crop_recommendation_1.ipynb

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          "output_type": "stream",
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          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import random\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "import plotly.graph_objects as go\n",
        "import plotly.express as px\n",
        "from plotly.subplots import make_subplots"
      ],
      "metadata": {
        "id": "0mVd-NsQeAqf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.read_csv(\"/content/drive/MyDrive/AgriWise/ML/crop-recommendation/Crop_recommendation1.csv\")\n",
        "data.head()"
      ],
      "metadata": {
        "colab": {
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          "height": 206
        },
        "id": "RwIwR9QYf3r6",
        "outputId": "4b78ea2b-da04-46f8-a909-7e94b19452ca"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    N   P   K  temperature   humidity        ph    rainfall label\n",
              "0  90  42  43    20.879744  82.002744  6.502985  202.935536  rice\n",
              "1  85  58  41    21.770462  80.319644  7.038096  226.655537  rice\n",
              "2  60  55  44    23.004459  82.320763  7.840207  263.964248  rice\n",
              "3  74  35  40    26.491096  80.158363  6.980401  242.864034  rice\n",
              "4  78  42  42    20.130175  81.604873  7.628473  262.717340  rice"
            ],
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              "      <th></th>\n",
              "      <th>N</th>\n",
              "      <th>P</th>\n",
              "      <th>K</th>\n",
              "      <th>temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>ph</th>\n",
              "      <th>rainfall</th>\n",
              "      <th>label</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>90</td>\n",
              "      <td>42</td>\n",
              "      <td>43</td>\n",
              "      <td>20.879744</td>\n",
              "      <td>82.002744</td>\n",
              "      <td>6.502985</td>\n",
              "      <td>202.935536</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>85</td>\n",
              "      <td>58</td>\n",
              "      <td>41</td>\n",
              "      <td>21.770462</td>\n",
              "      <td>80.319644</td>\n",
              "      <td>7.038096</td>\n",
              "      <td>226.655537</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
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              "      <td>82.320763</td>\n",
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              "      <td>263.964248</td>\n",
              "      <td>rice</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>74</td>\n",
              "      <td>35</td>\n",
              "      <td>40</td>\n",
              "      <td>26.491096</td>\n",
              "      <td>80.158363</td>\n",
              "      <td>6.980401</td>\n",
              "      <td>242.864034</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>78</td>\n",
              "      <td>42</td>\n",
              "      <td>42</td>\n",
              "      <td>20.130175</td>\n",
              "      <td>81.604873</td>\n",
              "      <td>7.628473</td>\n",
              "      <td>262.717340</td>\n",
              "      <td>rice</td>\n",
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              "          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",
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      "source": [
        "data.isnull().any()"
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        },
        "id": "O_IN5kaagisu",
        "outputId": "e9eb0685-548a-4f91-bc83-966ac7b00541"
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          "data": {
            "text/plain": [
              "N              False\n",
              "P              False\n",
              "K              False\n",
              "temperature    False\n",
              "humidity       False\n",
              "ph             False\n",
              "rainfall       False\n",
              "label          False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rkxVMVQOgKVb",
        "outputId": "fd4f5a4e-4d73-49d7-a904-c501839e1e17"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2200, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fqWzeIRSgRCU",
        "outputId": "dddbae30-5014-4f35-acbe-0a3cd95b18fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['N', 'P', 'K', 'temperature', 'humidity', 'ph', 'rainfall', 'label'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Number of classes = \", len(data['label'].unique()))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RNyDQ2P0gWje",
        "outputId": "3c372b8f-d56c-4364-d054-4a9b9c6888ac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of classes =  22\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"crops name: \", data['label'].unique())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MYn8C6Kig0m_",
