Final_project_know_your_data.ipynb

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              "   order_id  quantity                              item_name  \\\n",
              "0         1         1           Chips and Fresh Tomato Salsa   \n",
              "1         1         1                                   Izze   \n",
              "2         1         1                       Nantucket Nectar   \n",
              "3         1         1  Chips and Tomatillo-Green Chili Salsa   \n",
              "4         2         2                           Chicken Bowl   \n",
              "5         3         1                           Chicken Bowl   \n",
              "6         3         1                          Side of Chips   \n",
              "7         4         1                          Steak Burrito   \n",
              "8         4         1                       Steak Soft Tacos   \n",
              "9         5         1                          Steak Burrito   \n",
              "\n",
              "                                  choice_description item_price  \n",
              "0                                                NaN     $2.39   \n",
              "1                                       [Clementine]     $3.39   \n",
              "2                                            [Apple]     $3.39   \n",
              "3                                                NaN     $2.39   \n",
              "4  [Tomatillo-Red Chili Salsa (Hot), [Black Beans...    $16.98   \n",
              "5  [Fresh Tomato Salsa (Mild), [Rice, Cheese, Sou...    $10.98   \n",
              "6                                                NaN     $1.69   \n",
              "7  [Tomatillo Red Chili Salsa, [Fajita Vegetables...    $11.75   \n",
              "8  [Tomatillo Green Chili Salsa, [Pinto Beans, Ch...     $9.25   \n",
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              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 4622,\n  \"fields\": [\n    {\n      \"column\": \"order_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 528,\n        \"min\": 1,\n        \"max\": 1834,\n        \"num_unique_values\": 1834,\n        \"samples\": [\n          644,\n          333,\n          991\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 15,\n        \"num_unique_values\": 9,\n        \"samples\": [\n          8,\n          2,\n          15\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 50,\n        \"samples\": [\n          \"Barbacoa Burrito\",\n          \"Crispy Tacos\",\n          \"Chips and Roasted Chili Corn Salsa\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"choice_description\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1043,\n        \"samples\": [\n          \"[Roasted Chili Corn Salsa, [Black Beans, Sour Cream, Cheese, Guacamole]]\",\n          \"[Tomatillo Red Chili Salsa, [Guacamole, Cheese]]\",\n          \"[Fresh Tomato Salsa, [Rice, Cheese, Sour Cream, Guacamole, Lettuce]]\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_price\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 78,\n        \"samples\": [\n          \"$23.50 \",\n          \"$2.39 \",\n          \"$7.40 \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "data=pd.read_csv('/content/chipotle.tsv',sep='\\t')\n",
        "data.head(10)"
      ]
    },
    {
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      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "order_id               int64\n",
              "quantity               int64\n",
              "item_name             object\n",
              "choice_description    object\n",
              "item_price            object\n",
              "dtype: object"
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              "</div><br><label><b>dtype:</b> object</label>"
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      "execution_count": 3,
      "outputs": [
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 4622 entries, 0 to 4621\n",
            "Data columns (total 5 columns):\n",
            " #   Column              Non-Null Count  Dtype \n",
            "---  ------              --------------  ----- \n",
            " 0   order_id            4622 non-null   int64 \n",
            " 1   quantity            4622 non-null   int64 \n",
            " 2   item_name           4622 non-null   object\n",
            " 3   choice_description  3376 non-null   object\n",
            " 4   item_price          4622 non-null   object\n",
            "dtypes: int64(2), object(3)\n",
            "memory usage: 180.7+ KB\n"
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    {
      "cell_type": "code",
      "source": [
        "data.shape[0]  #no of observations in dataset"
      ],
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        },
        "id": "df9mHYeWQntZ",
        "outputId": "8adf2c8e-a2ae-49b0-e8b8-a1685a70e0fb"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4622"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape[1]  #no of columns in dataset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ahXjXHXsSKIe",
        "outputId": "319a4773-561d-4a60-8f26-a264d12adb2c"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.columns   #give the name of columns in dataset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qFyqdgIlStvV",
        "outputId": "a21787e8-fd9a-4bab-9756-7ad06685e1f7"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['order_id', 'quantity', 'item_name', 'choice_description',\n",
              "       'item_price'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.index    #gives the indexing idea of dataset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9XajSmasS8uG",
        "outputId": "3ec76ed2-fd32-4bd9-f0b2-94093956deab"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RangeIndex(start=0, stop=4622, step=1)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#most ordered item(sorted data according to quantity ordered)\n",
