InsuranceSales_.ipynb

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        "<a href=\"https://colab.research.google.com/github/fjadidi2001/DataScienceJourney/blob/master/InsuranceSales_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
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      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv(\"hf://datasets/infinite-dataset-hub/InsuranceSales/data.csv\")"
      ]
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        "df.head()"
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              "   idx  CustomerID  Age  Gender     Region InsuranceType PurchaseHistory  \\\n",
              "0    0       12345   45    Male  Northwest          Life      2 policies   \n",
              "1    1       23456   34  Female  Southeast        Health        1 policy   \n",
              "2    2       34567   29    Male  Northeast          Auto      3 policies   \n",
              "3    3       45678   50  Female    Midwest          Home      2 policies   \n",
              "4    4       56789   42    Male      South          Life        1 policy   \n",
              "\n",
              "   ServiceInteractions PredictedRiskCategory  PredictedNextPurchaseAmount  \\\n",
              "0                    3                Medium                         5000   \n",
              "1                    1                  High                        12000   \n",
              "2                    2                   Low                         1500   \n",
              "3                    4                Medium                         8000   \n",
              "4                    2                  High                         7000   \n",
              "\n",
              "               Label  \n",
              "0      CustomerLoyal  \n",
              "1  CustomerPotential  \n",
              "2       CustomerSafe  \n",
              "3     CustomerAtRisk  \n",
              "4      CustomerLoyal  "
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