        "outputId": "e6dda8a9-cfcb-4123-e235-48618336ca87"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "crops name:  ['rice' 'maize' 'chickpea' 'kidneybeans' 'pigeonpeas' 'mothbeans'\n",
            " 'mungbean' 'blackgram' 'lentil' 'pomegranate' 'banana' 'mango' 'grapes'\n",
            " 'watermelon' 'muskmelon' 'apple' 'orange' 'papaya' 'coconut' 'cotton'\n",
            " 'jute' 'coffee']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['label'].value_counts()"
      ],
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        },
        "id": "Ihwdx53Tg_36",
        "outputId": "cb6f2525-0c04-4350-8934-8d7abb1ff96f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "rice           100\n",
              "maize          100\n",
              "jute           100\n",
              "cotton         100\n",
              "coconut        100\n",
              "papaya         100\n",
              "orange         100\n",
              "apple          100\n",
              "muskmelon      100\n",
              "watermelon     100\n",
              "grapes         100\n",
              "mango          100\n",
              "banana         100\n",
              "pomegranate    100\n",
              "lentil         100\n",
              "blackgram      100\n",
              "mungbean       100\n",
              "mothbeans      100\n",
              "pigeonpeas     100\n",
              "kidneybeans    100\n",
              "chickpea       100\n",
              "coffee         100\n",
              "Name: label, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.describe()"
      ],
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        "colab": {
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          "height": 300
        },
        "id": "MmbItTS-pmqD",
        "outputId": "cc4a39f0-a3c4-40aa-bb9b-c5aed6e362e4"
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      "execution_count": null,
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          "data": {
            "text/plain": [
              "                 N            P            K  temperature     humidity  \\\n",
              "count  2200.000000  2200.000000  2200.000000  2200.000000  2200.000000   \n",
              "mean     50.551818    53.362727    48.149091    25.616244    71.481779   \n",
              "std      36.917334    32.985883    50.647931     5.063749    22.263812   \n",
              "min       0.000000     5.000000     5.000000     8.825675    14.258040   \n",
              "25%      21.000000    28.000000    20.000000    22.769375    60.261953   \n",
              "50%      37.000000    51.000000    32.000000    25.598693    80.473146   \n",
              "75%      84.250000    68.000000    49.000000    28.561654    89.948771   \n",
              "max     140.000000   145.000000   205.000000    43.675493    99.981876   \n",
              "\n",
              "                ph     rainfall  \n",
              "count  2200.000000  2200.000000  \n",
              "mean      6.469480   103.463655  \n",
              "std       0.773938    54.958389  \n",
              "min       3.504752    20.211267  \n",
              "25%       5.971693    64.551686  \n",
              "50%       6.425045    94.867624  \n",
              "75%       6.923643   124.267508  \n",
              "max       9.935091   298.560117  "
            ],
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>N</th>\n",
              "      <th>P</th>\n",
              "      <th>K</th>\n",
              "      <th>temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>ph</th>\n",
              "      <th>rainfall</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>50.551818</td>\n",
              "      <td>53.362727</td>\n",
              "      <td>48.149091</td>\n",
              "      <td>25.616244</td>\n",
              "      <td>71.481779</td>\n",
              "      <td>6.469480</td>\n",
              "      <td>103.463655</td>\n",
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              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>36.917334</td>\n",
              "      <td>32.985883</td>\n",
              "      <td>50.647931</td>\n",
              "      <td>5.063749</td>\n",
              "      <td>22.263812</td>\n",
              "      <td>0.773938</td>\n",
              "      <td>54.958389</td>\n",
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              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>8.825675</td>\n",
              "      <td>14.258040</td>\n",
              "      <td>3.504752</td>\n",
              "      <td>20.211267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>21.000000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>22.769375</td>\n",
              "      <td>60.261953</td>\n",
              "      <td>5.971693</td>\n",