        "d=data.groupby('item_name')\n",
        "d=d.sum()\n",
        "d=d.sort_values(['quantity'],ascending=False)\n",
        "d.head(5)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "risStKE1THUc",
        "outputId": "1b379ec2-6a86-46e9-e534-5adbcbfca444"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     order_id  quantity  \\\n",
              "item_name                                 \n",
              "Chicken Bowl           713926       761   \n",
              "Chicken Burrito        497303       591   \n",
              "Chips and Guacamole    449959       506   \n",
              "Steak Burrito          328437       386   \n",
              "Canned Soft Drink      304753       351   \n",
              "\n",
              "                                                    choice_description  \\\n",
              "item_name                                                                \n",
              "Chicken Bowl         [Tomatillo-Red Chili Salsa (Hot), [Black Beans...   \n",
              "Chicken Burrito      [Tomatillo-Green Chili Salsa (Medium), [Pinto ...   \n",
              "Chips and Guacamole                                                  0   \n",
              "Steak Burrito        [Tomatillo Red Chili Salsa, [Fajita Vegetables...   \n",
              "Canned Soft Drink    [Coke][Sprite][Coke][Coke][Lemonade][Sprite][D...   \n",
              "\n",
              "                                                            item_price  \n",
              "item_name                                                               \n",
              "Chicken Bowl         $16.98 $10.98 $11.25 $8.75 $8.49 $11.25 $8.75 ...  \n",
              "Chicken Burrito      $8.49 $8.49 $10.98 $8.49 $10.98 $10.98 $8.75 $...  \n",
              "Chips and Guacamole  $4.45 $4.45 $4.45 $4.45 $4.45 $3.99 $4.45 $3.9...  \n",
              "Steak Burrito        $11.75 $9.25 $8.99 $11.75 $8.99 $8.99 $8.99 $8...  \n",
              "Canned Soft Drink    $1.25 $1.25 $1.25 $1.25 $1.25 $1.25 $1.25 $1.2...  "
            ],
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              "      <td>[Tomatillo-Red Chili Salsa (Hot), [Black Beans...</td>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "        document.querySelector('#df-445bedec-1c74-40f0-b501-adc34029d958 button.colab-df-convert');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-445bedec-1c74-40f0-b501-adc34029d958');\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",
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              "  .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "\n",
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              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "d",
              "summary": "{\n  \"name\": \"d\",\n  \"rows\": 50,\n  \"fields\": [\n    {\n      \"column\": \"item_name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 50,\n        \"samples\": [\n          \"Veggie Burrito\",\n          \"Veggie Soft Tacos\",\n          \"Barbacoa Soft Tacos\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"order_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 142559,\n        \"min\": 279,\n        \"max\": 713926,\n        \"num_unique_values\": 50,\n        \"samples\": [\n          80962,\n          5520,\n          18725\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 159,\n        \"min\": 1,\n        \"max\": 761,\n        \"num_unique_values\": 40,\n        \"samples\": [\n          56,\n          71,\n          87\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"choice_description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39,\n        \"samples\": [\n          \"[Braised Carnitas, Pinto Beans, [Sour Cream, Cheese, Cilantro-Lime Rice]][Adobo-Marinated and Grilled Steak, [Sour Cream, Salsa, Cheese, Cilantro-Lime Rice, Guacamole]]\",\n          \"[Adobo-Marinated and Grilled Steak][Adobo-Marinated and Grilled Chicken]\",\n          \"[Coke][Sprite][Coke][Coke][Lemonade][Sprite][Diet Coke][Coke][Coke][Coke][Sprite][Coke][Coke][Coke][Diet Coke][Lemonade][Coke][Diet Coke][Diet Coke][Diet Coke][Diet Coke][Nestea][Diet Coke][Coke][Coke][Lemonade][Coke][Coke][Diet Coke][Diet Coke][Lemonade][Lemonade][Diet Coke][Coke][Sprite][Coke][Sprite][Coke][Sprite][Nestea][Lemonade][Diet Coke][Coke][Sprite][Coke][Diet Coke][Sprite][Diet Coke][Coke][Lemonade][Lemonade][Diet Coke][Coke][Diet Coke][Diet Coke][Coke][Diet Coke][Coke][Coke][Diet Coke][Sprite][Diet Coke][Coke][Diet Coke][Diet Coke][Diet Coke][Diet Coke][Coke][Diet Coke][Diet Coke][Lemonade][Lemonade][Diet Coke][Coke][Diet Coke][Coke][Coke][Diet Coke][Coke][Coke][Lemonade][Coke][Diet Coke][Diet Coke][Diet Coke][Diet Coke][Diet Coke][Diet Coke][Coke][Nestea][Sprite][Diet Coke][Diet Coke][Lemonade][Coke][Sprite][Diet Coke][Coke][Coke][Lemonade][Diet Coke][Sprite][Diet Coke][Diet Coke][Lemonade][Sprite][Lemonade][Diet Coke][Lemonade][Sprite][Diet Coke][Coke][Coke][Coke][Coke][Diet Coke][Diet Coke][Sprite][Coke][Diet Coke][Coke][Lemonade][Diet Coke][Coke][Coke][Sprite][Diet Coke][Sprite][Diet Coke][Coke][Diet Coke][Sprite][Diet Coke][Sprite][Lemonade][Nestea][Diet Coke][Lemonade][Coke][Coke][Sprite][Sprite][Nestea][Nestea][Coke][Sprite][Coke][Coke][Diet Coke][Coke][Diet Coke][Sprite][Diet Coke][Coke][Sprite][Coke][Coke][Coke][Diet Coke][Diet Coke][Diet Coke][Nestea][Lemonade][Sprite][Diet Coke][Nestea][Diet Coke][Coke][Diet Coke][Sprite][Coke][Coke][Coke][Diet Coke][Coke][Diet Coke][Sprite][Diet Coke][Sprite][Coke][Diet Coke][Diet Coke][Coke][Diet Coke][Coke][Diet Coke][Coke][Diet Coke][Diet Coke][Sprite][Diet Coke][Sprite][Sprite][Nestea][Sprite][Sprite][Sprite][Nestea][Diet Coke][Diet Coke][Lemonade][Nestea][Coke][Diet Coke][Coke][Coke][Sprite][Diet Coke][Diet Coke][Coke][Coke][Sprite][Diet Coke][Diet Coke][Sprite][Coke][Diet Coke][Lemonade][Diet Coke][Sprite][Sprite][Diet Coke][Nestea][Coke][Coke][Lemonade][Nestea][Coke][Coke][Nestea][Nestea][Diet Coke][Lemonade][Coke][Coke][Diet