Exercise_2_Data_Wrangling.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/rizkyirw/MSIB/blob/main/Exercise_2_Data_Wrangling.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
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        "id": "EkiI3TAg4OU1"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "39Ck6KRo4Pt0",
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      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "df_household = pd.read_csv(\"/content/drive/MyDrive/household.csv\")\n",
        "\n",
        "df_household.tail(10)"
      ],
      "metadata": {
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          "height": 363
        },
        "id": "_bdQlh-q4TEs",
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      "execution_count": 3,
      "outputs": [
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              "       receipt_id  receipts_item_id     purchase_time              category  \\\n",
              "71990     5706802          17353920    12/8/2017 9:52  Sugar/Flavored Syrup   \n",
              "71991     5810097          17673421  12/20/2017 22:24  Sugar/Flavored Syrup   \n",
              "71992     5619551          17101654   12/3/2017 19:02  Sugar/Flavored Syrup   \n",
              "71993     5658236          17205706   12/6/2017 10:25  Sugar/Flavored Syrup   \n",
              "71994     5918414          17993057  12/28/2017 14:03  Sugar/Flavored Syrup   \n",
              "71995     5909305          17998610   12/27/2017 9:20  Sugar/Flavored Syrup   \n",
              "71996     5736299          17432379  12/13/2017 19:52  Sugar/Flavored Syrup   \n",
              "71997     5901144          18263665   12/27/2017 8:03  Sugar/Flavored Syrup   \n",
              "71998     5660630          17222218   12/7/2017 12:29  Sugar/Flavored Syrup   \n",
              "71999     5808147          17658789  12/19/2017 18:59  Sugar/Flavored Syrup   \n",
              "\n",
              "      sub_category       format  unit_price  discount  quantity yearmonth  \n",
              "71990        Sugar  supermarket     10700.0         0         2   2017-12  \n",
              "71991        Sugar   minimarket     12500.0         0         4   2017-12  \n",
              "71992        Sugar  supermarket     14600.0         0         1   2017-12  \n",
              "71993        Sugar   minimarket     12500.0         0         1   2017-12  \n",
              "71994        Sugar   minimarket     12500.0         0         1   2017-12  \n",
              "71995        Sugar   minimarket     25000.0         0         1   2017-12  \n",
              "71996        Sugar   minimarket     12500.0         0         1   2017-12  \n",
              "71997        Sugar   minimarket     12500.0         0         1   2017-12  \n",
              "71998        Sugar  hypermarket     12500.0         0         3   2017-12  \n",
              "71999        Sugar   minimarket     12500.0         0         3   2017-12  "
            ],
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              "      <td>12500.0</td>\n",
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      "execution_count": 4,
      "metadata": {
        "id": "YD8SBrtHx9vo"
      },
      "outputs": [],
      "source": [
        "#1. Buat kolom baru 'last_price' dengan valuenya berasal dari `unit_price*quantity*discount`\n",
        "df_household['last_price'] =  df_household['unit_price']*df_household['quantity']*df_household['discount']"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_household.head()"
      ],
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            "text/plain": [
              "   receipt_id  receipts_item_id    purchase_time category sub_category  \\\n",
              "0     9622257          32369294  7/22/2018 21:19     Rice         Rice   \n",
              "1     9446359          31885876  7/15/2018 16:17     Rice         Rice   \n",
              "2     9470290          31930241  7/15/2018 12:12     Rice         Rice   \n",
              "3     9643416          32418582   7/24/2018 8:27     Rice         Rice   \n",
              "4     9692093          32561236  7/26/2018 11:28     Rice         Rice   \n",
              "\n",
              "        format  unit_price  discount  quantity yearmonth  last_price  \n",
              "0  supermarket    128000.0         0         1   2018-07         0.0  \n",
              "1   minimarket    102750.0         0         1   2018-07         0.0  \n",
              "2  supermarket     64000.0         0         3   2018-07         0.0  \n",
              "3   minimarket     65000.0         0         1   2018-07         0.0  \n",
              "4  supermarket    124500.0         0         1   2018-07         0.0  "
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              "      <td>Rice</td>\n",
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              "      <td>7/15/2018 12:12</td>\n",
              "      <td>Rice</td>\n",
              "      <td>Rice</td>\n",
              "      <td>supermarket</td>\n",
              "      <td>64000.0</td>\n",
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              "      <td>2018-07</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>9643416</td>\n",
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              "      <td>Rice</td>\n",
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              "      <th>4</th>\n",
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              "      <td>Rice</td>\n",
