Lead_Allocation_Big_Query_&_GPT4o.ipynb

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      ]
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    {
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        "!pip install openai\n",
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          "text": [
            "Collecting openai\n",
            "  Downloading openai-1.35.14-py3-none-any.whl (328 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m328.5/328.5 kB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai) (3.7.1)\n",
            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from openai) (1.7.0)\n",
            "Collecting httpx<1,>=0.23.0 (from openai)\n",
            "  Downloading httpx-0.27.0-py3-none-any.whl (75 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.6/75.6 kB\u001b[0m \u001b[31m8.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from openai) (1.3.1)\n",
            "Requirement already satisfied: tqdm>4 in /usr/local/lib/python3.10/dist-packages (from openai) (4.66.4)\n",
            "Requirement already satisfied: typing-extensions<5,>=4.7 in /usr/local/lib/python3.10/dist-packages (from openai) (4.12.2)\n",
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            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->openai) (2024.7.4)\n",
            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai)\n",
            "  Downloading httpcore-1.0.5-py3-none-any.whl (77 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m77.9/77.9 kB\u001b[0m \u001b[31m9.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Installing collected packages: h11, httpcore, httpx, openai\n",
            "Successfully installed h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 openai-1.35.14\n",
            "Requirement already satisfied: tabulate in /usr/local/lib/python3.10/dist-packages (0.9.0)\n"
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      "cell_type": "code",
      "source": [
        "# get the openai secret key\n",
        "import pandas as pd\n",
        "import getpass\n",
        "secret_key = getpass.getpass('Please enter your openai key: ')\n",
        "from IPython.display import display, Markdown\n",
        "from tabulate import tabulate"
      ],
      "metadata": {
        "id": "c1rYBN0yrbWN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b90c1186-0da8-4215-b1b0-2624e640e4ef"
      },
      "execution_count": 1,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Please enter your openai key: ··········\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import auth\n",
        "auth.authenticate_user()"
      ],
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        "id": "2ZYa1C5eED1F"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%bigquery staff --project bigquerycourse-onetwothree\n",
        "SELECT * FROM `bigquerycourse-onetwothree.test.Staff`"
      ],
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            "42769baa2e094e7a91d56b24a79c4d3d"
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        },
        "id": "ORU9S3dCEcmE",
        "outputId": "215cdeb3-7c23-4c49-f2b9-da213ba00fe3"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Query is running:   0%|          |"
            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          |"
            ],
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    {
      "cell_type": "code",
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        "staff"
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          "height": 246
        },
        "id": "MIvVpLz_D263",
        "outputId": "a6064e85-4f17-4ee3-efcd-ef3cb9c0e77a"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   ID        Name   Sales New BMW  Sales New Nissan  Sales Used Premium  \\\n",
              "0    5    Tom Pops              0                30                   0   \n",
              "1    2  Tony Young              2                 2                   2   \n",
              "2    1   Tim Green             23                 1                  10   \n",
              "3    4  Brid Flynn             10                10                  10   \n",
              "4    3  Mary Choco              3                20                  20   \n",
              "\n",
              "   Sales Used Other                                                Bio  \\\n",
              "0                12  Tom leads the Nissan new Sales with 10 years o...   \n",
              "1                30  Tony is a first year salesman specialising in ...   \n",
              "2                 4  Tim is an experieced Salesman specialising in ...   \n",
              "3                10  Brid has been with the dealership 20 years and...   \n",
              "4                 5        Mary focuses on Premium Used and New Nissan   \n",
              "\n",
              "   Current Leads  \n",
              "0             10  \n",
              "1              5  \n",
              "2             10  \n",
              "3              7  \n",
              "4              8  "
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "staff",