Coke][Coke][Diet Coke][Lemonade][Coke][Lemonade][Sprite][Lemonade][Coke][Nestea][Coke][Sprite][Sprite][Diet Coke][Coke][Sprite][Coke][Coke][Coke][Diet Coke][Coke][Diet Coke][Coke][Diet Coke][Sprite][Nestea][Coke][Coke][Sprite][Coke][Coke][Coke][Lemonade][Sprite][Coke][Coke][Sprite][Coke][Diet Coke][Coke][Coke][Lemonade][Lemonade][Diet Coke][Diet Coke][Coke][Sprite][Lemonade][Sprite][Coke][Sprite][Diet Coke][Sprite][Sprite][Coke][Diet Coke][Sprite][Coke][Sprite][Diet Coke][Coke][Diet Coke][Nestea][Diet Coke][Coke][Sprite]\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_price\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 49,\n        \"samples\": [\n          \"$11.25 $8.49 $11.25 $11.25 $10.98 $8.49 $8.49 $11.25 $8.49 $8.49 $8.75 $8.49 $8.49 $8.49 $8.49 $8.49 $8.49 $8.75 $8.49 $11.25 $8.49 $8.49 $8.49 $11.25 $8.49 $11.25 $8.49 $11.25 $8.49 $8.75 $11.25 $8.49 $8.49 $8.49 $8.75 $10.98 $8.75 $8.49 $8.49 $8.75 $8.49 $11.25 $8.49 $11.25 $10.98 $11.25 $11.25 $11.25 $8.75 $8.75 $8.75 $8.75 $8.75 $11.25 $11.25 $11.25 $10.98 $8.75 $11.25 $8.75 $8.49 $8.49 $11.25 $8.49 $8.75 $11.25 $8.49 $11.25 $8.49 $8.75 $11.25 $8.75 $8.75 $8.49 $11.25 $8.49 $8.49 $11.25 $11.25 $33.75 $8.49 $11.25 $8.49 $8.49 $8.49 $8.49 $8.49 $8.49 $11.25 $11.25 $11.25 $11.25 $8.75 $11.25 $11.25 \",\n          \"$7.40 $7.40 \",\n          \"$8.99 \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#most ordered item according to choice_description(sorted data according to quantity ordered)\n",
        "d=data.groupby('choice_description')\n",
        "d=d.sum()\n",
        "d=d.sort_values(['quantity'],ascending=False)\n",
        "d.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 324
        },
        "id": "SjV_DDPTUirz",
        "outputId": "b38f56b9-9d15-412c-82cf-040ea2d364e6"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    order_id  quantity  \\\n",
              "choice_description                                                       \n",
              "[Diet Coke]                                           123455       159   \n",
              "[Coke]                                                122752       143   \n",
              "[Sprite]                                               80426        89   \n",
              "[Fresh Tomato Salsa, [Rice, Black Beans, Cheese...     43088        49   \n",
              "[Fresh Tomato Salsa, [Rice, Black Beans, Cheese...     36041        42   \n",
              "\n",
              "                                                                                            item_name  \\\n",
              "choice_description                                                                                      \n",
              "[Diet Coke]                                         Canned SodaCanned SodaCanned Soda6 Pack Soft D...   \n",
              "[Coke]                                              Canned Soft DrinkCanned Soft DrinkCanned Soft ...   \n",
              "[Sprite]                                            Canned SodaCanned SodaCanned Soft Drink6 Pack ...   \n",
              "[Fresh Tomato Salsa, [Rice, Black Beans, Cheese...  Chicken BowlChicken BurritoChicken BowlChicken...   \n",
              "[Fresh Tomato Salsa, [Rice, Black Beans, Cheese...  Chicken BowlChicken BowlChicken BurritoCarnita...   \n",
              "\n",
              "                                                                                           item_price  \n",
              "choice_description                                                                                     \n",
              "[Diet Coke]                                         $2.18 $1.09 $1.09 $6.49 $2.18 $1.25 $1.09 $6.4...  \n",
              "[Coke]                                              $1.25 $1.25 $1.25 $6.49 $1.25 $1.25 $1.25 $1.2...  \n",
              "[Sprite]                                            $2.18 $1.09 $1.25 $6.49 $1.25 $1.25 $1.09 $1.2...  \n",
              "[Fresh Tomato Salsa, [Rice, Black Beans, Cheese...  $8.75 $8.75 $8.75 $8.75 $9.25 $8.75 $8.75 $8.7...  \n",
              "[Fresh Tomato Salsa, [Rice, Black Beans, Cheese...  $17.50 $8.75 $8.75 $9.25 $8.75 $9.25 $8.75 $8....  "
            ],
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              "      <th></th>\n",
              "      <th>order_id</th>\n",
              "      <th>quantity</th>\n",
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              "      <td>123455</td>\n",
              "      <td>159</td>\n",
              "      <td>Canned SodaCanned SodaCanned Soda6 Pack Soft D...</td>\n",
              "      <td>$2.18 $1.09 $1.09 $6.49 $2.18 $1.25 $1.09 $6.4...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>[Coke]</th>\n",
              "      <td>122752</td>\n",
              "      <td>143</td>\n",
              "      <td>Canned Soft DrinkCanned Soft DrinkCanned Soft ...</td>\n",
              "      <td>$1.25 $1.25 $1.25 $6.49 $1.25 $1.25 $1.25 $1.2...</td>\n",
              "    </tr>\n",
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              "    </tr>\n",
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              "      <th>[Fresh Tomato Salsa, [Rice, Black Beans, Cheese, Sour Cream, Lettuce]]</th>\n",
              "      <td>43088</td>\n",
              "      <td>49</td>\n",
              "      <td>Chicken BowlChicken BurritoChicken BowlChicken...</td>\n",
              "      <td>$8.75 $8.75 $8.75 $8.75 $9.25 $8.75 $8.75 $8.7...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>[Fresh Tomato Salsa, [Rice, Black Beans, Cheese, Sour Cream]]</th>\n",
              "      <td>36041</td>\n",
              "      <td>42</td>\n",
              "      <td>Chicken BowlChicken BowlChicken BurritoCarnita...</td>\n",
              "      <td>$17.50 $8.75 $8.75 $9.25 $8.75 $9.25 $8.75 $8....</td>\n",
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              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      height: 32px;\n",
