CrewAI_data_analyst_Agent.ipynb

{
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      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WUDZ6jpzrwAd",
        "outputId": "16d0b3d0-d687-49c3-8846-b9aa00bf6563"
      },
      "outputs": [],
      "source": [
        "#install Libraries\n",
        "pip install crewai crewai_tools openai"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "eW9WNTZ_P_Az"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "\n",
        "os.environ[\"OPENAI_API_KEY\"] = 'your api key'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "from crewai import Agent, Task, Crew\n",
        "from crewai_tools import FileReadTool\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        },
        "id": "yCqg12DPQsNp",
        "outputId": "ba34d69c-d790-4142-c102-b4398aad8ee9"
      },
      "outputs": [
        {
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 156,\n  \"fields\": [\n    {\n      \"column\": \"Crop\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Oil palm fruit\",\n          \"Rubber, natural\",\n          \"Cocoa, beans\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precipitation (mm day-1)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 289.45791446544206,\n        \"min\": 1934.62,\n        \"max\": 3085.79,\n        \"num_unique_values\": 39,\n        \"samples\": [\n          2604.59,\n          2967.41,\n          2344.72\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Specific Humidity at 2 Meters (g/kg)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.29392256031822384,\n        \"min\": 17.54,\n        \"max\": 18.7,\n        \"num_unique_values\": 33,\n        \"samples\": [\n          18.5,\n          18.2,\n          18.34\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Relative Humidity at 2 Meters (%)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.9962263288344806,\n        \"min\": 82.11,\n        \"max\": 86.1,\n        \"num_unique_values\": 38,\n        \"samples\": [\n          83.65,\n          84.85,\n          84.12\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Temperature at 2 Meters (C)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2610498622941692,\n        \"min\": 25.56,\n        \"max\": 26.81,\n        \"num_unique_values\": 29,\n        \"samples\": [\n          26.46,\n          26.18,\n          26.27\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Yield\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 70421,\n        \"min\": 5249,\n        \"max\": 203399,\n        \"num_unique_values\": 155,\n        \"samples\": [\n          26648,\n          9612,\n          7066\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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              "variable_name": "df"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Crop</th>\n",
              "      <th>Precipitation (mm day-1)</th>\n",
              "      <th>Specific Humidity at 2 Meters (g/kg)</th>\n",
              "      <th>Relative Humidity at 2 Meters (%)</th>\n",
              "      <th>Temperature at 2 Meters (C)</th>\n",
              "      <th>Yield</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Cocoa, beans</td>\n",
              "      <td>2248.92</td>\n",
              "      <td>17.72</td>\n",
              "      <td>83.40</td>\n",
              "      <td>26.01</td>\n",
              "      <td>11560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Cocoa, beans</td>\n",
              "      <td>1938.42</td>\n",
              "      <td>17.54</td>\n",
              "      <td>82.11</td>\n",
              "      <td>26.11</td>\n",
              "      <td>11253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Cocoa, beans</td>\n",
