combined_normalised_df.ipynb

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  "metadata": {
    "colab": {
      "name": "combined normalised_df.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNh++HEGwre4wS2btwomE1T",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/theAkhileshRai/Projects/blob/master/combined_normalised_df.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mCReZ4kBVEoM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import collections\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o4aPmwEMVSph",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df1 = pd.read_csv('/content/Normalised_Merge_df-2.csv',index_col=False)\n",
        "df1 = df1[df1.columns[1:]]\n",
        "df1.columns = df1.columns.str.replace(' ', '')\n",
        "df1['station'] = 'Cross Barr'\n",
        "\n",
        "df2 = pd.read_csv('/content/Normalised_Goliad_05.csv',index_col=False)\n",
        "df2 = df2[df2.columns[1:]]\n",
        "df2['station'] = 'Goliad'\n",
        "\n",
        "df3 = pd.read_csv('//content/Normalised_Hobbit_05.csv',index_col=False)\n",
        "df3 = df3[df3.columns[1:]]\n",
        "df3 = df3.replace(np.nan, 0)\n",
        "df3['station'] = 'Hobbit'\n",
        "\n",
        "df4 = pd.read_csv('/content/Normalised_Katy_05.csv',index_col=False)\n",
        "df4 = df4[df4.columns[1:]]\n",
        "df4['station'] = 'Katy'\n",
        "\n",
        "\n",
        "df5 = pd.read_csv('/content/Normalised_Lighting_05.csv',index_col=False)\n",
        "df5 = df5[df5.columns[1:]]\n",
        "df5['station'] = 'Lightning'\n",
        "\n",
        "\n",
        "df6 = pd.read_csv('/content/Normalised_Reagon_05.csv',index_col=False)\n",
        "df6 = df6[df6.columns[1:]]\n",
        "df6['station'] = 'Reagon'\n",
        "\n",
        "df7 = pd.read_csv('/content/Normalised_Turkey_05.csv',index_col=False)\n",
        "df7 = df7[df7.columns[1:]]\n",
        "df7['station'] = 'Reagon'\n",
        "\n",
        "\n",
        "#cross_bar_df3 = pd.read_csv('/content/Normalised_CroosBar_05.csv',index_col=False)\n",
        "#cross_bar_df3 = cross_bar_df3[cross_bar_df3.columns[1:13]]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KUWHGFgGYDeq",
        "colab_type": "code",
        "colab": {
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          "height": 313
        },
        "outputId": "5e491c47-4d3a-4b92-c31a-b82d265a3bd0"
      },
      "source": [
        "df1.head()"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>cyl</th>\n",
              "      <th>s_temp_crank</th>\n",
              "      <th>d_temp_crank</th>\n",
              "      <th>s_pressure_crank</th>\n",
              "      <th>d_pressure_crank</th>\n",
              "      <th>rpm_crank</th>\n",
              "      <th>s_temp_mean</th>\n",
              "      <th>d_temp_mean</th>\n",
              "      <th>s_pressure_mean</th>\n",
              "      <th>d_pressure_mean</th>\n",
              "      <th>rpm_mean</th>\n",
              "      <th>y_true</th>\n",
              "      <th>leak_level</th>\n",
              "      <th>station</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>05/04/19 2:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.666534</td>\n",
              "      <td>2.080444</td>\n",
              "      <td>3.220836</td>\n",
              "      <td>10.105964</td>\n",
              "      <td>10.063987</td>\n",
              "      <td>0.666534</td>\n",
              "      <td>2.053527</td>\n",
              "      <td>3.307406</td>\n",
              "      <td>10.142075</td>\n",
              "      <td>10.063987</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>05/04/19 3:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.716066</td>\n",
              "      <td>2.153494</td>\n",
              "      <td>3.135203</td>\n",
              "      <td>9.998847</td>\n",
              "      <td>10.075669</td>\n",
              "      <td>0.716066</td>\n",
              "      <td>2.120434</td>\n",
              "      <td>3.243347</td>\n",
              "      <td>10.053597</td>\n",
              "      <td>10.075669</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>05/04/19 4:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.687551</td>\n",
              "      <td>2.142630</td>\n",
              "      <td>3.066270</td>\n",
              "      <td>9.954641</td>\n",
              "      <td>10.081478</td>\n",
              "      <td>0.687551</td>\n",
              "      <td>2.105328</td>\n",
              "      <td>3.181119</td>\n",
              "      <td>10.001306</td>\n",
              "      <td>10.081478</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>05/04/19 5:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.686916</td>\n",