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              "      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",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      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",
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              "        document.querySelector('#df-e8de7f36-1223-42b9-b586-59708d7c5039 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-e8de7f36-1223-42b9-b586-59708d7c5039');\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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-95883ad9-cac4-49af-8312-fb431f3b3678 button');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "d",
              "summary": "{\n  \"name\": \"d\",\n  \"rows\": 1043,\n  \"fields\": [\n    {\n      \"column\": \"choice_description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1043,\n        \"samples\": [\n          \"[Roasted Chili Corn Salsa, [Fajita Vegetables, Rice, Pinto Beans, Cheese, Guacamole, Lettuce]]\",\n          \"[Tomatillo-Red Chili Salsa (Hot), [Cheese, Sour Cream, Lettuce]]\",\n          \"[[Fresh Tomato Salsa (Mild), Tomatillo-Green Chili Salsa (Medium), Roasted Chili Corn Salsa (Medium), Tomatillo-Red Chili Salsa (Hot)], [Pinto Beans, Black Beans, Rice, Cheese, Sour Cream]]\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"order_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7177,\n        \"min\": 4,\n        \"max\": 123455,\n        \"num_unique_values\": 922,\n        \"samples\": [\n          628,\n          1607,\n          414\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 1,\n        \"max\": 159,\n        \"num_unique_values\": 34,\n        \"samples\": [\n          20,\n          15,\n          7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 404,\n        \"samples\": [\n          \"Barbacoa Soft TacosBarbacoa Soft TacosBarbacoa Soft TacosBarbacoa Soft TacosBarbacoa Soft TacosCarnitas BurritoBarbacoa Soft TacosSteak Burrito\",\n          \"Chicken Soft TacosSteak BowlVeggie BowlCarnitas Bowl\",\n          \"Barbacoa Bowl\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_price\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 284,\n        \"samples\": [\n          \"$9.25 $8.75 $9.25 $8.75 $8.75 $8.75 $8.75 $8.75 $8.75 $8.75 $8.75 $8.75 $8.75 $9.25 $8.75 $8.75 $9.25 $8.75 $8.75 $8.75 $17.50 $8.75 $8.75 $8.75 $9.25 $8.75 $8.75 $8.75 $8.75 \",\n          \"$8.75 $9.39 \",\n          \"$10.98 $10.98 $10.98 $10.98 $10.98 \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#total items ordered\n",
        "total_items_ordered=data.quantity.sum()\n",
        "print(total_items_ordered)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K5lLz0N_VZF7",
        "outputId": "a1cdb9aa-0ad2-4063-9c40-9e716ffa3d77"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4972\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.item_price.dtype"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2_jzDhFeV9ww",
        "outputId": "2368fd81-1673-4599-8904-e06336c689fb"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('float64')"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#to convert item_price to float data type\n",
        "#dollarizer = lambda x: float(x[1:-1])\n",
        "#data.item_price = data.item_price.apply(dollarizer)"
      ],
      "metadata": {
        "id": "aMImD6fvikMZ"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.item_price.dtype"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JQhVXmbSlodZ",
        "outputId": "294a0ce5-55b0-4a70-f93e-243476bcc737"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('float64')"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "22ltEDPAlrdn",
        "outputId": "37c0d762-cab0-4c07-989b-5ab9ee4d24eb"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "order_id                int64\n",
              "quantity                int64\n",
              "item_name              object\n",
              "choice_description     object\n",
              "item_price            float64\n",
              "dtype: object"
            ],
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              "      <th>0</th>\n",
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              "      <th>order_id</th>\n",
              "      <td>int64</td>\n",
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              "      <th>quantity</th>\n",
              "      <td>int64</td>\n",
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              "      <th>item_name</th>\n",
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              "</div><br><label><b>dtype:</b> object</label>"
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    {
      "cell_type": "code",
      "source": [
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      "metadata": {
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          "base_uri": "https://localhost:8080/",
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      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.info of       order_id  quantity                              item_name  \\\n",
              "0            1         1           Chips and Fresh Tomato Salsa   \n",
              "1            1         1                                   Izze   \n",
              "2            1         1                       Nantucket Nectar   \n",
              "3            1         1  Chips and Tomatillo-Green Chili Salsa   \n",
              "4            2         2                           Chicken Bowl   \n",
              "...        ...       ...                                    ...   \n",
              "4617      1833         1                          Steak Burrito   \n",
              "4618      1833         1                          Steak Burrito   \n",
              "4619      1834         1                     Chicken Salad Bowl   \n",
              "4620      1834         1                     Chicken Salad Bowl   \n",