              "      <td>64.551686</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>37.000000</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>25.598693</td>\n",
              "      <td>80.473146</td>\n",
              "      <td>6.425045</td>\n",
              "      <td>94.867624</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>84.250000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>28.561654</td>\n",
              "      <td>89.948771</td>\n",
              "      <td>6.923643</td>\n",
              "      <td>124.267508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>140.000000</td>\n",
              "      <td>145.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>43.675493</td>\n",
              "      <td>99.981876</td>\n",
              "      <td>9.935091</td>\n",
              "      <td>298.560117</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "                                                     [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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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "crop_mean_value = pd.pivot_table(data,index=['label'],aggfunc='mean')\n",
        "crop_mean_value.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "Hjmb8iKChGeK",
        "outputId": "8b322d8a-4aac-4627-f197-58bc1a24bf0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                K       N       P   humidity        ph    rainfall  \\\n",
              "label                                                                \n",
              "apple      199.89   20.80  134.22  92.333383  5.929663  112.654779   \n",
              "banana      50.05  100.23   82.01  80.358123  5.983893  104.626980   \n",
              "blackgram   19.24   40.02   67.47  65.118426  7.133952   67.884151   \n",
              "chickpea    79.92   40.09   67.79  16.860439  7.336957   80.058977   \n",
              "coconut     30.59   21.98   16.93  94.844272  5.976562  175.686646   \n",
              "\n",
              "           temperature  \n",
              "label                   \n",
              "apple        22.630942  \n",
              "banana       27.376798  \n",
              "blackgram    29.973340  \n",
              "chickpea     18.872847  \n",
              "coconut      27.409892  "
            ],
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              "      <th>K</th>\n",
              "      <th>N</th>\n",
              "      <th>P</th>\n",
              "      <th>humidity</th>\n",
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              "      <th>rainfall</th>\n",
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              "      <th>apple</th>\n",
              "      <td>199.89</td>\n",
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              "      <th>banana</th>\n",
              "      <td>50.05</td>\n",
              "      <td>100.23</td>\n",
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              "      <th>blackgram</th>\n",
              "      <td>19.24</td>\n",
              "      <td>40.02</td>\n",
              "      <td>67.47</td>\n",
              "      <td>65.118426</td>\n",
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              "      <th>chickpea</th>\n",
              "      <td>79.92</td>\n",
              "      <td>40.09</td>\n",
              "      <td>67.79</td>\n",
              "      <td>16.860439</td>\n",
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              "    <tr>\n",
              "      <th>coconut</th>\n",
              "      <td>30.59</td>\n",
              "      <td>21.98</td>\n",
              "      <td>16.93</td>\n",
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              "          const element = document.querySelector('#df-560106bd-1016-408e-b3c2-953cb02a87f3');\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "colorarray = ['#0592D0','#Cd7f32', '#E97451', '#Bdb76b', '#954535', '#C2b280', '#808000','#C2b280', '#E4d008', '#9acd32', '#Eedc82', '#E4d96f',\n",
        "           '#32cd32','#39ff14','#00ff7f', '#008080', '#36454f', '#F88379', '#Ff4500', '#Ffb347', '#A94064', '#E75480', '#Ffb6c1', '#E5e4e2',\n",
        "           '#Faf0e6', '#8c92ac', '#Dbd7d2','#A7a6ba', '#B38b6d']"
      ],
      "metadata": {
        "id": "jw-0DVnniqyT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def Element_analysis (values,code,name):\n",
        "  fig = make_subplots(rows=1, cols=2)\n",
        "\n",
        "  top = {\n",
        "      'y' : values[code][0:10].sort_values().index,\n",
        "      'x' : values[code][0:10].sort_values()\n",
        "  }\n",
        "\n",
        "  last = {\n",
        "      'y' : values[code][-10:].index,\n",
        "      'x' : values[code][-10:]\n",
        "  }\n",
        "\n",
        "  fig.add_trace(\n",
        "      go.Bar(top,\n",
        "            name=\"Most \"+name+\" required\",\n",
        "            marker_color=random.choice(colorarray),\n",