              "      <td>2301.54</td>\n",
              "      <td>17.81</td>\n",
              "      <td>82.79</td>\n",
              "      <td>26.24</td>\n",
              "      <td>9456</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Cocoa, beans</td>\n",
              "      <td>2592.35</td>\n",
              "      <td>17.61</td>\n",
              "      <td>85.07</td>\n",
              "      <td>25.56</td>\n",
              "      <td>9321</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Cocoa, beans</td>\n",
              "      <td>2344.72</td>\n",
              "      <td>17.61</td>\n",
              "      <td>84.12</td>\n",
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            "text/plain": [
              "           Crop  Precipitation (mm day-1)  \\\n",
              "0  Cocoa, beans                   2248.92   \n",
              "1  Cocoa, beans                   1938.42   \n",
              "2  Cocoa, beans                   2301.54   \n",
              "3  Cocoa, beans                   2592.35   \n",
              "4  Cocoa, beans                   2344.72   \n",
              "\n",
              "   Specific Humidity at 2 Meters (g/kg)  Relative Humidity at 2 Meters (%)  \\\n",
              "0                                 17.72                              83.40   \n",
              "1                                 17.54                              82.11   \n",
              "2                                 17.81                              82.79   \n",
              "3                                 17.61                              85.07   \n",
              "4                                 17.61                              84.12   \n",
              "\n",
              "   Temperature at 2 Meters (C)  Yield  \n",
              "0                        26.01  11560  \n",
              "1                        26.11  11253  \n",
              "2                        26.24   9456  \n",
              "3                        25.56   9321  \n",
              "4                        25.76   8800  "
            ]
          },
          "execution_count": 45,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "\n",
        "df=pd.read_csv('/content/crop_yield_prediction.csv')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q6udl03Zf_SG",
        "outputId": "144a54cc-b973-4fc3-fc33-472ef43fa687"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:opentelemetry.trace:Overriding of current TracerProvider is not allowed\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[1m\u001b[95m# Agent:\u001b[00m \u001b[1m\u001b[92mData Analyst\u001b[00m\n",
            "\u001b[95m## Task:\u001b[00m \u001b[92mPerform an exploratory data analysis on the dataset. Identify key features, detect missing values, and summarize correlations.\u001b[00m\n",
            "\n",
            "\n",
            "\u001b[1m\u001b[95m# Agent:\u001b[00m \u001b[1m\u001b[92mData Analyst\u001b[00m\n",
            "\u001b[95m## Thought:\u001b[00m \u001b[92mI need to start by reading the content of the dataset to begin the exploratory data analysis.\u001b[00m\n",
            "\u001b[95m## Using tool:\u001b[00m \u001b[92mRead a file's content\u001b[00m\n",
            "\u001b[95m## Tool Input:\u001b[00m \u001b[92m\n",
            "\"{\\\"file_path\\\": \\\"/content/crop_yield_prediction.csv\\\"}\"\u001b[00m\n",
            "\u001b[95m## Tool Output:\u001b[00m \u001b[92m\n",
            "Crop,Precipitation (mm day-1),Specific Humidity at 2 Meters (g/kg),Relative Humidity at 2 Meters (%),Temperature at 2 Meters (C),Yield\n",
            "\"Cocoa, beans\",2248.92,17.72,83.4,26.01,11560\n",
            "\"Cocoa, beans\",1938.42,17.54,82.11,26.11,11253\n",
            "\"Cocoa, beans\",2301.54,17.81,82.79,26.24,9456\n",