              "summary": "{\n  \"name\": \"staff\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"ID \",\n      \"properties\": {\n        \"dtype\": \"Int64\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2,\n          3,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Name \",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Tony Young\",\n          \"Mary Choco\",\n          \"Tim Green\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sales New BMW\",\n      \"properties\": {\n        \"dtype\": \"Int64\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2,\n          3,\n          23\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sales New Nissan\",\n      \"properties\": {\n        \"dtype\": \"Int64\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2,\n          20,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sales Used Premium\",\n      \"properties\": {\n        \"dtype\": \"Int64\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          2,\n          20,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sales Used Other\",\n      \"properties\": {\n        \"dtype\": \"Int64\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          30,\n          5,\n          4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Bio\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Tony is a first year salesman specialising in all used Cars \",\n          \"Mary focuses on Premium Used and New Nissan\",\n          \"Tim is an experieced Salesman specialising in BMW - He is the Sales Manager of the dealership\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Current Leads\",\n      \"properties\": {\n        \"dtype\": \"Int64\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          5,\n          8,\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%bigquery leads --project bigquerycourse-onetwothree\n",
        "SELECT * FROM `bigquerycourse-onetwothree.test.Leads`"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81,
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      "execution_count": 58,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Query is running:   0%|          |"
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              "Downloading:   0%|          |"
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    {
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        "id": "1Ef61t5BExF8",
        "outputId": "471ba402-2b62-40e6-a37f-d96c958b40ae"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   No           Name  New Customer  Interested in   \\\n",
              "0   7    Jeff Stubbs          False           Used   \n",
              "1   9     Fred Flynn          False           Used   \n",
              "2   3     Arron Wise          False           Used   \n",
              "3   4     Mairead Bo           True           Used   \n",
              "4  10    Kerry Gregg           True           Used   \n",
              "5   8    Perry Terry           True           Used   \n",
              "6   1     Dave Young           True        New BMW   \n",
              "7   6  Barry O Brien           True       New BMW    \n",
              "8   2      Joe Peats          False     New Nissan   \n",
              "9   5       Josh Tas          False     New Nissan   \n",
              "\n",
              "                                             Enquiry  Allocated Sales Person  \\\n",
              "0  There is a 05 BMW 3 Series on the site, is it ...      False         None   \n",
              "1  Im looking to trade in X-Trail I bought from B...      False         None   \n",
              "2  Dear Dealership, Have you heard about the new ...      False         None   \n",
              "3                          £££$£@$£@$$%£%$@£$!@£$R£!      False         None   \n",
              "4  Can I arrange a test drive of the 20D Opel Ast...      False         None   \n",
              "5                         Is the 23D black Jag Sold?      False         None   \n",
              "6  Im interested in the new 5 Series changed by C...      False         None   \n",
              "7          Looking for more info on the new 3 series      False         None   \n",
              "8  Hello, I like the look of the new X-Trail, ple...      False         None   \n",
              "9  Hi Guys, Do you have any avaliability of the N...      False         None   \n",
              "\n",
              "  allocation_reason  \n",
              "0              None  \n",
              "1              None  \n",
              "2              None  \n",
              "3              None  \n",
              "4              None  \n",
              "5              None  \n",
              "6              None  \n",
              "7              None  \n",
              "8              None  \n",
              "9              None  "
            ],
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              "      <td>New Nissan</td>\n",
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              "            title=\"Generate code using this dataframe.\"\n",
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              "\n",
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              "       width=\"24px\">\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('leads');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "leads",
              "repr_error": "Out of range float values are not JSON compliant: nan"
            }
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "leads_markdown = tabulate(leads, headers='keys', tablefmt='pipe', showindex=False)\n",