        "            orientation='h',\n",
        "            text=top['x']),\n",
        "      \n",
        "      row=1, col=1\n",
        "  )\n",
        "\n",
        "  fig.add_trace(\n",
        "      go.Bar(last,\n",
        "            name=\"Least \"+name+\" required\",\n",
        "            marker_color=random.choice(colorarray),\n",
        "            orientation='h',\n",
        "            text=last['x']),\n",
        "      row=1, col=2\n",
        "  )\n",
        "  fig.update_traces(texttemplate='%{text}', textposition='inside')\n",
        "  fig.update_layout(title_text=name,\n",
        "                    plot_bgcolor='white',\n",
        "                    font_size=12, \n",
        "                    font_color='black',\n",
        "                  height=500)\n",
        "\n",
        "  fig.update_xaxes(showgrid=False)\n",
        "  fig.update_yaxes(showgrid=False)\n",
        "  fig.show()\n",
        "\n"
      ],
      "metadata": {
        "id": "ySX6ygnjjcIq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "Nitrogen Analysis\n"
      ],
      "metadata": {
        "id": "Q8JSYpjRjKLR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "Nitrogen = crop_mean_value.sort_values(by='N', ascending=False)\n",
        "Element_analysis(Nitrogen,'N',\"Nitrogen\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "8sVsXEUShrur",
        "outputId": "2ba9004b-0d45-4a29-9809-55e9d1eda7d4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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      "source": [
        "\n",
        "Phosphorus Analysis\n"
      ],
      "metadata": {
        "id": "7XGmZ2jVjOTE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Phosphorus=crop_mean_value.sort_values(by='P', ascending=False)\n",
        "Element_analysis(Phosphorus,'P',\"Phosphorus\")"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "g5RPnC1Li1t4",
        "outputId": "edec5a02-6bbe-405a-a26d-54c79e8ab279"
      },
      "execution_count": null,
      "outputs": [
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    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "Potassium analysis\n"
      ],
      "metadata": {
        "id": "t63ArZnhmK-x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Potassium=crop_mean_value.sort_values(by='K', ascending=False)\n",
        "Element_analysis(Potassium,'K',\"Potassium\")\n"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "AeGK3QzflvQH",
        "outputId": "630f1a9d-9b84-4dc5-947f-4c7db4ff7d50"
      },
      "execution_count": null,
      "outputs": [
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    {
      "cell_type": "markdown",
      "source": [
        "ratio of element for some crops"
      ],
      "metadata": {
        "id": "DLF2Qn7QmxCb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def Element_ratio(name):\n",
        "  labels = ['Nitrogen(N)','Phosphorous(P)','Potash(K)']\n",
        "  fig = make_subplots(rows=1, cols=5, specs=[[{'type':'domain'}, {'type':'domain'},\n",
        "                                              {'type':'domain'}, {'type':'domain'}, \n",
        "                                              {'type':'domain'}]])\n",
        "\n",
        "  element_npk = crop_mean_value[crop_mean_value.index==name]\n",
        "  values = [element_npk['N'][0], element_npk['P'][0], element_npk['K'][0]]\n",
        "  fig.add_trace(go.Pie(labels=labels, values=values,name=\"Rice\"),1, 1)\n",
        "  fig.show()"
      ],
      "metadata": {
        "id": "cKh90-nxmb_N"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Element_ratio('apple')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "xV1wDP6jntCm",
        "outputId": "0fed0380-a3a6-4f40-ae91-f7d77b02a4a4"
      },
      "execution_count": null,
      "outputs": [
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    {
      "cell_type": "markdown",
      "source": [
        "Comparision between rainfall, temerature and humidity"
      ],
      "metadata": {
        "id": "78mLqLooogVT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig = px.bar(crop_mean_value, x=crop_mean_value.index, y=[\"rainfall\", \"temperature\", \"humidity\"])\n",
        "fig.update_xaxes(showgrid=False)\n",
        "fig.update_yaxes(showgrid=False)\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "JxMBipuYoHUR",
        "outputId": "7c10b8d7-89e9-4bf6-d13d-ed00c6265680"
      },
      "execution_count": null,
      "outputs": [
        {
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            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.jointplot(x=\"rainfall\",y=\"humidity\",data=data[(data['temperature']<40) & \n",
        "                                                  (data['rainfall']>40)],height=10,hue=\"label\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 746
        },
        "id": "IOnkh6_fqEpt",