              "4621      1834         1                     Chicken Salad Bowl   \n",
              "\n",
              "                                     choice_description  item_price  \n",
              "0                                                   NaN        2.39  \n",
              "1                                          [Clementine]        3.39  \n",
              "2                                               [Apple]        3.39  \n",
              "3                                                   NaN        2.39  \n",
              "4     [Tomatillo-Red Chili Salsa (Hot), [Black Beans...       16.98  \n",
              "...                                                 ...         ...  \n",
              "4617  [Fresh Tomato Salsa, [Rice, Black Beans, Sour ...       11.75  \n",
              "4618  [Fresh Tomato Salsa, [Rice, Sour Cream, Cheese...       11.75  \n",
              "4619  [Fresh Tomato Salsa, [Fajita Vegetables, Pinto...       11.25  \n",
              "4620  [Fresh Tomato Salsa, [Fajita Vegetables, Lettu...        8.75  \n",
              "4621  [Fresh Tomato Salsa, [Fajita Vegetables, Pinto...        8.75  \n",
              "\n",
              "[4622 rows x 5 columns]>"
            ],
            "text/html": [
              "<div style=\"max-width:800px; border: 1px solid var(--colab-border-color);\"><style>\n",
              "      pre.function-repr-contents {\n",
              "        overflow-x: auto;\n",
              "        padding: 8px 12px;\n",
              "        max-height: 500px;\n",
              "      }\n",
              "\n",
              "      pre.function-repr-contents.function-repr-contents-collapsed {\n",
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              "    </style>\n",
              "    <pre style=\"white-space: initial; background:\n",
              "         var(--colab-secondary-surface-color); padding: 8px 12px;\n",
              "         border-bottom: 1px solid var(--colab-border-color);\"><b>pandas.core.frame.DataFrame.info</b><br/>def info(verbose: bool | None=None, buf: WriteBuffer[str] | None=None, max_cols: int | None=None, memory_usage: bool | str | None=None, show_counts: bool | None=None) -&gt; None</pre><pre class=\"function-repr-contents function-repr-contents-collapsed\" style=\"\"><a class=\"filepath\" style=\"display:none\" href=\"#\">/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py</a>Print a concise summary of a DataFrame.\n",
              "\n",
              "This method prints information about a DataFrame including\n",
              "the index dtype and columns, non-null values and memory usage.\n",
              "\n",
              "Parameters\n",
              "----------\n",
              "verbose : bool, optional\n",
              "    Whether to print the full summary. By default, the setting in\n",
              "    ``pandas.options.display.max_info_columns`` is followed.\n",
              "buf : writable buffer, defaults to sys.stdout\n",
              "    Where to send the output. By default, the output is printed to\n",
              "    sys.stdout. Pass a writable buffer if you need to further process\n",
              "    the output.\n",
              "max_cols : int, optional\n",
              "    When to switch from the verbose to the truncated output. If the\n",
              "    DataFrame has more than `max_cols` columns, the truncated output\n",
              "    is used. By default, the setting in\n",
              "    ``pandas.options.display.max_info_columns`` is used.\n",
              "memory_usage : bool, str, optional\n",
              "    Specifies whether total memory usage of the DataFrame\n",
              "    elements (including the index) should be displayed. By default,\n",
              "    this follows the ``pandas.options.display.memory_usage`` setting.\n",
              "\n",
              "    True always show memory usage. False never shows memory usage.\n",
              "    A value of &#x27;deep&#x27; is equivalent to &quot;True with deep introspection&quot;.\n",
              "    Memory usage is shown in human-readable units (base-2\n",
              "    representation). Without deep introspection a memory estimation is\n",
              "    made based in column dtype and number of rows assuming values\n",
              "    consume the same memory amount for corresponding dtypes. With deep\n",
              "    memory introspection, a real memory usage calculation is performed\n",
              "    at the cost of computational resources. See the\n",
              "    :ref:`Frequently Asked Questions &lt;df-memory-usage&gt;` for more\n",
              "    details.\n",
              "show_counts : bool, optional\n",
              "    Whether to show the non-null counts. By default, this is shown\n",
              "    only if the DataFrame is smaller than\n",
              "    ``pandas.options.display.max_info_rows`` and\n",
              "    ``pandas.options.display.max_info_columns``. A value of True always\n",
              "    shows the counts, and False never shows the counts.\n",
              "\n",
              "Returns\n",
              "-------\n",
              "None\n",
              "    This method prints a summary of a DataFrame and returns None.\n",
              "\n",
              "See Also\n",
              "--------\n",
              "DataFrame.describe: Generate descriptive statistics of DataFrame\n",
              "    columns.\n",
              "DataFrame.memory_usage: Memory usage of DataFrame columns.\n",
              "\n",
              "Examples\n",
              "--------\n",
              "&gt;&gt;&gt; int_values = [1, 2, 3, 4, 5]\n",
              "&gt;&gt;&gt; text_values = [&#x27;alpha&#x27;, &#x27;beta&#x27;, &#x27;gamma&#x27;, &#x27;delta&#x27;, &#x27;epsilon&#x27;]\n",
              "&gt;&gt;&gt; float_values = [0.0, 0.25, 0.5, 0.75, 1.0]\n",
              "&gt;&gt;&gt; df = pd.DataFrame({&quot;int_col&quot;: int_values, &quot;text_col&quot;: text_values,\n",