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              "      <td>1</td>\n",
              "      <td>2018-07</td>\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#2. Buat kolom baru 'test' dengan valuenya = 1\n",
        "df_household['test'] = 1"
      ],
      "metadata": {
        "id": "Jvv4eQ4tyAZa"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_household.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qFOENLJDyBjq",
        "outputId": "aecc86af-491b-44e1-ecd7-5d7848da721e"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 72000 entries, 0 to 71999\n",
            "Data columns (total 12 columns):\n",
            " #   Column            Non-Null Count  Dtype  \n",
            "---  ------            --------------  -----  \n",
            " 0   receipt_id        72000 non-null  int64  \n",
            " 1   receipts_item_id  72000 non-null  int64  \n",
            " 2   purchase_time     72000 non-null  object \n",
            " 3   category          72000 non-null  object \n",
            " 4   sub_category      72000 non-null  object \n",
            " 5   format            72000 non-null  object \n",
            " 6   unit_price        72000 non-null  float64\n",
            " 7   discount          72000 non-null  int64  \n",
            " 8   quantity          72000 non-null  int64  \n",
            " 9   yearmonth         72000 non-null  object \n",
            " 10  last_price        72000 non-null  float64\n",
            " 11  test              72000 non-null  int64  \n",
            "dtypes: float64(2), int64(5), object(5)\n",
            "memory usage: 6.6+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#3. Drop kolom test tersebut\n",
        "df_household.drop('test', axis=1, inplace=True)"
      ],
      "metadata": {
        "id": "qoQf4CjZyCo2"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_household.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vHlgDA3uyEZ-",
        "outputId": "f7e6134a-fe40-47fd-c081-c20b4d8fca45"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 72000 entries, 0 to 71999\n",
            "Data columns (total 11 columns):\n",
            " #   Column            Non-Null Count  Dtype  \n",
            "---  ------            --------------  -----  \n",
            " 0   receipt_id        72000 non-null  int64  \n",
            " 1   receipts_item_id  72000 non-null  int64  \n",
            " 2   purchase_time     72000 non-null  object \n",
            " 3   category          72000 non-null  object \n",
            " 4   sub_category      72000 non-null  object \n",
            " 5   format            72000 non-null  object \n",
            " 6   unit_price        72000 non-null  float64\n",
            " 7   discount          72000 non-null  int64  \n",
            " 8   quantity          72000 non-null  int64  \n",
            " 9   yearmonth         72000 non-null  object \n",
            " 10  last_price        72000 non-null  float64\n",
            "dtypes: float64(2), int64(4), object(5)\n",
            "memory usage: 6.0+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#4. Drop rows 5 baris terakhir\n",
        "df_household.drop(df_household.index[-5:])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "pjot29dKyFlN",
        "outputId": "4f2027ae-1b35-4be0-c7d3-aefad8377dd9"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "       receipt_id  receipts_item_id     purchase_time              category  \\\n",
              "0         9622257          32369294   7/22/2018 21:19                  Rice   \n",
              "1         9446359          31885876   7/15/2018 16:17                  Rice   \n",
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              "3         9643416          32418582    7/24/2018 8:27                  Rice   \n",
              "4         9692093          32561236   7/26/2018 11:28                  Rice   \n",
              "...           ...               ...               ...                   ...   \n",
              "71990     5706802          17353920    12/8/2017 9:52  Sugar/Flavored Syrup   \n",
              "71991     5810097          17673421  12/20/2017 22:24  Sugar/Flavored Syrup   \n",
              "71992     5619551          17101654   12/3/2017 19:02  Sugar/Flavored Syrup   \n",
              "71993     5658236          17205706   12/6/2017 10:25  Sugar/Flavored Syrup   \n",
              "71994     5918414          17993057  12/28/2017 14:03  Sugar/Flavored Syrup   \n",
              "\n",
              "      sub_category       format  unit_price  discount  quantity yearmonth  \\\n",
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              "4             Rice  supermarket    124500.0         0         1   2018-07   \n",
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              "71991        Sugar   minimarket     12500.0         0         4   2017-12   \n",
              "71992        Sugar  supermarket     14600.0         0         1   2017-12   \n",
              "71993        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "71994        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
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      "cell_type": "code",
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        "df_household.index[-5:]"
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      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RangeIndex(start=71995, stop=72000, step=1)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_household.tail()"
      ],