        "outputId": "f9f62074-f7fc-4463-dc91-1d4f4e172334"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x7f090ee4a160>"
            ]
          },
          "metadata": {},
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Correlation between features"
      ],
      "metadata": {
        "id": "OJxRC-Fqo9Be"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(1, 1, figsize=(15, 9))\n",
        "sns.heatmap(data.corr(), annot=True,cmap='viridis' )\n",
        "ax.set(xlabel='features')\n",
        "ax.set(ylabel='features')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 555
        },
        "id": "ab9_sAwkoxlZ",
        "outputId": "36602d79-b277-49f3-d939-d67bd0b850af"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x648 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "features=data.drop('label', axis=1)\n",
        "y=data['label']"
      ],
      "metadata": {
        "id": "KmpSGt-3pIkp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn import metrics \n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.linear_model import LogisticRegression"
      ],
      "metadata": {
        "id": "bkQsNlQ_qqw6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Split dataset into train and test "
      ],
      "metadata": {
        "id": "6T9IUufeq0X6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(features, y, test_size = 0.2,\n",
        "                                                    shuffle = True, random_state = 42)\n",
        "acc=[]\n",
        "model=[]"
      ],
      "metadata": {
        "id": "Dgg1TsdMqzJM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "DecisionTree"
      ],
      "metadata": {
        "id": "XYddFD2rrp2n"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "DT = DecisionTreeClassifier(criterion=\"entropy\",random_state=42,max_depth=5)\n",
        "\n",
        "DT.fit(X_train,y_train)\n",
        "\n",
        "predicted_values = DT.predict(X_test)\n",
        "x = metrics.accuracy_score(y_test, predicted_values)\n",
        "acc.append(x)\n",
        "model.append('Decision Tree')\n",
        "print(\"Decision Tree's Accuracy is: \", x*100)\n",
        "\n",
        "print(metrics.classification_report(y_test,predicted_values))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RHItlZ3xrM-2",
        "outputId": "8a16e26b-b00d-4092-c0f1-3a222157db0a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Decision Tree's Accuracy is:  86.5909090909091\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        23\n",
            "      banana       1.00      1.00      1.00        21\n",
            "   blackgram       0.61      1.00      0.75        20\n",
            "    chickpea       1.00      0.96      0.98        26\n",
            "     coconut       0.96      0.96      0.96        27\n",
            "      coffee       1.00      1.00      1.00        17\n",
            "      cotton       1.00      1.00      1.00        17\n",
            "      grapes       1.00      1.00      1.00        14\n",
            "        jute       0.63      0.96      0.76        23\n",
            " kidneybeans       0.00      0.00      0.00        20\n",
            "      lentil       0.42      1.00      0.59        11\n",
            "       maize       1.00      1.00      1.00        21\n",
            "       mango       1.00      1.00      1.00        19\n",
            "   mothbeans       0.00      0.00      0.00        24\n",
            "    mungbean       1.00      1.00      1.00        19\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        14\n",
            "      papaya       1.00      0.87      0.93        23\n",
            "  pigeonpeas       0.59      1.00      0.74        23\n",
            " pomegranate       1.00      0.91      0.95        23\n",
            "        rice       0.92      0.63      0.75        19\n",
            "  watermelon       1.00      1.00      1.00        19\n",
            "\n",
            "    accuracy                           0.87       440\n",
            "   macro avg       0.82      0.88      0.84       440\n",
            "weighted avg       0.82      0.87      0.83       440\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n",
            "/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n",
            "/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "score = cross_val_score(DT, features, y,cv=5)\n",
        "print('Cross validation score: ',score)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XpmQLs4Es1r5",
        "outputId": "d29af496-5eec-4111-c503-54d70073e6f3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cross validation score:  [0.93636364 0.91136364 0.92045455 0.87272727 0.93636364]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dt_train_accuracy = DT.score(X_train,y_train)\n",
        "print(\"Training accuracy = \",dt_train_accuracy)\n",
        "dt_test_accuracy = DT.score(X_test,y_test)\n",
        "print(\"Testing accuracy = \",dt_test_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0NLRn0uQtc9U",