              "      <td>2.140013</td>\n",
              "      <td>3.071850</td>\n",
              "      <td>9.956670</td>\n",
              "      <td>10.054274</td>\n",
              "      <td>0.686916</td>\n",
              "      <td>2.101800</td>\n",
              "      <td>3.191233</td>\n",
              "      <td>10.008420</td>\n",
              "      <td>10.054274</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>05/04/19 6:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.698125</td>\n",
              "      <td>2.156244</td>\n",
              "      <td>3.063865</td>\n",
              "      <td>9.961413</td>\n",
              "      <td>10.091478</td>\n",
              "      <td>0.698125</td>\n",
              "      <td>2.117328</td>\n",
              "      <td>3.183534</td>\n",
              "      <td>10.009700</td>\n",
              "      <td>10.091478</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            time  cyl  s_temp_crank  ...  y_true  leak_level     station\n",
              "0  05/04/19 2:30    1      0.666534  ...       1           2  Cross Barr\n",
              "1  05/04/19 3:30    1      0.716066  ...       1           2  Cross Barr\n",
              "2  05/04/19 4:30    1      0.687551  ...       1           2  Cross Barr\n",
              "3  05/04/19 5:30    1      0.686916  ...       1           2  Cross Barr\n",
              "4  05/04/19 6:30    1      0.698125  ...       1           2  Cross Barr\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 53
        }
      ]
    },
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          "height": 104
        },
        "outputId": "ed45350e-2ef7-4c38-8871-1984e4c6a208"
      },
      "source": [
        "df1.columns"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['time', 'cyl', 's_temp_crank', 'd_temp_crank', 's_pressure_crank',\n",
              "       'd_pressure_crank', 'rpm_crank', 's_temp_mean', 'd_temp_mean',\n",
              "       's_pressure_mean', 'd_pressure_mean', 'rpm_mean', 'y_true',\n",
              "       'leak_level', 'station'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
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        "id": "ypc23rmeeW0a",
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          "height": 313
        },
        "outputId": "d25d054c-b191-4526-de7f-f7538c5539b1"
      },
      "source": [
        "df2.head()"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>cyl</th>\n",
              "      <th>s_temp_crank</th>\n",
              "      <th>d_temp_crank</th>\n",
              "      <th>s_pressure_crank</th>\n",
              "      <th>d_pressure_crank</th>\n",
              "      <th>rpm_crank</th>\n",
              "      <th>s_temp_mean</th>\n",
              "      <th>d_temp_mean</th>\n",
              "      <th>s_pressure_mean</th>\n",
              "      <th>d_pressure_mean</th>\n",
              "      <th>rpm_mean</th>\n",
              "      <th>y_true</th>\n",
              "      <th>leak_level</th>\n",
              "      <th>station</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>01/01/19 0:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.352399</td>\n",
              "      <td>1.426130</td>\n",
              "      <td>7.323812</td>\n",
              "      <td>14.003673</td>\n",
              "      <td>12.290037</td>\n",
              "      <td>0.352399</td>\n",
              "      <td>1.417231</td>\n",
              "      <td>7.353063</td>\n",
              "      <td>13.985577</td>\n",
              "      <td>12.290037</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Goliad</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>01/01/19 1:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.342632</td>\n",
              "      <td>1.409432</td>\n",
              "      <td>7.342196</td>\n",
              "      <td>13.987693</td>\n",
              "      <td>12.234907</td>\n",
              "      <td>0.342632</td>\n",
              "      <td>1.402894</td>\n",
              "      <td>7.367249</td>\n",
              "      <td>13.980752</td>\n",
              "      <td>12.234907</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Goliad</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>01/01/19 2:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.333028</td>\n",
              "      <td>1.398729</td>\n",
              "      <td>7.319715</td>\n",
              "      <td>13.943917</td>\n",
              "      <td>12.281904</td>\n",
              "      <td>0.333028</td>\n",
              "      <td>1.396863</td>\n",
