n",
              " False,\n",
              " [('Setup Config',\n",
              "                                  Description                 Value\n",
              "   0                               session_id                   123\n",
              "   1                            Original Data            (15156, 8)\n",
              "   2                           Missing Values                 False\n",
              "   3                         Numeric Features                     1\n",
              "   4                     Categorical Features                     6\n",
              "   5                         Ordinal Features                 False\n",
              "   6                High Cardinality Features                 False\n",
              "   7                  High Cardinality Method                  None\n",
              "   8                         Transformed Data         (15156, 6078)\n",
              "   9                                 CPU Jobs                    -1\n",
              "   10                                 Use GPU                 False\n",
              "   11                          Log Experiment                 False\n",
              "   12                         Experiment Name  anomaly-default-name\n",
              "   13                                     USI                  8237\n",
              "   14                         Imputation Type                simple\n",
              "   15          Iterative Imputation Iteration                  None\n",
              "   16                         Numeric Imputer                  mean\n",
              "   17      Iterative Imputation Numeric Model                  None\n",
              "   18                     Categorical Imputer                  mode\n",
              "   19  Iterative Imputation Categorical Model                  None\n",
              "   20           Unknown Categoricals Handling        least_frequent\n",
              "   21                               Normalize                 False\n",
              "   22                        Normalize Method                  None\n",
              "   23                          Transformation                 False\n",
              "   24                   Transformation Method                  None\n",
              "   25                                     PCA                 False\n",
              "   26                              PCA Method                  None\n",
              "   27                          PCA Components                  None\n",
              "   28                     Ignore Low Variance                 False\n",
              "   29                     Combine Rare Levels                 False\n",
              "   30                    Rare Level Threshold                  None\n",
              "   31                         Numeric Binning                 False\n",
              "   32                         Remove Outliers                 False\n",
              "   33                      Outliers Threshold                  None\n",
              "   34                Remove Multicollinearity                 False\n",
              "   35             Multicollinearity Threshold                  None\n",
              "   36                              Clustering                 False\n",
              "   37                    Clustering Iteration                  None\n",
              "   38                     Polynomial Features                 False\n",
              "   39                       Polynomial Degree                  None\n",
              "   40                    Trignometry Features                 False\n",
              "   41                    Polynomial Threshold                  None\n",
              "   42                          Group Features                 False\n",
              "   43                       Feature Selection                 False\n",
              "   44                Feature Selection Method               classic\n",
              "   45            Features Selection Threshold                  None\n",
              "   46                     Feature Interaction                 False\n",
              "   47                           Feature Ratio                 False\n",
              "   48                   Interaction Threshold                  None),\n",
              "  ('Transformed Data',        MERCHANDISE_AMT  ...  TRANS_DT_is_month_start_1\n",
              "   0            -5.500000  ...                        0.0\n",
              "   1            18.309999  ...                        0.0\n",
              "   2            21.610001  ...                        0.0\n",
              "   3            22.389999  ...                        0.0\n",
              "   4             5.440000  ...                        0.0\n",
              "   ...                ...  ...                        ...\n",
              "   15151        52.580002  ...                        0.0\n",
              "   15152        14.910000  ...                        0.0\n",
              "   15153       111.000000  ...                        0.0\n",
              "   15154        99.989998  ...                        0.0\n",
              "   15155        99.989998  ...                        0.0\n",
              "   \n",
              "   [15156 rows x 6078 columns]),\n",