        "outputId": "f14b7276-4927-4a88-dbee-9b958fbb2b9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training accuracy =  0.8875\n",
            "Testing accuracy =  0.865909090909091\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = DT.predict(X_test)\n",
        "y_true = y_test\n",
        "cm_dt = confusion_matrix(y_true,y_pred)\n",
        "f, ax = plt.subplots(figsize=(15,10))\n",
        "sns.heatmap(cm_dt, annot=True, linewidth=0.5, fmt=\".0f\",  cmap='viridis', ax = ax)\n",
        "plt.xlabel(\"Predicted\")\n",
        "plt.ylabel(\"Actual\")\n",
        "plt.title('Predicted vs actual')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "h3do4mXMuKKb",
        "outputId": "0575db40-bb31-4aea-9c91-024871fbfe4a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RandomForest"
      ],
      "metadata": {
        "id": "iBjb8a9yun85"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "\n",
        "RF = RandomForestClassifier(n_estimators=20, random_state=0)\n",
        "RF.fit(X_train,y_train)\n",
        "predicted_values = RF.predict(X_test)\n",
        "x = metrics.accuracy_score(y_test, predicted_values)\n",
        "acc.append(x)\n",
        "model.append('RF')\n",
        "print(\"Random Forest Accuracy is: \", x)\n",
        "\n",
        "print(metrics.classification_report(y_test,predicted_values))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "11yjDCBCubx7",
        "outputId": "2879bc25-56ef-4675-9893-90f1609c4723"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Random Forest Accuracy is:  0.9931818181818182\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        23\n",
            "      banana       1.00      1.00      1.00        21\n",
            "   blackgram       1.00      1.00      1.00        20\n",
            "    chickpea       1.00      1.00      1.00        26\n",
            "     coconut       1.00      1.00      1.00        27\n",
            "      coffee       1.00      1.00      1.00        17\n",
            "      cotton       1.00      1.00      1.00        17\n",
            "      grapes       1.00      1.00      1.00        14\n",
            "        jute       0.92      1.00      0.96        23\n",
            " kidneybeans       1.00      1.00      1.00        20\n",
            "      lentil       0.92      1.00      0.96        11\n",
            "       maize       1.00      1.00      1.00        21\n",
            "       mango       1.00      1.00      1.00        19\n",
            "   mothbeans       1.00      0.96      0.98        24\n",
            "    mungbean       1.00      1.00      1.00        19\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        14\n",
            "      papaya       1.00      1.00      1.00        23\n",
            "  pigeonpeas       1.00      1.00      1.00        23\n",
            " pomegranate       1.00      1.00      1.00        23\n",
            "        rice       1.00      0.89      0.94        19\n",
            "  watermelon       1.00      1.00      1.00        19\n",
            "\n",
            "    accuracy                           0.99       440\n",
            "   macro avg       0.99      0.99      0.99       440\n",
            "weighted avg       0.99      0.99      0.99       440\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "score = cross_val_score(RF,features,y,cv=5)\n",
        "print('Cross validation score: ',score)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "55hchC1Yuyrt",
        "outputId": "9c5b613a-eac5-4d97-b1ef-b748b863ae6f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cross validation score:  [0.99772727 0.99545455 0.99772727 0.99318182 0.98863636]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rf_train_accuracy = RF.score(X_train,y_train)\n",
        "print(\"Training accuracy = \",rf_train_accuracy)\n",
        "rf_test_accuracy = RF.score(X_test,y_test)\n",
        "print(\"Testing accuracy = \",rf_test_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NO3NRCOovAQ2",
        "outputId": "a653ce84-5e8a-4047-d0aa-8f45e2c1fbc2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training accuracy =  1.0\n",
            "Testing accuracy =  0.9931818181818182\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = RF.predict(X_test)\n",
        "y_true = y_test\n",
        "cm_rf = confusion_matrix(y_true,y_pred)\n",
        "f, ax = plt.subplots(figsize=(15,10))\n",
        "sns.heatmap(cm_rf, annot=True, linewidth=0.5, fmt=\".0f\",  cmap='viridis', ax = ax)\n",
        "plt.xlabel(\"Predicted\")\n",
        "plt.ylabel(\"Actual\")\n",
        "plt.title('Predicted vs actual')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "w47YBFkfvHzt",
        "outputId": "8edc9c33-b9a4-4f29-cd76-706806434758"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "NaiveBayes"
      ],
      "metadata": {
        "id": "oVutQC93vsmu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "NaiveBayes = GaussianNB()\n",