            "\"Cocoa, beans\",2592.35,17.61,85.07,25.56,9321\n",
            "\"Cocoa, beans\",2344.72,17.61,84.12,25.76,8800\n",
            "\"Cocoa, beans\",2339.3,17.7,84.54,25.76,8850\n",
            "\"Cocoa, beans\",2326.09,18.09,84.63,26.11,9003\n",
            "\"Cocoa, beans\",2718.08,18.3,85.43,26.12,9880\n",
            "\"Cocoa, beans\",2061.61,17.8,84.36,25.88,9201\n",
            "\"Cocoa, beans\",1934.62,17.94,83.43,26.21,8300\n",
            "\"Cocoa, beans\",2217.12,18.03,84.39,26.1,5765\n",
            "\"Cocoa, beans\",2249.7,18.01,84.24,26.11,5812\n",
            "\"Cocoa, beans\",2530.96,18.15,85.33,26.02,6667\n",
            "\"Cocoa, beans\",2504.7,18.19,85.45,26.02,6530\n",
            "\"Cocoa, beans\",2686.2,18.38,85.77,26.13,6912\n",
            "\"Cocoa, beans\",2414.79,18.18,85.76,25.93,7138\n",
            "\"Cocoa, beans\",1999.53,18.2,84.36,26.27,7525\n",
            "\"Cocoa, beans\",2362.8,18.7,84.03,26.79,7663\n",
            "\"Cocoa, beans\",2792.95,18.24,86.04,25.95,8300\n",
            "\"Cocoa, beans\",2751.24,18.31,85.98,26.02,9274\n",
            "\"Cocoa, beans\",2646.28,18.4,86.02,26.1,9956\n",
            "\"Cocoa, beans\",2302.99,18.22,84.48,26.25,9801\n",
            "\"Cocoa, beans\",2692.34,18.37,85.54,26.18,7965\n",
            "\"Cocoa, beans\",2424.55,18.28,85.16,26.18,7919\n",
            "\"Cocoa, beans\",2363.63,18.35,84.92,26.28,8226\n",
            "\"Cocoa, beans\",2892.78,18.49,86.09,26.18,10062\n",
            "\"Cocoa, beans\",2729.53,18.41,86.03,26.11,12362\n",
            "\"Cocoa, beans\",3085.79,18.34,86.1,26.03,13056\n",
            "\"Cocoa, beans\",2922.18,18.43,85.51,26.23,10058\n",
            "\"Cocoa, beans\",2546.33,18.43,84.23,26.49,7795\n",
            "\"Cocoa, beans\",2938.29,18.22,85.42,26.06,10737\n",
            "\"Cocoa, beans\",2771.73,18.38,84.98,26.3,7979\n",
            "\"Cocoa, beans\",2607.96,18.37,84.67,26.35,7066\n",
            "\"Cocoa, beans\",2604.59,18.19,83.44,26.43,7991\n",
            "\"Cocoa, beans\",2308.51,18.27,83.65,26.47,11108\n",
            "\"Cocoa, beans\",2410.13,18.58,83.45,26.81,11487\n",
            "\"Cocoa, beans\",2967.41,18.67,85.48,26.46,7314\n",
            "\"Cocoa, beans\",2333.46,18.5,84.85,26.43,9502\n",
            "\"Cocoa, beans\",2109.34,18.51,83.52,26.72,8848\n",
            "Oil palm fruit,2248.92,17.72,83.4,26.01,169783\n",
            "Oil palm fruit,1938.42,17.54,82.11,26.11,201436\n",
            "Oil palm fruit,2301.54,17.81,82.79,26.24,152343\n",
            "Oil palm fruit,2592.35,17.61,85.07,25.56,181826\n",
            "Oil palm fruit,2344.72,17.61,84.12,25.76,178183\n",
            "Oil palm fruit,2339.3,17.7,84.54,25.76,169781\n",
            "Oil palm fruit,2326.09,18.09,84.63,26.11,166042\n",
            "Oil palm fruit,2718.08,18.3,85.43,26.12,165262\n",
            "Oil palm fruit,2061.61,17.8,84.36,25.88,183004\n",
            "Oil palm fruit,1934.62,17.94,83.43,26.21,177543\n",
            "Oil palm fruit,2217.12,18.03,84.39,26.1,150428\n",
            "Oil palm fruit,2249.7,18.01,84.24,26.11,151070\n",
            "Oil palm fruit,2530.96,18.15,85.33,26.02,172165\n",
            "Oil palm fruit,2504.7,18.19,85.45,26.02,160862\n",
            "Oil palm fruit,2686.2,18.38,85.77,26.13,166136\n",
            "Oil palm fruit,2414.79,18.18,85.76,25.93,163541\n",
            "Oil palm fruit,1999.53,18.2,84.36,26.27,164772\n",
            "Oil palm fruit,2362.8,18.7,84.03,26.79,142425\n",
            "Oil palm fruit,2792.95,18.24,86.04,25.95,165993\n",
            "Oil palm fruit,2751.24,18.31,85.98,26.02,167621\n",
            "Oil palm fruit,2646.28,18.4,86.02,26.1,168476\n",
            "Oil palm fruit,2302.99,18.22,84.48,26.25,162240\n",