        "salespeople_markdown = tabulate(staff, headers='keys', tablefmt='pipe', showindex=False)"
      ],
      "metadata": {
        "id": "fQImiNzGNwNW"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(leads_markdown)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wTLxq3YTT-Lh",
        "outputId": "7ff336ed-279a-4308-c8ef-2e119e141ca5"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "|   No | Name          | New Customer    | Interested in    | Enquiry                                                                                                                                                   | Allocated   | Sales Person   | allocation_reason   |\n",
            "|-----:|:--------------|:----------------|:-----------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------|:------------|:---------------|:--------------------|\n",
            "|    7 | Jeff Stubbs   | False           | Used             | There is a 05 BMW 3 Series on the site, is it sold?                                                                                                       | False       |                |                     |\n",
            "|    9 | Fred Flynn    | False           | Used             | Im looking to trade in X-Trail I bought from Brid and upgrade to one of the 221D ones you have in stock, can you get her to give me a call? Regards, Fred | False       |                |                     |\n",
            "|    3 | Arron Wise    | False           | Used             | Dear Dealership, Have you heard about the new website 123cars.ie. It will blow your mind.                                                                 | False       |                |                     |\n",
            "|    4 | Mairead Bo    | True            | Used             | £££$£@$£@$$%£%$@£$!@£$R£!                                                                                                                                 | False       |                |                     |\n",
            "|   10 | Kerry Gregg   | True            | Used             | Can I arrange a test drive of the 20D Opel Astra this week? Number is 0876543452 Thanks, Kerry                                                            | False       |                |                     |\n",
            "|    8 | Perry Terry   | True            | Used             | Is the 23D black Jag Sold?                                                                                                                                | False       |                |                     |\n",
            "|    1 | Dave Young    | True            | New BMW          | Im interested in the new 5 Series changed by Car with Tim last year.                                                                                      | False       |                |                     |\n",
            "|    6 | Barry O Brien | True            | New BMW          | Looking for more info on the new 3 series                                                                                                                 | False       |                |                     |\n",
            "|    2 | Joe Peats     | False           | New Nissan       | Hello, I like the look of the new X-Trail, please give me a call on 0864561234. RGDS Joe                                                                  | False       |                |                     |\n",
            "|    5 | Josh Tas      | False           | New Nissan       | Hi Guys, Do you have any avaliability of the New Juke for 242D My number is 0861245673. Regards, J                                                        | False       |                |                     |\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from openai import OpenAI\n",
        "client = OpenAI(api_key=secret_key)\n",
        "\n",
        "def get_response(prompt):\n",
        "  # Create a request to the chat completions endpoint\n",
        "  response = client.chat.completions.create(\n",
        "    model=\"gpt-4o\",\n",
        "    # Assign the role and content for the message\n",
        "    messages=\n",
        "     [\n",
        "        {\n",
        "            \"role\": \"system\", \"content\": f\"\"\"\n",
        "\n",
        "              You are an AI assistant tasked with allocating leads to salespeople for my Car Dealership based on the following rules:\n",
        "              1. Consider if any leads are spam - Allocate these to the Salesperson Spam\n",
        "              2. Allocate leads to the correct salesperson based on  speciality while ensuring lead allocation is balanced between the salespeople considering current leads.\n",
        "\n",
        "\n",
        "              For each lead, provide the allocation in the following format:\n",
        "              [\n",
        "                  {{\"No\": lead_no, \"Name\": lead_name, \"Sales Person\": salesperson, \"allocation_reason\": \"reason for allocation\"}},\n",
        "                  ...\n",
        "              ]\n",
        "\n",
        "              Provide no description text just output the json within the brackets.\n",
        "\n",
        "            \"\"\"\n",
        "        },\n",
        "        {\n",
        "            \"role\": \"user\", \"content\": prompt\n",