              "...                   &quot;float_col&quot;: float_values})\n",
              "&gt;&gt;&gt; df\n",
              "    int_col text_col  float_col\n",
              "0        1    alpha       0.00\n",
              "1        2     beta       0.25\n",
              "2        3    gamma       0.50\n",
              "3        4    delta       0.75\n",
              "4        5  epsilon       1.00\n",
              "\n",
              "Prints information of all columns:\n",
              "\n",
              "&gt;&gt;&gt; df.info(verbose=True)\n",
              "&lt;class &#x27;pandas.core.frame.DataFrame&#x27;&gt;\n",
              "RangeIndex: 5 entries, 0 to 4\n",
              "Data columns (total 3 columns):\n",
              " #   Column     Non-Null Count  Dtype\n",
              "---  ------     --------------  -----\n",
              " 0   int_col    5 non-null      int64\n",
              " 1   text_col   5 non-null      object\n",
              " 2   float_col  5 non-null      float64\n",
              "dtypes: float64(1), int64(1), object(1)\n",
              "memory usage: 248.0+ bytes\n",
              "\n",
              "Prints a summary of columns count and its dtypes but not per column\n",
              "information:\n",
              "\n",
              "&gt;&gt;&gt; df.info(verbose=False)\n",
              "&lt;class &#x27;pandas.core.frame.DataFrame&#x27;&gt;\n",
              "RangeIndex: 5 entries, 0 to 4\n",
              "Columns: 3 entries, int_col to float_col\n",
              "dtypes: float64(1), int64(1), object(1)\n",
              "memory usage: 248.0+ bytes\n",
              "\n",
              "Pipe output of DataFrame.info to buffer instead of sys.stdout, get\n",
              "buffer content and writes to a text file:\n",
              "\n",
              "&gt;&gt;&gt; import io\n",
              "&gt;&gt;&gt; buffer = io.StringIO()\n",
              "&gt;&gt;&gt; df.info(buf=buffer)\n",
              "&gt;&gt;&gt; s = buffer.getvalue()\n",
              "&gt;&gt;&gt; with open(&quot;df_info.txt&quot;, &quot;w&quot;,\n",
              "...           encoding=&quot;utf-8&quot;) as f:  # doctest: +SKIP\n",
              "...     f.write(s)\n",
              "260\n",
              "\n",
              "The `memory_usage` parameter allows deep introspection mode, specially\n",
              "useful for big DataFrames and fine-tune memory optimization:\n",
              "\n",
              "&gt;&gt;&gt; random_strings_array = np.random.choice([&#x27;a&#x27;, &#x27;b&#x27;, &#x27;c&#x27;], 10 ** 6)\n",
              "&gt;&gt;&gt; df = pd.DataFrame({\n",
              "...     &#x27;column_1&#x27;: np.random.choice([&#x27;a&#x27;, &#x27;b&#x27;, &#x27;c&#x27;], 10 ** 6),\n",
              "...     &#x27;column_2&#x27;: np.random.choice([&#x27;a&#x27;, &#x27;b&#x27;, &#x27;c&#x27;], 10 ** 6),\n",
              "...     &#x27;column_3&#x27;: np.random.choice([&#x27;a&#x27;, &#x27;b&#x27;, &#x27;c&#x27;], 10 ** 6)\n",
              "... })\n",
              "&gt;&gt;&gt; df.info()\n",
              "&lt;class &#x27;pandas.core.frame.DataFrame&#x27;&gt;\n",
              "RangeIndex: 1000000 entries, 0 to 999999\n",
              "Data columns (total 3 columns):\n",
              " #   Column    Non-Null Count    Dtype\n",
              "---  ------    --------------    -----\n",
              " 0   column_1  1000000 non-null  object\n",
              " 1   column_2  1000000 non-null  object\n",
              " 2   column_3  1000000 non-null  object\n",
              "dtypes: object(3)\n",
              "memory usage: 22.9+ MB\n",
              "\n",
              "&gt;&gt;&gt; df.info(memory_usage=&#x27;deep&#x27;)\n",
              "&lt;class &#x27;pandas.core.frame.DataFrame&#x27;&gt;\n",
              "RangeIndex: 1000000 entries, 0 to 999999\n",
              "Data columns (total 3 columns):\n",
              " #   Column    Non-Null Count    Dtype\n",
              "---  ------    --------------    -----\n",
              " 0   column_1  1000000 non-null  object\n",
              " 1   column_2  1000000 non-null  object\n",
              " 2   column_3  1000000 non-null  object\n",
              "dtypes: object(3)\n",
              "memory usage: 165.9 MB</pre>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#how many orders were made in that period\n",
        "orders=data.order_id.value_counts().count()\n",
        "print(orders)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dbp_nVhUocr9",
        "outputId": "952608f0-05b8-4544-d15c-178e6ef221d4"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1834\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "revenue = (data['quantity']* data['item_price']).sum()\n",
        "#print('Revenue was: $' + str(np.round(revenue,2)))\n",
        "data['revenue'] = data['quantity'] * data['item_price']\n",
        "order_grouped = data.groupby(by=['order_id']).sum()\n",
        "order_grouped"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 628
        },
        "id": "t4wNP2rDorGc",
        "outputId": "21cd5219-5556-48cd-fcca-e8bada0d3dfb"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          quantity                                          item_name  \\\n",
              "order_id                                                                \n",
              "1                4  Chips and Fresh Tomato SalsaIzzeNantucket Nect...   \n",
              "2                2                                       Chicken Bowl   \n",
              "3                2                          Chicken BowlSide of Chips   \n",
              "4                2                      Steak BurritoSteak Soft Tacos   \n",
              "5                2                   Steak BurritoChips and Guacamole   \n",
              "...            ...                                                ...   \n",
              "1830             2                        Steak BurritoVeggie Burrito   \n",