            "Oil palm fruit,2692.34,18.37,85.54,26.18,175629\n",
            "Oil palm fruit,2424.55,18.28,85.16,26.18,180323\n",
            "Oil palm fruit,2363.63,18.35,84.92,26.28,184629\n",
            "Oil palm fruit,2892.78,18.49,86.09,26.18,190626\n",
            "Oil palm fruit,2729.53,18.41,86.03,26.11,183544\n",
            "Oil palm fruit,3085.79,18.34,86.1,26.03,195523\n",
            "Oil palm fruit,2922.18,18.43,85.51,26.23,182696\n",
            "Oil palm fruit,2546.33,18.43,84.23,26.49,171189\n",
            "Oil palm fruit,2938.29,18.22,85.42,26.06,185831\n",
            "Oil palm fruit,2771.73,18.38,84.98,26.3,186959\n",
            "Oil palm fruit,2607.96,18.37,84.67,26.35,181496\n",
            "Oil palm fruit,2604.59,18.19,83.44,26.43,203399\n",
            "Oil palm fruit,2308.51,18.27,83.65,26.47,202379\n",
            "Oil palm fruit,2410.13,18.58,83.45,26.81,172601\n",
            "Oil palm fruit,2967.41,18.67,85.48,26.46,199074\n",
            "Oil palm fruit,2333.46,18.5,84.85,26.43,189657\n",
            "Oil palm fruit,2109.34,18.51,83.52,26.72,189896\n",
            "\"Rice, paddy\",2248.92,17.72,83.4,26.01,28409\n",
            "\"Rice, paddy\",1938.42,17.54,82.11,26.11,27619\n",
            "\"Rice, paddy\",2301.54,17.81,82.79,26.24,26041\n",
            "\"Rice, paddy\",2592.35,17.61,85.07,25.56,25187\n",
            "\"Rice, paddy\",2344.72,17.61,84.12,25.76,26648\n",
            "\"Rice, paddy\",2339.3,17.7,84.54,25.76,26399\n",
            "\"Rice, paddy\",2326.09,18.09,84.63,26.11,24686\n",
            "\"Rice, paddy\",2718.08,18.3,85.43,26.12,25251\n",
            "\"Rice, paddy\",2061.61,17.8,84.36,25.88,26251\n",
            "\"Rice, paddy\",1934.62,17.94,83.43,26.21,27694\n",
            "\"Rice, paddy\",2217.12,18.03,84.39,26.1,28178\n",
            "\"Rice, paddy\",2249.7,18.01,84.24,26.11,29918\n",
            "\"Rice, paddy\",2530.96,18.15,85.33,26.02,30348\n",
            "\"Rice, paddy\",2504.7,18.19,85.45,26.02,30614\n",
            "\"Rice, paddy\",2686.2,18.38,85.77,26.13,31619\n",
            "\"Rice, paddy\",2414.79,18.18,85.76,25.93,32510\n",
            "\"Rice, paddy\",1999.53,18.2,84.36,26.27,30676\n",
            "\"Rice, paddy\",2362.8,18.7,84.03,26.79,28829\n",
            "\"Rice, paddy\",2792.95,18.24,86.04,25.95,29415\n",
            "\"Rice, paddy\",2751.24,18.31,85.98,26.02,30640\n",
            "\"Rice, paddy\",2646.28,18.4,86.02,26.1,31101\n",
            "\"Rice, paddy\",2302.99,18.22,84.48,26.25,32385\n",
            "\"Rice, paddy\",2692.34,18.37,85.54,26.18,33596\n",
            "\"Rice, paddy\",2424.55,18.28,85.16,26.18,33260\n",
            "\"Rice, paddy\",2363.63,18.35,84.92,26.28,34221\n",
            "\"Rice, paddy\",2892.78,18.49,86.09,26.18,33907\n",
            "\"Rice, paddy\",2729.53,18.41,86.03,26.11,35277\n",
            "\"Rice, paddy\",3085.79,18.34,86.1,26.03,35836\n",
            "\"Rice, paddy\",2922.18,18.43,85.51,26.23,37205\n",
            "\"Rice, paddy\",2546.33,18.43,84.23,26.49,36361\n",
            "\"Rice, paddy\",2938.29,18.22,85.42,26.06,37468\n",
            "\"Rice, paddy\",2771.73,18.38,84.98,26.3,37972\n",
            "\"Rice, paddy\",2607.96,18.37,84.67,26.35,38763\n",
            "\"Rice, paddy\",2604.59,18.19,83.44,26.43,29855\n",
            "\"Rice, paddy\",2308.51,18.27,83.65,26.47,40223\n",
            "\"Rice, paddy\",2410.13,18.58,83.45,26.81,39775\n",
            "\"Rice, paddy\",2967.41,18.67,85.48,26.46,37496\n",
            "\"Rice, paddy\",2333.46,18.5,84.85,26.43,37704\n",
            "\"Rice, paddy\",2109.34,18.51,83.52,26.72,42550\n",
            "\"Rubber, natural\",2248.92,17.72,83.4,26.01,9322\n",
            "\"Rubber, natural\",1938.42,17.54,82.11,26.11,9223\n",