              "  ('Transformation Pipeline', Pipeline(memory=None,\n",
              "            steps=[('dtypes',\n",
              "                    DataTypes_Auto_infer(categorical_features=[],\n",
              "                                         display_types=True, features_todrop=[],\n",
              "                                         id_columns=[], ml_usecase='regression',\n",
              "                                         numerical_features=[],\n",
              "                                         target='UNSUPERVISED_DUMMY_TARGET',\n",
              "                                         time_features=[])),\n",
              "                   ('imputer',\n",
              "                    Simple_Imputer(categorical_strategy='most frequent',\n",
              "                                   fill_value_categorical=None,\n",
              "                                   fill_value_numerical=None...\n",
              "                   ('scaling', 'passthrough'), ('P_transform', 'passthrough'),\n",
              "                   ('binn', 'passthrough'), ('rem_outliers', 'passthrough'),\n",
              "                   ('cluster_all', 'passthrough'),\n",
              "                   ('dummy', Dummify(target='UNSUPERVISED_DUMMY_TARGET')),\n",
              "                   ('fix_perfect', 'passthrough'),\n",
              "                   ('clean_names', Clean_Colum_Names()),\n",
              "                   ('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),\n",
              "                   ('dfs', 'passthrough'), ('pca', 'passthrough')],\n",
              "            verbose=False))],\n",
              "        FISCAL_YEAR  FISCAL_PERIOD  ...    TRANS_DT MERCHANDISE_AMT\n",
              " 0             2015              1  ...    6/3/2014           -5.50\n",
              " 1             2015              1  ...   6/26/2014           18.31\n",
              " 2             2015              1  ...   6/26/2014           21.61\n",
              " 3             2015              1  ...   6/26/2014           22.39\n",
              " 4             2015              1  ...   6/26/2014            5.44\n",
              " ...            ...            ...  ...         ...             ...\n",
              " 15151         2020              6  ...  12/12/2019           52.58\n",
              " 15152         2020              6  ...  12/13/2019           14.91\n",
              " 15153         2020              6  ...  12/13/2019          111.00\n",
              " 15154         2020              6  ...   12/5/2019           99.99\n",
              " 15155         2020              6  ...   12/9/2019           99.99\n",
              " \n",
              " [15156 rows x 8 columns],\n",
              " [<pandas.io.formats.style.Styler at 0x7efe9318d510>],\n",
              " 'lightgbm',\n",
              " 5,\n",
              " {'abod': <pycaret.containers.models.anomaly.ABODAnomalyContainer at 0x7efe931b0f10>,\n",
              "  'cluster': <pycaret.containers.models.anomaly.CBLOFAnomalyContainer at 0x7efe931b0b10>,\n",
              "  'cof': <pycaret.containers.models.anomaly.COFAnomalyContainer at 0x7efe931b0ad0>,\n",
              "  'histogram': <pycaret.containers.models.anomaly.HBOSAnomalyContainer at 0x7efe93202950>,\n",
              "  'iforest': <pycaret.containers.models.anomaly.IForestAnomalyContainer at 0x7efe931b0c90>,\n",
              "  'knn': <pycaret.containers.models.anomaly.KNNAnomalyContainer at 0x7efe93160090>,\n",
              "  'lof': <pycaret.containers.models.anomaly.LOFAnomalyContainer at 0x7efe93160410>,\n",
              "  'mcd': <pycaret.containers.models.anomaly.MCDAnomalyContainer at 0x7efe93160390>,\n",
              "  'pca': <pycaret.containers.models.anomaly.PCAAnomalyContainer at 0x7efe9316b350>,\n",
              "  'sod': <pycaret.containers.models.anomaly.SODAnomalyContainer at 0x7efe9316b450>,\n",
              "  'sos': <pycaret.containers.models.anomaly.SOSAnomalyContainer at 0x7efe9316bc10>,\n",
              "  'svm': <pycaret.containers.models.anomaly.OCSVMAnomalyContainer at 0x7efe9316b210>},\n",
              " True,\n",
              " {},\n",
              " 'lightgbm',\n",
              " {'USI',\n",
              "  'X',\n",
              "  '_all_metrics',\n",
              "  '_all_models',\n",
              "  '_all_models_internal',\n",
              "  '_available_plots',\n",
              "  '_gpu_n_jobs_param',\n",
              "  '_internal_pipeline',\n",
              "  '_ml_usecase',\n",
              "  'create_model_container',\n",
              "  'data_before_preprocess',\n",
              "  'display_container',\n",
              "  'exp_name_log',\n",
              "  'experiment__',\n",
              "  'fix_imbalance_method_param',\n",
              "  'fix_imbalance_param',\n",
              "  'fold_generator',\n",
              "  'fold_groups_param',\n",
              "  'fold_groups_param_full',\n",
              "  'fold_param',\n",
              "  'fold_shuffle_param',\n",
              "  'gpu_param',\n",
              "  'html_param',\n",
              "  'imputation_classifier',\n",
              "  'imputation_regressor',\n",
              "  'iterative_imputation_iters_param',\n",
              "  'log_plots_param',\n",
              "  'logging_param',\n",
              "  'master_model_container',\n",