        "        }\n",
        "     ],\n",
        "    temperature = 0.4,\n",
        "    max_tokens=3000)\n",
        "  return response.choices[0].message.content"
      ],
      "metadata": {
        "id": "w309wtpY89Vr"
      },
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Extract the result\n",
        "result = get_response(f\"\"\"Leads:\n",
        "              {leads_markdown}\n",
        "              Salespeople:\n",
        "              {salespeople_markdown}\"\"\")"
      ],
      "metadata": {
        "id": "Mk4f1xB2M0mk"
      },
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Add Results to Big Query\n"
      ],
      "metadata": {
        "id": "GCuNwAgrTUj7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(result)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "26T5fdK4SRBP",
        "outputId": "a994a0b6-2837-43ff-95c0-07dc3f61bb0a"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[\n",
            "    {\"No\": 7, \"Name\": \"Jeff Stubbs\", \"Sales Person\": \"Tony Young\", \"allocation_reason\": \"Used car enquiry, balanced allocation\"},\n",
            "    {\"No\": 9, \"Name\": \"Fred Flynn\", \"Sales Person\": \"Brid Flynn\", \"allocation_reason\": \"Used car enquiry, balanced allocation\"},\n",
            "    {\"No\": 3, \"Name\": \"Arron Wise\", \"Sales Person\": \"Spam\", \"allocation_reason\": \"Spam enquiry\"},\n",
            "    {\"No\": 4, \"Name\": \"Mairead Bo\", \"Sales Person\": \"Spam\", \"allocation_reason\": \"Spam enquiry\"},\n",
            "    {\"No\": 10, \"Name\": \"Kerry Gregg\", \"Sales Person\": \"Tony Young\", \"allocation_reason\": \"Used car enquiry, balanced allocation\"},\n",
            "    {\"No\": 8, \"Name\": \"Perry Terry\", \"Sales Person\": \"Brid Flynn\", \"allocation_reason\": \"Used car enquiry, balanced allocation\"},\n",
            "    {\"No\": 1, \"Name\": \"Dave Young\", \"Sales Person\": \"Tim Green\", \"allocation_reason\": \"New BMW enquiry, balanced allocation\"},\n",
            "    {\"No\": 6, \"Name\": \"Barry O Brien\", \"Sales Person\": \"Tim Green\", \"allocation_reason\": \"New BMW enquiry, balanced allocation\"},\n",
            "    {\"No\": 2, \"Name\": \"Joe Peats\", \"Sales Person\": \"Mary Choco\", \"allocation_reason\": \"New Nissan enquiry, balanced allocation\"},\n",
            "    {\"No\": 5, \"Name\": \"Josh Tas\", \"Sales Person\": \"Tom Pops\", \"allocation_reason\": \"New Nissan enquiry, balanced allocation\"}\n",
            "]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Convert the output to a DataFrame\n",
        "allocations_list = eval(result.strip())\n",
        "allocations_df = pd.DataFrame(allocations_list)\n",
        "\n",
        "# Function to generate the update code\n",
        "def generate_update_code(row):\n",
        "    return f\"\"\"\n",
        "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
        "SET Allocated = True, `Sales Person` = '{row['Sales Person']}', allocation_reason = '{row['allocation_reason']}'\n",
        "WHERE `Name` = '{row['Name']}';\n",
        "\"\"\"\n",
        "\n",
        "# Generate the update code for each row\n",
        "update_code = \"\"\n",
        "for _, row in allocations_df.iterrows():\n",
        "    update_code += generate_update_code(row)\n",
        "\n",
        "print(update_code)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FXJUs4D3S7ES",
        "outputId": "b09c81a2-e5c3-4466-ba69-65fbe6d1560f"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tony Young', allocation_reason = 'Specialises in all used cars and has balanced lead numbers'\n",
            "WHERE `Name` = 'Jeff Stubbs';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Brid Flynn', allocation_reason = 'Requested Brid specifically and has balanced lead numbers'\n",
            "WHERE `Name` = 'Fred Flynn';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Spam', allocation_reason = 'Spam enquiry'\n",
            "WHERE `Name` = 'Arron Wise';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tom Pops', allocation_reason = 'Specialises in New Nissan and has balanced lead numbers'\n",
            "WHERE `Name` = 'Josh Tas';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tom Pops', allocation_reason = 'Specialises in New Nissan and has balanced lead numbers'\n",
            "WHERE `Name` = 'Joe Peats';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tony Young', allocation_reason = 'Specialises in all used cars and has balanced lead numbers'\n",
            "WHERE `Name` = 'Kerry Gregg';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tony Young', allocation_reason = 'Specialises in all used cars and has balanced lead numbers'\n",
            "WHERE `Name` = 'Perry Terry';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Spam', allocation_reason = 'Spam enquiry'\n",
            "WHERE `Name` = 'Mairead Bo';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tim Green', allocation_reason = 'Specialises in New BMW and has balanced lead numbers'\n",
            "WHERE `Name` = 'Dave Young';\n",
            "\n",
            "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tim Green', allocation_reason = 'Specialises in New BMW and has balanced lead numbers'\n",
            "WHERE `Name` = 'Barry O Brien';\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "allocations_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "EHatB3noU7oE",