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      },
      "execution_count": 12,
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        {
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          "data": {
            "text/plain": [
              "       receipt_id  receipts_item_id     purchase_time              category  \\\n",
              "71995     5909305          17998610   12/27/2017 9:20  Sugar/Flavored Syrup   \n",
              "71996     5736299          17432379  12/13/2017 19:52  Sugar/Flavored Syrup   \n",
              "71997     5901144          18263665   12/27/2017 8:03  Sugar/Flavored Syrup   \n",
              "71998     5660630          17222218   12/7/2017 12:29  Sugar/Flavored Syrup   \n",
              "71999     5808147          17658789  12/19/2017 18:59  Sugar/Flavored Syrup   \n",
              "\n",
              "      sub_category       format  unit_price  discount  quantity yearmonth  \\\n",
              "71995        Sugar   minimarket     25000.0         0         1   2017-12   \n",
              "71996        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "71997        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "71998        Sugar  hypermarket     12500.0         0         3   2017-12   \n",
              "71999        Sugar   minimarket     12500.0         0         3   2017-12   \n",
              "\n",
              "       last_price  \n",
              "71995         0.0  \n",
              "71996         0.0  \n",
              "71997         0.0  \n",
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              "      <td>12500.0</td>\n",
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              "      <th>71998</th>\n",
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              "      <td>hypermarket</td>\n",
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              "      <td>0</td>\n",
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              "      <td>Sugar/Flavored Syrup</td>\n",
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              "      <td>minimarket</td>\n",
              "      <td>12500.0</td>\n",
              "      <td>0</td>\n",
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              "      <td>2017-12</td>\n",
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    {
      "cell_type": "code",
      "source": [
        "# 4. Cara 2\n",
        "df_household.drop([71995, 71996, 71997, 71998, 71999], axis=0, inplace=True)\n",
        "df_household.head()\n",
        "\n",
        "df_household.drop"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eaWbGRrqM-FA",
        "outputId": "03458857-2d2f-41d8-cba8-0bd63f508483"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.drop of        receipt_id  receipts_item_id     purchase_time              category  \\\n",
              "0         9622257          32369294   7/22/2018 21:19                  Rice   \n",
              "1         9446359          31885876   7/15/2018 16:17                  Rice   \n",
              "2         9470290          31930241   7/15/2018 12:12                  Rice   \n",
              "3         9643416          32418582    7/24/2018 8:27                  Rice   \n",
              "4         9692093          32561236   7/26/2018 11:28                  Rice   \n",
              "...           ...               ...               ...                   ...   \n",
              "71990     5706802          17353920    12/8/2017 9:52  Sugar/Flavored Syrup   \n",
              "71991     5810097          17673421  12/20/2017 22:24  Sugar/Flavored Syrup   \n",
              "71992     5619551          17101654   12/3/2017 19:02  Sugar/Flavored Syrup   \n",
              "71993     5658236          17205706   12/6/2017 10:25  Sugar/Flavored Syrup   \n",
              "71994     5918414          17993057  12/28/2017 14:03  Sugar/Flavored Syrup   \n",
              "\n",
              "      sub_category       format  unit_price  discount  quantity yearmonth  \\\n",
              "0             Rice  supermarket    128000.0         0         1   2018-07   \n",
              "1             Rice   minimarket    102750.0         0         1   2018-07   \n",
              "2             Rice  supermarket     64000.0         0         3   2018-07   \n",
              "3             Rice   minimarket     65000.0         0         1   2018-07   \n",
              "4             Rice  supermarket    124500.0         0         1   2018-07   \n",
              "...            ...          ...         ...       ...       ...       ...   \n",
              "71990        Sugar  supermarket     10700.0         0         2   2017-12   \n",
              "71991        Sugar   minimarket     12500.0         0         4   2017-12   \n",
              "71992        Sugar  supermarket     14600.0         0         1   2017-12   \n",
              "71993        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "71994        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "\n",
              "       last_price  \n",
              "0             0.0  \n",
              "1             0.0  \n",
              "2             0.0  \n",
              "3             0.0  \n",
              "4             0.0  \n",
              "...           ...  \n",
              "71990         0.0  \n",
              "71991         0.0  \n",
              "71992         0.0  \n",
              "71993         0.0  \n",
              "71994         0.0  \n",
              "\n",