            "\"Rubber, natural\",2301.54,17.81,82.79,26.24,9866\n",
            "\"Rubber, natural\",2592.35,17.61,85.07,25.56,9718\n",
            "\"Rubber, natural\",2344.72,17.61,84.12,25.76,9573\n",
            "\"Rubber, natural\",2339.3,17.7,84.54,25.76,10024\n",
            "\"Rubber, natural\",2326.09,18.09,84.63,26.11,10285\n",
            "\"Rubber, natural\",2718.08,18.3,85.43,26.12,10010\n",
            "\"Rubber, natural\",2061.61,17.8,84.36,25.88,8604\n",
            "\"Rubber, natural\",1934.62,17.94,83.43,26.21,8002\n",
            "\"Rubber, natural\",2217.12,18.03,84.39,26.1,6913\n",
            "\"Rubber, natural\",2249.7,18.01,84.24,26.11,6546\n",
            "\"Rubber, natural\",2530.96,18.15,85.33,26.02,6077\n",
            "\"Rubber, natural\",2504.7,18.19,85.45,26.02,6333\n",
            "\"Rubber, natural\",2686.2,18.38,85.77,26.13,6448\n",
            "\"Rubber, natural\",2414.79,18.18,85.76,25.93,6562\n",
            "\"Rubber, natural\",1999.53,18.2,84.36,26.27,6008\n",
            "\"Rubber, natural\",2362.8,18.7,84.03,26.79,5693\n",
            "\"Rubber, natural\",2792.95,18.24,86.04,25.95,5249\n",
            "\"Rubber, natural\",2751.24,18.31,85.98,26.02,6484\n",
            "\"Rubber, natural\",2646.28,18.4,86.02,26.1,6348\n",
            "\"Rubber, natural\",2302.99,18.22,84.48,26.25,6597\n",
            "\"Rubber, natural\",2692.34,18.37,85.54,26.18,7435\n",
            "\"Rubber, natural\",2424.55,18.28,85.16,26.18,9139\n",
            "\"Rubber, natural\",2363.63,18.35,84.92,26.28,8857\n",
            "\"Rubber, natural\",2892.78,18.49,86.09,26.18,10159\n",
            "\"Rubber, natural\",2729.53,18.41,86.03,26.11,9612\n",
            "\"Rubber, natural\",3085.79,18.34,86.1,26.03,8599\n",
            "\"Rubber, natural\",2922.18,18.43,85.51,26.23,8337\n",
            "\"Rubber, natural\",2546.33,18.43,84.23,26.49,9205\n",
            "\"Rubber, natural\",2938.29,18.22,85.42,26.06,9701\n",
            "\"Rubber, natural\",2771.73,18.38,84.98,26.3,8865\n",
            "\"Rubber, natural\",2607.96,18.37,84.67,26.35,7817\n",
            "\"Rubber, natural\",2604.59,18.19,83.44,26.43,6275\n",
            "\"Rubber, natural\",2308.51,18.27,83.65,26.47,6721\n",
            "\"Rubber, natural\",2410.13,18.58,83.45,26.81,6248\n",
            "\"Rubber, natural\",2967.41,18.67,85.48,26.46,6842\n",
            "\"Rubber, natural\",2333.46,18.5,84.85,26.43,5571\n",
            "\"Rubber, natural\",2109.34,18.51,83.52,26.72,5903\u001b[00m\n",
            "\n",
            "\n",
            "\u001b[1m\u001b[95m# Agent:\u001b[00m \u001b[1m\u001b[92mData Analyst\u001b[00m\n",
            "\u001b[95m## Final Answer:\u001b[00m \u001b[92m\n",
            "The dataset contains information on Crop, Precipitation, Specific Humidity at 2 Meters, Relative Humidity at 2 Meters, Temperature at 2 Meters, and Crop Yield for Cocoa beans, Oil palm fruit, Rice paddy, and Rubber natural.\n",
            "\n",
            "Key Features: \n",
            "- Crops: Cocoa beans, Oil palm fruit, Rice paddy, and Rubber natural.\n",
            "- Climate Factors: Precipitation, Specific Humidity, Relative Humidity, Temperature.\n",
            "- Crop Yield: Yield of each crop.\n",
            "\n",
            "Missing Values: \n",
            "There do not appear to be any missing values in the dataset provided.\n",
            "\n",
            "Correlations:\n",
            "- There may be correlations present between the climate factors (Precipitation, Specific Humidity, Relative Humidity, Temperature) and the Crop Yield for each crop. Further analysis and statistical tests are needed to confirm these correlations.\n",
            "\n",
            "Additional Insights: \n",