              "1831             3                    Carnitas BowlChipsBottled Water   \n",
              "1832             2              Chicken Soft TacosChips and Guacamole   \n",
              "1833             2                         Steak BurritoSteak Burrito   \n",
              "1834             3  Chicken Salad BowlChicken Salad BowlChicken Sa...   \n",
              "\n",
              "                                         choice_description  \\\n",
              "order_id                                                      \n",
              "1                                       [Clementine][Apple]   \n",
              "2         [Tomatillo-Red Chili Salsa (Hot), [Black Beans...   \n",
              "3         [Fresh Tomato Salsa (Mild), [Rice, Cheese, Sou...   \n",
              "4         [Tomatillo Red Chili Salsa, [Fajita Vegetables...   \n",
              "5         [Fresh Tomato Salsa, [Rice, Black Beans, Pinto...   \n",
              "...                                                     ...   \n",
              "1830      [Fresh Tomato Salsa, [Rice, Sour Cream, Cheese...   \n",
              "1831      [Fresh Tomato Salsa, [Fajita Vegetables, Rice,...   \n",
              "1832       [Fresh Tomato Salsa, [Rice, Cheese, Sour Cream]]   \n",
              "1833      [Fresh Tomato Salsa, [Rice, Black Beans, Sour ...   \n",
              "1834      [Fresh Tomato Salsa, [Fajita Vegetables, Pinto...   \n",
              "\n",
              "                        item_price                   revenue  \n",
              "order_id                                                      \n",
              "1         $2.39 $3.39 $3.39 $2.39   $2.39 $3.39 $3.39 $2.39   \n",
              "2                          $16.98             $16.98 $16.98   \n",
              "3                    $10.98 $1.69              $10.98 $1.69   \n",
              "4                    $11.75 $9.25              $11.75 $9.25   \n",
              "5                     $9.25 $4.45               $9.25 $4.45   \n",
              "...                            ...                       ...  \n",
              "1830                $11.75 $11.25             $11.75 $11.25   \n",
              "1831            $9.25 $2.15 $1.50         $9.25 $2.15 $1.50   \n",
              "1832                  $8.75 $4.45               $8.75 $4.45   \n",
              "1833                $11.75 $11.75             $11.75 $11.75   \n",
              "1834           $11.25 $8.75 $8.75        $11.25 $8.75 $8.75   \n",
              "\n",
              "[1834 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-dbd95747-b74b-4f90-94a0-84d90c448de7\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>quantity</th>\n",
              "      <th>item_name</th>\n",
              "      <th>choice_description</th>\n",
              "      <th>item_price</th>\n",
              "      <th>revenue</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>order_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4</td>\n",
              "      <td>Chips and Fresh Tomato SalsaIzzeNantucket Nect...</td>\n",
              "      <td>[Clementine][Apple]</td>\n",
              "      <td>$2.39 $3.39 $3.39 $2.39</td>\n",
              "      <td>$2.39 $3.39 $3.39 $2.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>Chicken Bowl</td>\n",
              "      <td>[Tomatillo-Red Chili Salsa (Hot), [Black Beans...</td>\n",
              "      <td>$16.98</td>\n",
              "      <td>$16.98 $16.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>Chicken BowlSide of Chips</td>\n",
              "      <td>[Fresh Tomato Salsa (Mild), [Rice, Cheese, Sou...</td>\n",
              "      <td>$10.98 $1.69</td>\n",
              "      <td>$10.98 $1.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>Steak BurritoSteak Soft Tacos</td>\n",
              "      <td>[Tomatillo Red Chili Salsa, [Fajita Vegetables...</td>\n",
              "      <td>$11.75 $9.25</td>\n",
              "      <td>$11.75 $9.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2</td>\n",
              "      <td>Steak BurritoChips and Guacamole</td>\n",
              "      <td>[Fresh Tomato Salsa, [Rice, Black Beans, Pinto...</td>\n",
              "      <td>$9.25 $4.45</td>\n",
              "      <td>$9.25 $4.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1830</th>\n",
              "      <td>2</td>\n",
              "      <td>Steak BurritoVeggie Burrito</td>\n",
              "      <td>[Fresh Tomato Salsa, [Rice, Sour Cream, Cheese...</td>\n",
              "      <td>$11.75 $11.25</td>\n",
              "      <td>$11.75 $11.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1831</th>\n",
              "      <td>3</td>\n",
              "      <td>Carnitas BowlChipsBottled Water</td>\n",
              "      <td>[Fresh Tomato Salsa, [Fajita Vegetables, Rice,...</td>\n",
              "      <td>$9.25 $2.15 $1.50</td>\n",
              "      <td>$9.25 $2.15 $1.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1832</th>\n",
              "      <td>2</td>\n",
              "      <td>Chicken Soft TacosChips and Guacamole</td>\n",
              "      <td>[Fresh Tomato Salsa, [Rice, Cheese, Sour Cream]]</td>\n",
              "      <td>$8.75 $4.45</td>\n",
              "      <td>$8.75 $4.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1833</th>\n",
              "      <td>2</td>\n",
              "      <td>Steak BurritoSteak Burrito</td>\n",
              "      <td>[Fresh Tomato Salsa, [Rice, Black Beans, Sour ...</td>\n",
              "      <td>$11.75 $11.75</td>\n",
              "      <td>$11.75 $11.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1834</th>\n",
              "      <td>3</td>\n",
              "      <td>Chicken Salad BowlChicken Salad BowlChicken Sa...</td>\n",
              "      <td>[Fresh Tomato Salsa, [Fajita Vegetables, Pinto...</td>\n",
              "      <td>$11.25 $8.75 $8.75</td>\n",