              "  'n_jobs_param',\n",
              "  'prep_pipe',\n",
              "  'pycaret_globals',\n",
              "  'seed',\n",
              "  'stratify_param',\n",
              "  'target_param',\n",
              "  'transform_target_method_param',\n",
              "  'transform_target_param'},\n",
              " Pipeline(memory=None, steps=[('empty_step', 'passthrough')], verbose=False),\n",
              " 'anomaly-default-name',\n",
              " [],\n",
              " KFold(n_splits=10, random_state=None, shuffle=False),\n",
              " 123,\n",
              " False,\n",
              " 'box-cox',\n",
              " [],\n",
              " False,\n",
              " None,\n",
              " False,\n",
              " False,\n",
              " 'UNSUPERVISED_DUMMY_TARGET',\n",
              " <MLUsecase.ANOMALY: 4>,\n",
              " False,\n",
              " False,\n",
              " 10)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6YVlMSC1kn1w",
        "outputId": "9a02d1e5-94a2-41b3-e63b-e5773985386d"
      },
      "source": [
        "get_config('X').columns"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['MERCHANDISE_AMT', 'FISCAL_YEAR_2015', 'FISCAL_YEAR_2016',\n",
              "       'FISCAL_YEAR_2017', 'FISCAL_YEAR_2018', 'FISCAL_YEAR_2019',\n",
              "       'FISCAL_YEAR_2020', 'FISCAL_PERIOD_1', 'FISCAL_PERIOD_10',\n",
              "       'FISCAL_PERIOD_11',\n",
              "       ...\n",
              "       'TRANS_DT_weekday_1', 'TRANS_DT_weekday_2', 'TRANS_DT_weekday_3',\n",
              "       'TRANS_DT_weekday_4', 'TRANS_DT_weekday_5', 'TRANS_DT_weekday_6',\n",
              "       'TRANS_DT_is_month_end_0', 'TRANS_DT_is_month_end_1',\n",
              "       'TRANS_DT_is_month_start_0', 'TRANS_DT_is_month_start_1'],\n",
              "      dtype='object', length=6078)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "824a27666fe14bd5a312eae9ba996207",
            "f57fd3e871ff40718427ba4cef970456",
            "d9b11c1411234a92a829b78c08fbabbc",
            "247a6afdcc2f4c7a82006e4b0d718f3e",
            "b42cd7fa7b26454c9a276e6c53840c65",
            "b11c9330f5de43bdb6ae05ca182ed4da"
          ]
        },
        "id": "EbG96mNoklCT",
        "outputId": "abd6434c-5055-4b71-b928-59966d703e64"
      },
      "source": [
        "s = setup(data, session_id = 123,\n",
        "          ignore_features = ['CAT_DESCR'], high_cardinality_features= ['MERCHANT'],\n",
        "          numeric_features = ['FISCAL_YEAR', 'FISCAL_PERIOD' ])"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>Description</th>\n",
              "      <th>Value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>session_id</td>\n",
              "      <td>123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Original Data</td>\n",
              "      <td>(15156, 8)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Missing Values</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Numeric Features</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Categorical Features</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Ordinal Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>High Cardinality Features</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>High Cardinality Method</td>\n",
              "      <td>frequency</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Transformed Data</td>\n",
              "      <td>(15156, 53)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>CPU Jobs</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Use GPU</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Log Experiment</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Experiment Name</td>\n",
              "      <td>anomaly-default-name</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>USI</td>\n",
              "      <td>f760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Imputation Type</td>\n",
              "      <td>simple</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Iterative Imputation Iteration</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Numeric Imputer</td>\n",
              "      <td>mean</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Iterative Imputation Numeric Model</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Categorical Imputer</td>\n",
              "      <td>mode</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Iterative Imputation Categorical Model</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Unknown Categoricals Handling</td>\n",
              "      <td>least_frequent</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Normalize</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Normalize Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Transformation</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Transformation Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>PCA</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>PCA Method</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>PCA Components</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Ignore Low Variance</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Combine Rare Levels</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Rare Level Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Numeric Binning</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Remove Outliers</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Outliers Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Remove Multicollinearity</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>Multicollinearity Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Clustering</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>Clustering Iteration</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Polynomial Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Polynomial Degree</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Trignometry Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>Polynomial Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Group Features</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>Feature Selection</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Feature Selection Method</td>\n",