        "outputId": "0f15075e-710f-4b0f-fc5b-27b26bc76ee9"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   No           Name Sales Person  \\\n",
              "0   7    Jeff Stubbs   Tony Young   \n",
              "1   9     Fred Flynn   Brid Flynn   \n",
              "2   3     Arron Wise         Spam   \n",
              "3   5       Josh Tas     Tom Pops   \n",
              "4   2      Joe Peats     Tom Pops   \n",
              "5  10    Kerry Gregg   Tony Young   \n",
              "6   8    Perry Terry   Tony Young   \n",
              "7   4     Mairead Bo         Spam   \n",
              "8   1     Dave Young    Tim Green   \n",
              "9   6  Barry O Brien    Tim Green   \n",
              "\n",
              "                                   allocation_reason  \n",
              "0  Specialises in all used cars and has balanced ...  \n",
              "1  Requested Brid specifically and has balanced l...  \n",
              "2                                       Spam enquiry  \n",
              "3  Specialises in New Nissan and has balanced lea...  \n",
              "4  Specialises in New Nissan and has balanced lea...  \n",
              "5  Specialises in all used cars and has balanced ...  \n",
              "6  Specialises in all used cars and has balanced ...  \n",
              "7                                       Spam enquiry  \n",
              "8  Specialises in New BMW and has balanced lead n...  \n",
              "9  Specialises in New BMW and has balanced lead n...  "
            ],
            "text/html": [
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              "  <div id=\"df-0fbb0aac-ca41-4690-96f6-d121e8e2d207\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
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              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>No</th>\n",
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              "      <td>4</td>\n",
              "      <td>Mairead Bo</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
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              "      <td>6</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0fbb0aac-ca41-4690-96f6-d121e8e2d207')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        document.querySelector('#df-0fbb0aac-ca41-4690-96f6-d121e8e2d207 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-0fbb0aac-ca41-4690-96f6-d121e8e2d207');\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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              "        element.appendChild(docLink);\n",
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              "\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
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              "</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",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    border-radius: 50%;\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
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              "\n",
              "  .colab-df-spinner {\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
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              "    }\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-e3344c8f-70b4-4104-8da2-185f753a0cac button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_d2e48369-e87e-4190-a4c9-f6e60fb01b8f\">\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('allocations_df')\"\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_d2e48369-e87e-4190-a4c9-f6e60fb01b8f button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('allocations_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "allocations_df",
              "summary": "{\n  \"name\": \"allocations_df\",\n  \"rows\": 10,\n  \"fields\": [\n    {\n      \"column\": \"No\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 1,\n        \"max\": 10,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          1,\n          9,\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"Dave Young\",\n          \"Fred Flynn\",\n          \"Kerry Gregg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sales Person\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Brid Flynn\",\n          \"Tim Green\",\n          \"Spam\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"allocation_reason\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"Requested Brid specifically and has balanced lead numbers\",\n          \"Specialises in New BMW and has balanced lead numbers\",\n          \"Spam enquiry\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.cloud import bigquery\n",
        "# Initialize BigQuery client\n",
        "client = bigquery.Client(project='bigquerycourse-onetwothree')\n",
        "\n",
        "# Split the update_code string into individual queries\n",
        "queries = update_code.strip().split(';')\n",
        "\n",
        "# Execute each query\n",
        "for query in queries:\n",
        "    if query.strip():  # Ensure the query is not empty\n",
        "        query = query.strip() + ';'  # Ensure the query ends with a semicolon\n",
        "        print(f\"Executing query: {query}\")  # For debugging purposes\n",
        "        client.query(query).result()\n",
        "\n",