              "      <td>7.343025</td>\n",
              "      <td>13.971357</td>\n",
              "      <td>12.281904</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Goliad</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>01/01/19 3:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.315652</td>\n",
              "      <td>1.378132</td>\n",
              "      <td>7.350524</td>\n",
              "      <td>13.984950</td>\n",
              "      <td>12.316841</td>\n",
              "      <td>0.315652</td>\n",
              "      <td>1.374157</td>\n",
              "      <td>7.373479</td>\n",
              "      <td>13.994667</td>\n",
              "      <td>12.316841</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Goliad</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>01/01/19 7:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.451939</td>\n",
              "      <td>1.541067</td>\n",
              "      <td>7.481886</td>\n",
              "      <td>14.355843</td>\n",
              "      <td>11.606204</td>\n",
              "      <td>0.451939</td>\n",
              "      <td>1.542423</td>\n",
              "      <td>7.535327</td>\n",
              "      <td>14.465096</td>\n",
              "      <td>11.606204</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Goliad</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            time  cyl  s_temp_crank  ...  y_true  leak_level  station\n",
              "0  01/01/19 0:30    1      0.352399  ...       0           0   Goliad\n",
              "1  01/01/19 1:30    1      0.342632  ...       0           0   Goliad\n",
              "2  01/01/19 2:30    1      0.333028  ...       0           0   Goliad\n",
              "3  01/01/19 3:30    1      0.315652  ...       0           0   Goliad\n",
              "4  01/01/19 7:30    1      0.451939  ...       0           0   Goliad\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Aps97qbteYIW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "outputId": "89c0616a-63cb-4f8a-d2c3-ece4b95572f1"
      },
      "source": [
        "df3.head()"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>cyl</th>\n",
              "      <th>s_temp_crank</th>\n",
              "      <th>d_temp_crank</th>\n",
              "      <th>s_pressure_crank</th>\n",
              "      <th>d_pressure_crank</th>\n",
              "      <th>rpm_crank</th>\n",
              "      <th>s_temp_mean</th>\n",
              "      <th>d_temp_mean</th>\n",
              "      <th>s_pressure_mean</th>\n",
              "      <th>d_pressure_mean</th>\n",
              "      <th>rpm_mean</th>\n",
              "      <th>y_true</th>\n",
              "      <th>leak_level</th>\n",
              "      <th>station</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>23/02/19 4:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.041658</td>\n",
              "      <td>0.309163</td>\n",
              "      <td>0.088923</td>\n",
              "      <td>0.404177</td>\n",
              "      <td>1.935182</td>\n",
              "      <td>0.041658</td>\n",
              "      <td>0.315062</td>\n",
              "      <td>0.089620</td>\n",
              "      <td>0.417038</td>\n",
              "      <td>1.934557</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Hobbit</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>23/02/19 5:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.043996</td>\n",
              "      <td>0.308594</td>\n",
              "      <td>0.088413</td>\n",
              "      <td>0.396981</td>\n",
              "      <td>1.936042</td>\n",
              "      <td>0.043996</td>\n",
              "      <td>0.315150</td>\n",
              "      <td>0.089053</td>\n",
              "      <td>0.410710</td>\n",
              "      <td>1.935261</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Hobbit</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>23/02/19 6:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.044308</td>\n",
              "      <td>0.312818</td>\n",
              "      <td>0.088497</td>\n",
              "      <td>0.404102</td>\n",
              "      <td>1.935808</td>\n",
              "      <td>0.044308</td>\n",
              "      <td>0.318225</td>\n",
              "      <td>0.089280</td>\n",
              "      <td>0.416284</td>\n",
              "      <td>1.934987</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Hobbit</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23/02/19 7:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.043919</td>\n",
              "      <td>0.309842</td>\n",
              "      <td>0.087955</td>\n",