              "      <td>classic</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Features Selection Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Feature Interaction</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>Feature Ratio</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Interaction Threshold</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                               Description                 Value\n",
              "0                               session_id                   123\n",
              "1                            Original Data            (15156, 8)\n",
              "2                           Missing Values                 False\n",
              "3                         Numeric Features                     3\n",
              "4                     Categorical Features                     3\n",
              "5                         Ordinal Features                 False\n",
              "6                High Cardinality Features                  True\n",
              "7                  High Cardinality Method             frequency\n",
              "8                         Transformed Data           (15156, 53)\n",
              "9                                 CPU Jobs                    -1\n",
              "10                                 Use GPU                 False\n",
              "11                          Log Experiment                 False\n",
              "12                         Experiment Name  anomaly-default-name\n",
              "13                                     USI                  f760\n",
              "14                         Imputation Type                simple\n",
              "15          Iterative Imputation Iteration                  None\n",
              "16                         Numeric Imputer                  mean\n",
              "17      Iterative Imputation Numeric Model                  None\n",
              "18                     Categorical Imputer                  mode\n",
              "19  Iterative Imputation Categorical Model                  None\n",
              "20           Unknown Categoricals Handling        least_frequent\n",
              "21                               Normalize                 False\n",
              "22                        Normalize Method                  None\n",
              "23                          Transformation                 False\n",
              "24                   Transformation Method                  None\n",
              "25                                     PCA                 False\n",
              "26                              PCA Method                  None\n",
              "27                          PCA Components                  None\n",
              "28                     Ignore Low Variance                 False\n",
              "29                     Combine Rare Levels                 False\n",
              "30                    Rare Level Threshold                  None\n",
              "31                         Numeric Binning                 False\n",
              "32                         Remove Outliers                 False\n",
              "33                      Outliers Threshold                  None\n",
              "34                Remove Multicollinearity                 False\n",
              "35             Multicollinearity Threshold                  None\n",
              "36                              Clustering                 False\n",
              "37                    Clustering Iteration                  None\n",
              "38                     Polynomial Features                 False\n",
              "39                       Polynomial Degree                  None\n",
              "40                    Trignometry Features                 False\n",
              "41                    Polynomial Threshold                  None\n",
              "42                          Group Features                 False\n",
              "43                       Feature Selection                 False\n",
              "44                Feature Selection Method               classic\n",
              "45            Features Selection Threshold                  None\n",
              "46                     Feature Interaction                 False\n",
              "47                           Feature Ratio                 False\n",
              "48                   Interaction Threshold                  None"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MOIbKXA4BMuw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e6c161ec-0499-4c8c-d8b7-0468825325f8"