              "      <td>$11.25 $8.75 $8.75</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1834 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-dbd95747-b74b-4f90-94a0-84d90c448de7 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-dbd95747-b74b-4f90-94a0-84d90c448de7');\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",
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              "\n",
              "\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5dbbb2d4-dbaf-4ba5-975f-fe11897fc5db button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_038ecdea-ca6c-4ef3-a379-c1d06f600e4d\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('order_grouped')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_038ecdea-ca6c-4ef3-a379-c1d06f600e4d button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('order_grouped');\n",
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              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "order_grouped",
              "summary": "{\n  \"name\": \"order_grouped\",\n  \"rows\": 1834,\n  \"fields\": [\n    {\n      \"column\": \"order_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 529,\n        \"min\": 1,\n        \"max\": 1834,\n        \"num_unique_values\": 1834,\n        \"samples\": [\n          644,\n          333,\n          991\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 35,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          4,\n          16,\n          35\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 866,\n        \"samples\": [\n          \"Canned Soft DrinkChicken BowlChicken Crispy Tacos\",\n          \"Chicken BowlBottled WaterChips\",\n          \"Steak BurritoCanned Soft DrinkChips and Tomatillo Red Chili Salsa\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"choice_description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1412,\n        \"samples\": [\n          \"[Roasted Chili Corn Salsa (Medium), [Rice, Guacamole, Lettuce]][[Fresh Tomato Salsa (Mild), Tomatillo-Green Chili Salsa (Medium), Roasted Chili Corn Salsa (Medium), Tomatillo-Red Chili Salsa (Hot)], [Pinto Beans, Black Beans, Rice, Cheese, Sour Cream]]\",\n          \"[Tomatillo Red Chili Salsa, [Rice, Cheese, Lettuce]][Tomatillo Red Chili Salsa, [Rice, Cheese]]\",\n          \"[Lemonade][Roasted Chili Corn Salsa, [Rice, Fajita Vegetables, Sour Cream, Cheese, Lettuce]][Roasted Chili Corn Salsa, [Rice, Fajita Vegetables, Cheese, Lettuce, Guacamole]][Roasted Chili Corn Salsa, [Rice, Fajita Vegetables, Sour Cream, Lettuce, Guacamole]]\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"item_price\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 642,\n        \"samples\": [\n          \"$8.75 $1.25 $2.15 \",\n          \"$8.75 $4.45 $8.75 $2.95 $8.75 $2.15 \",\n          \"$8.19 $2.29 \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"revenue\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 642,\n        \"samples\": [\n          \"$8.75 $1.25 $2.15 \",\n          \"$8.75 $4.45 $8.75 $2.95 $8.75 $2.15 \",\n          \"$8.19 $2.29 \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "lJgXGAgSqRKV",
        "outputId": "516b93ff-4a1b-4bd2-d4d4-cb1291be73ac"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          order_id     quantity\n",
              "count  4622.000000  4622.000000\n",
              "mean    927.254868     1.075725\n",
              "std     528.890796     0.410186\n",
              "min       1.000000     1.000000\n",
              "25%     477.250000     1.000000\n",
              "50%     926.000000     1.000000\n",
              "75%    1393.000000     1.000000\n",
              "max    1834.000000    15.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5b88c963-9b1a-4bd4-9d59-3b5260861da9\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .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>order_id</th>\n",
              "      <th>quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>4622.000000</td>\n",
              "      <td>4622.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>927.254868</td>\n",
              "      <td>1.075725</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>528.890796</td>\n",
              "      <td>0.410186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>477.250000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>926.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1393.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1834.000000</td>\n",
              "      <td>15.000000</td>\n",
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              "  </tbody>\n",
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              "      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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-5b88c963-9b1a-4bd4-9d59-3b5260861da9 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-5b88c963-9b1a-4bd4-9d59-3b5260861da9');\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",
              "\n",
              "\n",
              "<div id=\"df-0628d4db-4b52-40d8-b7bc-46179a5afcd2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0628d4db-4b52-40d8-b7bc-46179a5afcd2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0628d4db-4b52-40d8-b7bc-46179a5afcd2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"order_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1441.9860407220838,\n        \"min\": 1.0,\n        \"max\": 4622.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          927.2548680225011,\n          926.0,\n          4622.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quantity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1633.0965283367182,\n        \"min\": 0.4101863342575426,\n        \"max\": 4622.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1.0757247944612722,\n          15.0,\n          0.4101863342575426\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "wsIFjTtn4M6j"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}