              "      <td>0.398055</td>\n",
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              "    <tr>\n",
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              "      <td>23/02/19 8:30</td>\n",
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              "      <td>0.314058</td>\n",
              "      <td>0.087936</td>\n",
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              "</table>\n",
              "</div>"
            ],
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              "            time  cyl  s_temp_crank  ...  y_true  leak_level  station\n",
              "0  23/02/19 4:30    1      0.041658  ...     0.0         0.0   Hobbit\n",
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              "4  23/02/19 8:30    1      0.046833  ...     0.0         0.0   Hobbit\n",
              "\n",
              "[5 rows x 15 columns]"
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              "             time  cyl  s_temp_crank  ...  y_true  leak_level  station\n",
              "0   10/01/19 8:30    1      0.258961  ...       0           0     Katy\n",
              "1   10/01/19 9:30    1      0.252190  ...       0           0     Katy\n",
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              "\n",
              "[5 rows x 15 columns]"
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      "outputs": [
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              "      <td>0.361222</td>\n",
              "      <td>0.511394</td>\n",
              "      <td>1.798988</td>\n",
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              "      <td>0.067276</td>\n",
              "      <td>0.334847</td>\n",
              "      <td>0.572140</td>\n",
              "      <td>1.837768</td>\n",
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              "      <td>0.607145</td>\n",
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              "    <tr>\n",
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              "      <td>01/01/19 4:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.050350</td>\n",
              "      <td>0.326511</td>\n",
              "      <td>0.543435</td>\n",
              "      <td>1.831486</td>\n",
              "      <td>2.264437</td>\n",
              "      <td>0.050350</td>\n",
              "      <td>0.323512</td>\n",
              "      <td>0.575267</td>\n",
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              "            time  cyl  s_temp_crank  ...  y_true  leak_level    station\n",
              "0  01/01/19 0:30    1      0.074845  ...       0           0  Lightning\n",
              "1  01/01/19 1:30    1      0.072585  ...       0           0  Lightning\n",
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              "4  01/01/19 4:30    1      0.050350  ...       0           0  Lightning\n",
              "\n",
              "[5 rows x 15 columns]"
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      "source": [
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              "      <td>11.303658</td>\n",
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              "      <td>24/04/19 19:30</td>\n",
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              "      <td>11.303396</td>\n",
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              "      <td>-0.108994</td>\n",
              "      <td>-0.098437</td>\n",
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              "      <td>-0.121829</td>\n",
              "      <td>0.117812</td>\n",
              "      <td>11.309291</td>\n",
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              "    <tr>\n",
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              "      <td>24/04/19 21:30</td>\n",
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              "      <td>0.511111</td>\n",
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              "      <td>11.307875</td>\n",
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              "      <td>0.128907</td>\n",
              "      <td>11.307320</td>\n",
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            "text/plain": [
              "             time  cyl  s_temp_crank  ...  y_true  leak_level  station\n",
              "0  24/04/19 16:30    1      0.359371  ...       0           0   Reagon\n",
              "1  24/04/19 18:30    1      0.404163  ...       0           0   Reagon\n",
              "2  24/04/19 19:30    1      0.461680  ...       0           0   Reagon\n",
              "3  24/04/19 20:30    1      0.492692  ...       0           0   Reagon\n",