      },
      "source": [
        "get_config('X').columns"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['FISCAL_YEAR', 'FISCAL_PERIOD', 'MERCHANT', 'MERCHANDISE_AMT',\n",
              "       'DEPT_NAME_DEPT OF EDUCATION', 'DIV_NAME_ADVISORY COUNCIL',\n",
              "       'DIV_NAME_Academic Support', 'DIV_NAME_Adult Education and Work Force',\n",
              "       'DIV_NAME_DEPARTMENT OF EDUCATION', 'DIV_NAME_DRIVER TRAINING',\n",
              "       'DIV_NAME_Department of Education', 'DIV_NAME_Driver Training',\n",
              "       'DIV_NAME_E Education Block Grants', 'DIV_NAME_E Transportation',\n",
              "       'DIV_NAME_EDUCATION BLOCK GRANTS', 'DIV_NAME_Education Block Grants',\n",
              "       'DIV_NAME_Educator Support', 'DIV_NAME_OTHER ITEMS',\n",
              "       'DIV_NAME_Office of Early Learning', 'DIV_NAME_Office of the Secretary',\n",
              "       'DIV_NAME_Operations Support', 'DIV_NAME_Other Items',\n",
              "       'DIV_NAME_Professional Standards Board',\n",
              "       'DIV_NAME_Public School Transportation',\n",
              "       'DIV_NAME_SPECIAL NEEDS PROGRAMS', 'DIV_NAME_Special Needs Programs',\n",
              "       'DIV_NAME_State Board of Education', 'DIV_NAME_Student Support',\n",
              "       'DIV_NAME_TRANSPORTATION', 'DIV_NAME_Transportation',\n",
              "       'TRANS_DT_month_1', 'TRANS_DT_month_10', 'TRANS_DT_month_11',\n",
              "       'TRANS_DT_month_12', 'TRANS_DT_month_2', 'TRANS_DT_month_3',\n",
              "       'TRANS_DT_month_4', 'TRANS_DT_month_5', 'TRANS_DT_month_6',\n",
              "       'TRANS_DT_month_7', 'TRANS_DT_month_8', 'TRANS_DT_month_9',\n",
              "       'TRANS_DT_weekday_0', 'TRANS_DT_weekday_1', 'TRANS_DT_weekday_2',\n",
              "       'TRANS_DT_weekday_3', 'TRANS_DT_weekday_4', 'TRANS_DT_weekday_5',\n",
              "       'TRANS_DT_weekday_6', 'TRANS_DT_is_month_end_0',\n",
              "       'TRANS_DT_is_month_end_1', 'TRANS_DT_is_month_start_0',\n",
              "       'TRANS_DT_is_month_start_1'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xiOuM1syBMuw"
      },
      "source": [
        "iforest = create_model('iforest')"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "160rc-x-BMux",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "33e6e478-552f-46b1-8aba-e90c5adeb15e"
      },
      "source": [
        "r = assign_model(iforest)\n",
        "r.head()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>FISCAL_YEAR</th>\n",
              "      <th>FISCAL_PERIOD</th>\n",
              "      <th>DEPT_NAME</th>\n",
              "      <th>DIV_NAME</th>\n",
              "      <th>MERCHANT</th>\n",
              "      <th>CAT_DESCR</th>\n",
              "      <th>TRANS_DT</th>\n",
              "      <th>MERCHANDISE_AMT</th>\n",
              "      <th>Anomaly</th>\n",
              "      <th>Anomaly_Score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>DOUBLETREE HOTELS WASHING</td>\n",
              "      <td>LODGING</td>\n",
              "      <td>6/3/2014</td>\n",
              "      <td>-5.50</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.081450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>18.31</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.071574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>21.61</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.071574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>22.39</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.071574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>DEPT OF EDUCATION</td>\n",
              "      <td>DEPARTMENT OF EDUCATION</td>\n",
              "      <td>HYATT REGENCY NW ORLE F/B</td>\n",
              "      <td>EATING PLACES RESTAURANTS</td>\n",
              "      <td>6/26/2014</td>\n",
              "      <td>5.44</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.071310</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   FISCAL_YEAR  FISCAL_PERIOD  ... Anomaly Anomaly_Score\n",
              "0         2015              1  ...       0     -0.081450\n",
              "1         2015              1  ...       0     -0.071574\n",
              "2         2015              1  ...       0     -0.071574\n",
              "3         2015              1  ...       0     -0.071574\n",
              "4         2015              1  ...       0     -0.071310\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "nsEFIQ7xlu-d",
        "outputId": "7eb09908-f3a5-47b0-81f6-ce44009caade"
      },
      "source": [
        "get_config('X')"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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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>FISCAL_YEAR</th>\n",
              "      <th>FISCAL_PERIOD</th>\n",
              "      <th>MERCHANT</th>\n",
              "      <th>MERCHANDISE_AMT</th>\n",
              "      <th>DEPT_NAME_DEPT OF EDUCATION</th>\n",
              "      <th>DIV_NAME_ADVISORY COUNCIL</th>\n",
              "      <th>DIV_NAME_Academic Support</th>\n",
              "      <th>DIV_NAME_Adult Education and Work Force</th>\n",
              "      <th>DIV_NAME_DEPARTMENT OF EDUCATION</th>\n",
              "      <th>DIV_NAME_DRIVER TRAINING</th>\n",
              "      <th>DIV_NAME_Department of Education</th>\n",