            "- Further analysis, such as data visualization, statistical tests, and machine learning models, can provide more detailed insights into the relationships between climate factors and crop yield.\n",
            "- It would be beneficial to explore the trends and patterns within each crop type individually to understand specific factors affecting crop yield.\u001b[00m\n",
            "\n",
            "\n",
            "The dataset contains information on Crop, Precipitation, Specific Humidity at 2 Meters, Relative Humidity at 2 Meters, Temperature at 2 Meters, and Crop Yield for Cocoa beans, Oil palm fruit, Rice paddy, and Rubber natural.\n",
            "\n",
            "Key Features: \n",
            "- Crops: Cocoa beans, Oil palm fruit, Rice paddy, and Rubber natural.\n",
            "- Climate Factors: Precipitation, Specific Humidity, Relative Humidity, Temperature.\n",
            "- Crop Yield: Yield of each crop.\n",
            "\n",
            "Missing Values: \n",
            "There do not appear to be any missing values in the dataset provided.\n",
            "\n",
            "Correlations:\n",
            "- There may be correlations present between the climate factors (Precipitation, Specific Humidity, Relative Humidity, Temperature) and the Crop Yield for each crop. Further analysis and statistical tests are needed to confirm these correlations.\n",
            "\n",
            "Additional Insights: \n",
            "- Further analysis, such as data visualization, statistical tests, and machine learning models, can provide more detailed insights into the relationships between climate factors and crop yield.\n",
            "- It would be beneficial to explore the trends and patterns within each crop type individually to understand specific factors affecting crop yield.\n"
          ]
        }
      ],
      "source": [
        "# Define tools\n",
        "csv_tool = FileReadTool(file_path='/content/crop_yield_prediction.csv')\n",
        "\n",
        "# Define the Data Analyst agent\n",
        "data_analyst = Agent(\n",
        "    role='Data Analyst',\n",
        "    goal='Analyze the dataset to provide actionable insights.',\n",
        "    verbose=True,\n",
        "    memory=True,\n",
        "    backstory=(\n",
        "        \"You are an expert in data analysis, proficient in identifying trends, patterns, and correlations.\"\n",
        "    ),\n",
        "    tools=[csv_tool],\n",
        "    allow_delegation=True\n",
        ")\n",
        "\n",
        "# Analysis task to analyze the dataset\n",
        "analysis_task = Task(\n",
        "    description=(\n",
        "        \"Perform an exploratory data analysis on the dataset. Identify key features, detect missing values, and summarize correlations.\"\n",
        "    ),\n",
        "    expected_output='A detailed summary of dataset analysis, including missing values, correlations, and key insights.',\n",
        "    tools=[csv_tool],\n",
        "    agent=data_analyst\n",
        ")\n",
        "\n",
        "# Create the crew\n",
        "data_crew = Crew(\n",
        "    agents=[data_analyst],\n",
        "    tasks=[analysis_task],\n",
        "    process=\"sequential\"\n",
        ")\n",
        "\n",
        "# Simulate execution\n",
        "if __name__ == \"__main__\":\n",
        "    # Trigger the crew execution\n",
        "    results = data_crew.kickoff()\n",
        "\n",
        "    # Print the final results\n",
        "    print(results)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-NcmUnJkbMjf"
      },
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "base",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.7"
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  },
  "nbformat": 4,
  "nbformat_minor": 0
}