              "4  24/04/19 21:30    1      0.475864  ...       0           0   Reagon\n",
              "\n",
              "[5 rows x 15 columns]"
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          "height": 313
        },
        "outputId": "659e318f-049d-4516-818e-e19370a51bdb"
      },
      "source": [
        "df7.head()"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>cyl</th>\n",
              "      <th>s_temp_crank</th>\n",
              "      <th>d_temp_crank</th>\n",
              "      <th>s_pressure_crank</th>\n",
              "      <th>d_pressure_crank</th>\n",
              "      <th>rpm_crank</th>\n",
              "      <th>s_temp_mean</th>\n",
              "      <th>d_temp_mean</th>\n",
              "      <th>s_pressure_mean</th>\n",
              "      <th>d_pressure_mean</th>\n",
              "      <th>rpm_mean</th>\n",
              "      <th>y_true</th>\n",
              "      <th>leak_level</th>\n",
              "      <th>station</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>01/01/19 0:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.240118</td>\n",
              "      <td>0.345046</td>\n",
              "      <td>0.947764</td>\n",
              "      <td>1.069577</td>\n",
              "      <td>12.358909</td>\n",
              "      <td>0.240118</td>\n",
              "      <td>1.320083</td>\n",
              "      <td>0.901426</td>\n",
              "      <td>3.076177</td>\n",
              "      <td>12.358909</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Reagon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>01/01/19 1:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.259492</td>\n",
              "      <td>0.381999</td>\n",
              "      <td>0.886889</td>\n",
              "      <td>1.023905</td>\n",
              "      <td>12.361382</td>\n",
              "      <td>0.259492</td>\n",
              "      <td>1.357156</td>\n",
              "      <td>0.840248</td>\n",
              "      <td>2.957726</td>\n",
              "      <td>12.361382</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Reagon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>01/01/19 2:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.252180</td>\n",
              "      <td>0.374878</td>\n",
              "      <td>0.723645</td>\n",
              "      <td>0.845881</td>\n",
              "      <td>12.357089</td>\n",
              "      <td>0.252180</td>\n",
              "      <td>1.407982</td>\n",
              "      <td>0.646505</td>\n",
              "      <td>2.592744</td>\n",
              "      <td>12.357089</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Reagon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>01/01/19 3:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.213724</td>\n",
              "      <td>0.322137</td>\n",
              "      <td>0.750418</td>\n",
              "      <td>0.860661</td>\n",
              "      <td>12.351531</td>\n",
              "      <td>0.213724</td>\n",
              "      <td>1.345088</td>\n",
              "      <td>0.682092</td>\n",
              "      <td>2.657678</td>\n",
              "      <td>12.351531</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Reagon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>01/01/19 7:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.165952</td>\n",
              "      <td>0.290423</td>\n",
              "      <td>0.796574</td>\n",
              "      <td>0.928926</td>\n",
              "      <td>12.360173</td>\n",
              "      <td>0.165952</td>\n",
              "      <td>1.262580</td>\n",
              "      <td>0.737667</td>\n",
              "      <td>2.702684</td>\n",
              "      <td>12.360173</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Reagon</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            time  cyl  s_temp_crank  ...  y_true  leak_level  station\n",
              "0  01/01/19 0:30    1      0.240118  ...       0           0   Reagon\n",
              "1  01/01/19 1:30    1      0.259492  ...       0           0   Reagon\n",
              "2  01/01/19 2:30    1      0.252180  ...       0           0   Reagon\n",
              "3  01/01/19 3:30    1      0.213724  ...       0           0   Reagon\n",
              "4  01/01/19 7:30    1      0.165952  ...       0           0   Reagon\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wg2ztFxBo7PX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "merge_all_df = pd.concat([df1,df2,df3,df4,df5,df6,df7],join = 'inner' )"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "erst9HfKqnc4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "outputId": "de997aa1-e442-434a-d5fc-f45a39468a98"