              "      <th>DIV_NAME_Driver Training</th>\n",
              "      <th>DIV_NAME_E Education Block Grants</th>\n",
              "      <th>DIV_NAME_E Transportation</th>\n",
              "      <th>DIV_NAME_EDUCATION BLOCK GRANTS</th>\n",
              "      <th>DIV_NAME_Education Block Grants</th>\n",
              "      <th>DIV_NAME_Educator Support</th>\n",
              "      <th>DIV_NAME_OTHER ITEMS</th>\n",
              "      <th>DIV_NAME_Office of Early Learning</th>\n",
              "      <th>DIV_NAME_Office of the Secretary</th>\n",
              "      <th>DIV_NAME_Operations Support</th>\n",
              "      <th>DIV_NAME_Other Items</th>\n",
              "      <th>DIV_NAME_Professional Standards Board</th>\n",
              "      <th>DIV_NAME_Public School Transportation</th>\n",
              "      <th>DIV_NAME_SPECIAL NEEDS PROGRAMS</th>\n",
              "      <th>DIV_NAME_Special Needs Programs</th>\n",
              "      <th>DIV_NAME_State Board of Education</th>\n",
              "      <th>DIV_NAME_Student Support</th>\n",
              "      <th>DIV_NAME_TRANSPORTATION</th>\n",
              "      <th>DIV_NAME_Transportation</th>\n",
              "      <th>TRANS_DT_month_1</th>\n",
              "      <th>TRANS_DT_month_10</th>\n",
              "      <th>TRANS_DT_month_11</th>\n",
              "      <th>TRANS_DT_month_12</th>\n",
              "      <th>TRANS_DT_month_2</th>\n",
              "      <th>TRANS_DT_month_3</th>\n",
              "      <th>TRANS_DT_month_4</th>\n",
              "      <th>TRANS_DT_month_5</th>\n",
              "      <th>TRANS_DT_month_6</th>\n",
              "      <th>TRANS_DT_month_7</th>\n",
              "      <th>TRANS_DT_month_8</th>\n",
              "      <th>TRANS_DT_month_9</th>\n",
              "      <th>TRANS_DT_weekday_0</th>\n",
              "      <th>TRANS_DT_weekday_1</th>\n",
              "      <th>TRANS_DT_weekday_2</th>\n",
              "      <th>TRANS_DT_weekday_3</th>\n",
              "      <th>TRANS_DT_weekday_4</th>\n",
              "      <th>TRANS_DT_weekday_5</th>\n",
              "      <th>TRANS_DT_weekday_6</th>\n",
              "      <th>TRANS_DT_is_month_end_0</th>\n",
              "      <th>TRANS_DT_is_month_end_1</th>\n",
              "      <th>TRANS_DT_is_month_start_0</th>\n",
              "      <th>TRANS_DT_is_month_start_1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2015.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>-5.500000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2015.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>18.309999</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2015.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>21.610001</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2015.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>22.389999</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.440000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</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",
              "      <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",
              "      <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>15151</th>\n",
              "      <td>2020.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>52.580002</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15152</th>\n",
              "      <td>2020.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>14.910000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15153</th>\n",
              "      <td>2020.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>111.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15154</th>\n",
              "      <td>2020.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>99.989998</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15155</th>\n",
              "      <td>2020.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>99.989998</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>15156 rows × 53 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       FISCAL_YEAR  ...  TRANS_DT_is_month_start_1\n",
              "0           2015.0  ...                        0.0\n",
              "1           2015.0  ...                        0.0\n",
              "2           2015.0  ...                        0.0\n",
              "3           2015.0  ...                        0.0\n",
              "4           2015.0  ...                        0.0\n",
              "...            ...  ...                        ...\n",
              "15151       2020.0  ...                        0.0\n",
              "15152       2020.0  ...                        0.0\n",
              "15153       2020.0  ...                        0.0\n",
              "15154       2020.0  ...                        0.0\n",
              "15155       2020.0  ...                        0.0\n",
              "\n",
              "[15156 rows x 53 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-eBM7_jNBMuy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "5730be21-3328-43fb-cee5-4738f837ebbb"
      },
      "source": [
        "r['Anomaly_Score'].hist(bins=100, figsize=(10,6))"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7efe9318d790>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZSnhkne8j78d"
      },
      "source": [
        "--------------------------------"
      ]
    }
  ]
}