              "[71995 rows x 11 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Filter table based on value -> df_household[tulis kondisinya: select_kolom ==/>/</!=/dll <value>]"
      ],
      "metadata": {
        "id": "unMnKhSqNAP-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#select_kolom ==/>/</!=/dll <value>\n",
        "\n",
        "df_household['quantity'] > 4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3GQn1CE2NrOR",
        "outputId": "b48c9441-dba5-453c-99f0-9a548c5bd301"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        False\n",
              "1        False\n",
              "2        False\n",
              "3        False\n",
              "4        False\n",
              "         ...  \n",
              "71990    False\n",
              "71991    False\n",
              "71992    False\n",
              "71993    False\n",
              "71994    False\n",
              "Name: quantity, Length: 71995, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#tolong drop data dari table df_household ketika quantitynya lebih dari 5\n",
        "\n",
        "test3 = df_household[df_household['quantity'] < 5]\n",
        "test3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "gbJ05p7HNtBl",
        "outputId": "59a2e1b5-f32b-4cb4-e93f-5435ec5be5a1"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       receipt_id  receipts_item_id     purchase_time              category  \\\n",
              "0         9622257          32369294   7/22/2018 21:19                  Rice   \n",
              "1         9446359          31885876   7/15/2018 16:17                  Rice   \n",
              "2         9470290          31930241   7/15/2018 12:12                  Rice   \n",
              "3         9643416          32418582    7/24/2018 8:27                  Rice   \n",
              "4         9692093          32561236   7/26/2018 11:28                  Rice   \n",
              "...           ...               ...               ...                   ...   \n",
              "71990     5706802          17353920    12/8/2017 9:52  Sugar/Flavored Syrup   \n",
              "71991     5810097          17673421  12/20/2017 22:24  Sugar/Flavored Syrup   \n",
              "71992     5619551          17101654   12/3/2017 19:02  Sugar/Flavored Syrup   \n",
              "71993     5658236          17205706   12/6/2017 10:25  Sugar/Flavored Syrup   \n",
              "71994     5918414          17993057  12/28/2017 14:03  Sugar/Flavored Syrup   \n",
              "\n",
              "      sub_category       format  unit_price  discount  quantity yearmonth  \\\n",
              "0             Rice  supermarket    128000.0         0         1   2018-07   \n",
              "1             Rice   minimarket    102750.0         0         1   2018-07   \n",
              "2             Rice  supermarket     64000.0         0         3   2018-07   \n",
              "3             Rice   minimarket     65000.0         0         1   2018-07   \n",
              "4             Rice  supermarket    124500.0         0         1   2018-07   \n",
              "...            ...          ...         ...       ...       ...       ...   \n",
              "71990        Sugar  supermarket     10700.0         0         2   2017-12   \n",
              "71991        Sugar   minimarket     12500.0         0         4   2017-12   \n",
              "71992        Sugar  supermarket     14600.0         0         1   2017-12   \n",
              "71993        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "71994        Sugar   minimarket     12500.0         0         1   2017-12   \n",
              "\n",
              "       last_price  \n",
              "0             0.0  \n",
              "1             0.0  \n",
              "2             0.0  \n",
              "3             0.0  \n",
              "4             0.0  \n",
              "...           ...  \n",
              "71990         0.0  \n",
              "71991         0.0  \n",
              "71992         0.0  \n",
              "71993         0.0  \n",
              "71994         0.0  \n",
              "\n",
              "[69989 rows x 11 columns]"
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              "      <td>7/15/2018 12:12</td>\n",
              "      <td>Rice</td>\n",
              "      <td>Rice</td>\n",
              "      <td>supermarket</td>\n",
              "      <td>64000.0</td>\n",
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              "      <th>3</th>\n",
              "      <td>9643416</td>\n",
              "      <td>32418582</td>\n",
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              "      <td>65000.0</td>\n",
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              "      <td>2018-07</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9692093</td>\n",
              "      <td>32561236</td>\n",
              "      <td>7/26/2018 11:28</td>\n",
              "      <td>Rice</td>\n",
              "      <td>Rice</td>\n",
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              "      <td>124500.0</td>\n",
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              "      <th>71990</th>\n",
              "      <td>5706802</td>\n",
              "      <td>17353920</td>\n",
              "      <td>12/8/2017 9:52</td>\n",
              "      <td>Sugar/Flavored Syrup</td>\n",
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              "      <td>10700.0</td>\n",