      },
      "source": [
        "merge_all_df.head()"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>cyl</th>\n",
              "      <th>s_temp_crank</th>\n",
              "      <th>d_temp_crank</th>\n",
              "      <th>s_pressure_crank</th>\n",
              "      <th>d_pressure_crank</th>\n",
              "      <th>rpm_crank</th>\n",
              "      <th>s_temp_mean</th>\n",
              "      <th>d_temp_mean</th>\n",
              "      <th>s_pressure_mean</th>\n",
              "      <th>d_pressure_mean</th>\n",
              "      <th>rpm_mean</th>\n",
              "      <th>y_true</th>\n",
              "      <th>leak_level</th>\n",
              "      <th>station</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>05/04/19 2:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.666534</td>\n",
              "      <td>2.080444</td>\n",
              "      <td>3.220836</td>\n",
              "      <td>10.105964</td>\n",
              "      <td>10.063987</td>\n",
              "      <td>0.666534</td>\n",
              "      <td>2.053527</td>\n",
              "      <td>3.307406</td>\n",
              "      <td>10.142075</td>\n",
              "      <td>10.063987</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>05/04/19 3:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.716066</td>\n",
              "      <td>2.153494</td>\n",
              "      <td>3.135203</td>\n",
              "      <td>9.998847</td>\n",
              "      <td>10.075669</td>\n",
              "      <td>0.716066</td>\n",
              "      <td>2.120434</td>\n",
              "      <td>3.243347</td>\n",
              "      <td>10.053597</td>\n",
              "      <td>10.075669</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>05/04/19 4:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.687551</td>\n",
              "      <td>2.142630</td>\n",
              "      <td>3.066270</td>\n",
              "      <td>9.954641</td>\n",
              "      <td>10.081478</td>\n",
              "      <td>0.687551</td>\n",
              "      <td>2.105328</td>\n",
              "      <td>3.181119</td>\n",
              "      <td>10.001306</td>\n",
              "      <td>10.081478</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>05/04/19 5:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.686916</td>\n",
              "      <td>2.140013</td>\n",
              "      <td>3.071850</td>\n",
              "      <td>9.956670</td>\n",
              "      <td>10.054274</td>\n",
              "      <td>0.686916</td>\n",
              "      <td>2.101800</td>\n",
              "      <td>3.191233</td>\n",
              "      <td>10.008420</td>\n",
              "      <td>10.054274</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>05/04/19 6:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.698125</td>\n",
              "      <td>2.156244</td>\n",
              "      <td>3.063865</td>\n",
              "      <td>9.961413</td>\n",
              "      <td>10.091478</td>\n",
              "      <td>0.698125</td>\n",
              "      <td>2.117328</td>\n",
              "      <td>3.183534</td>\n",
              "      <td>10.009700</td>\n",
              "      <td>10.091478</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            time  cyl  s_temp_crank  ...  y_true  leak_level     station\n",
              "0  05/04/19 2:30    1      0.666534  ...     1.0         2.0  Cross Barr\n",
              "1  05/04/19 3:30    1      0.716066  ...     1.0         2.0  Cross Barr\n",
              "2  05/04/19 4:30    1      0.687551  ...     1.0         2.0  Cross Barr\n",
              "3  05/04/19 5:30    1      0.686916  ...     1.0         2.0  Cross Barr\n",
              "4  05/04/19 6:30    1      0.698125  ...     1.0         2.0  Cross Barr\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rH5nmZJTqrm1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "9bfd3886-f5d6-43fe-8380-ed0268f9e088"
      },
      "source": [
        "merge_all_df.columns"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['time', 'cyl', 's_temp_crank', 'd_temp_crank', 's_pressure_crank',\n",
              "       'd_pressure_crank', 'rpm_crank', 's_temp_mean', 'd_temp_mean',\n",
              "       's_pressure_mean', 'd_pressure_mean', 'rpm_mean', 'y_true',\n",
              "       'leak_level', 'station'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kZwXNhkrqw9j",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "merge_all_df = merge_all_df.reset_index(drop=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZmjjZFxerBUK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "outputId": "08a7634b-b67e-4e24-92bb-b0dba96808a2"