        "print(\"All updates executed successfully.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NcsgwthdX9RV",
        "outputId": "9f0d127d-5429-4dcb-84ea-b3a86f89423c"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tony Young', allocation_reason = 'Specialises in all used cars and has balanced lead numbers'\n",
            "WHERE `Name` = 'Jeff Stubbs';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Brid Flynn', allocation_reason = 'Requested Brid specifically and has balanced lead numbers'\n",
            "WHERE `Name` = 'Fred Flynn';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Spam', allocation_reason = 'Spam enquiry'\n",
            "WHERE `Name` = 'Arron Wise';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tom Pops', allocation_reason = 'Specialises in New Nissan and has balanced lead numbers'\n",
            "WHERE `Name` = 'Josh Tas';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tom Pops', allocation_reason = 'Specialises in New Nissan and has balanced lead numbers'\n",
            "WHERE `Name` = 'Joe Peats';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tony Young', allocation_reason = 'Specialises in all used cars and has balanced lead numbers'\n",
            "WHERE `Name` = 'Kerry Gregg';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tony Young', allocation_reason = 'Specialises in all used cars and has balanced lead numbers'\n",
            "WHERE `Name` = 'Perry Terry';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Spam', allocation_reason = 'Spam enquiry'\n",
            "WHERE `Name` = 'Mairead Bo';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tim Green', allocation_reason = 'Specialises in New BMW and has balanced lead numbers'\n",
            "WHERE `Name` = 'Dave Young';\n",
            "Executing query: UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
            "SET Allocated = True, `Sales Person` = 'Tim Green', allocation_reason = 'Specialises in New BMW and has balanced lead numbers'\n",
            "WHERE `Name` = 'Barry O Brien';\n",
            "All updates executed successfully.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Big Query Magic Commands"
      ],
      "metadata": {
        "id": "hqi2xJ5EaiVr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Rename Table Column\n",
        "%%bigquery --project bigquerycourse-onetwothree\n",
        "ALTER TABLE `bigquerycourse-onetwothree.test.Leads`\n",
        "RENAME COLUMN `Enquiry ` TO `Enquiry`;"
      ],
      "metadata": {
        "id": "QiOF_qIxJY_1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Add Column to table\n",
        "%%bigquery --project bigquerycourse-onetwothree\n",
        "ALTER TABLE `bigquerycourse-onetwothree.test.Leads`\n",
        "ADD COLUMN allocation_reason STRING;"
      ],
      "metadata": {
        "id": "HxzkbxsvKVkt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Update Row\n",
        "%%bigquery --project bigquerycourse-onetwothree\n",
        "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
        "SET `Sales Person` = 'New Sales Person 1',\n",
        "    allocation_reason = 'Reason for allocation 1',\n",
        "    Allocated = True\n",
        "WHERE `Name` = 'Arron Wise';\n",
        "\n",
        "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
        "SET `Sales Person` = 'New Sales Person 2',\n",
        "    allocation_reason = 'Reason for allocation 2',\n",
        "    Allocated = True\n",
        "WHERE `Name` = 'Jeff Stubbs';"
      ],
      "metadata": {
        "id": "AOu8cQ91Kavg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Reset Allocations\n",
        "%%bigquery --project bigquerycourse-onetwothree\n",
        "\n",
        "UPDATE `bigquerycourse-onetwothree.test.Leads`\n",
        "SET Allocated = False , `Sales Person` = NULL, allocation_reason = NULL\n",
        "Where `Enquiry` is not null;"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85,
          "referenced_widgets": [
            "20fe54f2dba14175954e72693b260c73",
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            "a36537a4915a431b8440f4898706bd22"
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        "id": "meUUOvIjES9E",
        "outputId": "7d9d772b-5045-4eac-ae49-c82b18cfd170"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Query is running:   0%|          |"
            ],
            "application/vnd.jupyter.widget-view+json": {
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              "model_id": "20fe54f2dba14175954e72693b260c73"
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          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: []\n",
              "Index: []"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-89db3bcd-fba5-4e00-b494-d56b39223aa3\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-89db3bcd-fba5-4e00-b494-d56b39223aa3')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
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              "      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-89db3bcd-fba5-4e00-b494-d56b39223aa3 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-89db3bcd-fba5-4e00-b494-d56b39223aa3');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"get_ipython()\",\n  \"rows\": 0,\n  \"fields\": []\n}"
            }
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    }
  ]
}