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              "      <td>2017-12</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>71991</th>\n",
              "      <td>5810097</td>\n",
              "      <td>17673421</td>\n",
              "      <td>12/20/2017 22:24</td>\n",
              "      <td>Sugar/Flavored Syrup</td>\n",
              "      <td>Sugar</td>\n",
              "      <td>minimarket</td>\n",
              "      <td>12500.0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>2017-12</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>71992</th>\n",
              "      <td>5619551</td>\n",
              "      <td>17101654</td>\n",
              "      <td>12/3/2017 19:02</td>\n",
              "      <td>Sugar/Flavored Syrup</td>\n",
              "      <td>Sugar</td>\n",
              "      <td>supermarket</td>\n",
              "      <td>14600.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2017-12</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>71993</th>\n",
              "      <td>5658236</td>\n",
              "      <td>17205706</td>\n",
              "      <td>12/6/2017 10:25</td>\n",
              "      <td>Sugar/Flavored Syrup</td>\n",
              "      <td>Sugar</td>\n",
              "      <td>minimarket</td>\n",
              "      <td>12500.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2017-12</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>71994</th>\n",
              "      <td>5918414</td>\n",
              "      <td>17993057</td>\n",
              "      <td>12/28/2017 14:03</td>\n",
              "      <td>Sugar/Flavored Syrup</td>\n",
              "      <td>Sugar</td>\n",
              "      <td>minimarket</td>\n",
              "      <td>12500.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2017-12</td>\n",
              "      <td>0.0</td>\n",
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              "<p>69989 rows × 11 columns</p>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#5. Drop value ketika last_price nya kurang dari 10000\n",
        "df_household = df_household[df_household['last_price'] >= 10000]\n",
        "df_household"
      ],
      "metadata": {
        "id": "YHJm4Z0LyJNA",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "3ce20e84-4453-4227-d23b-7aefa2337b9b"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       receipt_id  receipts_item_id     purchase_time              category  \\\n",
              "23        9767244          32763935    7/29/2018 8:25                  Rice   \n",
              "43        9483559          31978405   7/16/2018 16:24                  Rice   \n",
              "48        9841041          33010608    7/29/2018 8:21                  Rice   \n",
              "55        9284943          31450853    7/6/2018 12:05                  Rice   \n",
              "72        9853312          33070898   7/30/2018 13:54                  Rice   \n",
              "...           ...               ...               ...                   ...   \n",
              "71935     5737076          17437723  12/13/2017 14:13  Sugar/Flavored Syrup   \n",
              "71941     5613876          17044297   12/3/2017 16:33  Sugar/Flavored Syrup   \n",
              "71956     5681770          17293166   12/8/2017 11:16  Sugar/Flavored Syrup   \n",
              "71970     5872479          17910741  12/24/2017 13:14  Sugar/Flavored Syrup   \n",
              "71977     5678339          17317824   12/8/2017 17:11  Sugar/Flavored Syrup   \n",
              "\n",
              "      sub_category       format  unit_price  discount  quantity yearmonth  \\\n",
              "23            Rice  supermarket     59900.0      4100         1   2018-07   \n",
              "43            Rice  supermarket     46900.0      4300         1   2018-07   \n",
              "48            Rice  supermarket    117900.0     10100         1   2018-07   \n",
              "55            Rice  supermarket     59900.0      4100         1   2018-07   \n",
              "72            Rice  supermarket    119890.0      8110         1   2018-07   \n",
              "...            ...          ...         ...       ...       ...       ...   \n",
              "71935        Sugar   minimarket     12200.0       600         2   2017-12   \n",
              "71941        Sugar  hypermarket     12000.0      1000         2   2017-12   \n",
              "71956        Sugar  supermarket     12000.0      1000         2   2017-12   \n",
              "71970        Sugar  hypermarket     11500.0      6000         6   2017-12   \n",
              "71977        Sugar  hypermarket     11990.0       260         1   2017-12   \n",
              "\n",
              "         last_price  \n",
              "23     2.455900e+08  \n",
              "43     2.016700e+08  \n",
              "48     1.190790e+09  \n",
              "55     2.455900e+08  \n",
              "72     9.723079e+08  \n",
              "...             ...  \n",
              "71935  1.464000e+07  \n",
              "71941  2.400000e+07  \n",
              "71956  2.400000e+07  \n",
              "71970  4.140000e+08  \n",
              "71977  3.117400e+06  \n",
              "\n",
              "[11845 rows x 11 columns]"
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              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-17c42a18-1067-4de2-ab22-a23e2672aff3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-17c42a18-1067-4de2-ab22-a23e2672aff3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    }
  ]
}