      },
      "source": [
        "merge_all_df.head()"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\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>time</th>\n",
              "      <th>cyl</th>\n",
              "      <th>s_temp_crank</th>\n",
              "      <th>d_temp_crank</th>\n",
              "      <th>s_pressure_crank</th>\n",
              "      <th>d_pressure_crank</th>\n",
              "      <th>rpm_crank</th>\n",
              "      <th>s_temp_mean</th>\n",
              "      <th>d_temp_mean</th>\n",
              "      <th>s_pressure_mean</th>\n",
              "      <th>d_pressure_mean</th>\n",
              "      <th>rpm_mean</th>\n",
              "      <th>y_true</th>\n",
              "      <th>leak_level</th>\n",
              "      <th>station</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>05/04/19 2:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.666534</td>\n",
              "      <td>2.080444</td>\n",
              "      <td>3.220836</td>\n",
              "      <td>10.105964</td>\n",
              "      <td>10.063987</td>\n",
              "      <td>0.666534</td>\n",
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              "      <td>3.307406</td>\n",
              "      <td>10.142075</td>\n",
              "      <td>10.063987</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>05/04/19 3:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.716066</td>\n",
              "      <td>2.153494</td>\n",
              "      <td>3.135203</td>\n",
              "      <td>9.998847</td>\n",
              "      <td>10.075669</td>\n",
              "      <td>0.716066</td>\n",
              "      <td>2.120434</td>\n",
              "      <td>3.243347</td>\n",
              "      <td>10.053597</td>\n",
              "      <td>10.075669</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>05/04/19 4:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.687551</td>\n",
              "      <td>2.142630</td>\n",
              "      <td>3.066270</td>\n",
              "      <td>9.954641</td>\n",
              "      <td>10.081478</td>\n",
              "      <td>0.687551</td>\n",
              "      <td>2.105328</td>\n",
              "      <td>3.181119</td>\n",
              "      <td>10.001306</td>\n",
              "      <td>10.081478</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>05/04/19 5:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.686916</td>\n",
              "      <td>2.140013</td>\n",
              "      <td>3.071850</td>\n",
              "      <td>9.956670</td>\n",
              "      <td>10.054274</td>\n",
              "      <td>0.686916</td>\n",
              "      <td>2.101800</td>\n",
              "      <td>3.191233</td>\n",
              "      <td>10.008420</td>\n",
              "      <td>10.054274</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>05/04/19 6:30</td>\n",
              "      <td>1</td>\n",
              "      <td>0.698125</td>\n",
              "      <td>2.156244</td>\n",
              "      <td>3.063865</td>\n",
              "      <td>9.961413</td>\n",
              "      <td>10.091478</td>\n",
              "      <td>0.698125</td>\n",
              "      <td>2.117328</td>\n",
              "      <td>3.183534</td>\n",
              "      <td>10.009700</td>\n",
              "      <td>10.091478</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Cross Barr</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            time  cyl  s_temp_crank  ...  y_true  leak_level     station\n",
              "0  05/04/19 2:30    1      0.666534  ...     1.0         2.0  Cross Barr\n",
              "1  05/04/19 3:30    1      0.716066  ...     1.0         2.0  Cross Barr\n",
              "2  05/04/19 4:30    1      0.687551  ...     1.0         2.0  Cross Barr\n",
              "3  05/04/19 5:30    1      0.686916  ...     1.0         2.0  Cross Barr\n",
              "4  05/04/19 6:30    1      0.698125  ...     1.0         2.0  Cross Barr\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XRNHy-gMrHaB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "8c7f373b-e722-450b-ebd4-d3366a2a50e1"
      },
      "source": [
        "merge_all_df.shape"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(165861, 15)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2aOXS2XJsPuJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "merge_all_df.to_csv(\"/content/Combined_df.csv\")"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}