        "NaiveBayes.fit(X_train,y_train)\n",
        "predicted_values = NaiveBayes.predict(X_test)\n",
        "x = metrics.accuracy_score(y_test, predicted_values)\n",
        "acc.append(x)\n",
        "model.append('Naive Bayes')\n",
        "print(\"Naive Bayes Accuracy is: \", x)\n",
        "print(metrics.classification_report(y_test,predicted_values))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LqPil210vWzp",
        "outputId": "5bea0424-a3f2-44a5-8d97-8238aed2442b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Naive Bayes Accuracy is:  0.9954545454545455\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        23\n",
            "      banana       1.00      1.00      1.00        21\n",
            "   blackgram       1.00      1.00      1.00        20\n",
            "    chickpea       1.00      1.00      1.00        26\n",
            "     coconut       1.00      1.00      1.00        27\n",
            "      coffee       1.00      1.00      1.00        17\n",
            "      cotton       1.00      1.00      1.00        17\n",
            "      grapes       1.00      1.00      1.00        14\n",
            "        jute       0.92      1.00      0.96        23\n",
            " kidneybeans       1.00      1.00      1.00        20\n",
            "      lentil       1.00      1.00      1.00        11\n",
            "       maize       1.00      1.00      1.00        21\n",
            "       mango       1.00      1.00      1.00        19\n",
            "   mothbeans       1.00      1.00      1.00        24\n",
            "    mungbean       1.00      1.00      1.00        19\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        14\n",
            "      papaya       1.00      1.00      1.00        23\n",
            "  pigeonpeas       1.00      1.00      1.00        23\n",
            " pomegranate       1.00      1.00      1.00        23\n",
            "        rice       1.00      0.89      0.94        19\n",
            "  watermelon       1.00      1.00      1.00        19\n",
            "\n",
            "    accuracy                           1.00       440\n",
            "   macro avg       1.00      1.00      1.00       440\n",
            "weighted avg       1.00      1.00      1.00       440\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "score = cross_val_score(NaiveBayes,features,y,cv=5)\n",
        "print('Cross validation score: ',score)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kd4yZGd1v4kV",
        "outputId": "63cbb946-57c8-4658-af53-ac9978bc357f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cross validation score:  [0.99772727 0.99545455 0.99545455 0.99545455 0.99090909]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nv_train_accuracy = NaiveBayes.score(X_train,y_train)\n",
        "print(\"Training accuracy = \",nv_train_accuracy)\n",
        "nv_test_accuracy = NaiveBayes.score(X_test,y_test)\n",
        "print(\"Testing accuracy = \",nv_test_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3BkgGZ6AwA_B",
        "outputId": "5d34b18a-f8af-4869-bf91-29a5a2312507"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training accuracy =  0.9948863636363636\n",
            "Testing accuracy =  0.9954545454545455\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = NaiveBayes.predict(X_test)\n",
        "y_true = y_test\n",
        "cm_rf = confusion_matrix(y_true,y_pred)\n",
        "f, ax = plt.subplots(figsize=(15,10))\n",
        "sns.heatmap(cm_rf, annot=True, linewidth=0.5, fmt=\".0f\",  cmap='viridis', ax = ax)\n",
        "plt.xlabel(\"Predicted\")\n",
        "plt.ylabel(\"Actual\")\n",
        "plt.title('Predicted vs actual')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "8zwoxQKXwhMc",
        "outputId": "cc9eb91f-2edc-4b78-e8aa-06219cbf7505"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "SVM"
      ],
      "metadata": {
        "id": "DXkIGACe0JKp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "SVM = SVC(gamma='auto')\n",
        "SVM.fit(X_train,y_train)\n",
        "predicted_values = SVM.predict(X_test)\n",
        "x = metrics.accuracy_score(y_test, predicted_values)\n",
        "acc.append(x)\n",
        "model.append('SVM')\n",
        "print(\"SVM's Accuracy is: \", x)\n",
        "print(metrics.classification_report(y_test,predicted_values))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z-Dsczm40Hf5",
        "outputId": "9610fb81-6295-4760-b15a-e7bdceff3304"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SVM's Accuracy is:  0.09090909090909091\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      0.13      0.23        23\n",
            "      banana       1.00      0.05      0.09        21\n",
            "   blackgram       1.00      0.05      0.10        20\n",
            "    chickpea       0.00      0.00      0.00        26\n",
            "     coconut       1.00      0.07      0.14        27\n",
            "      coffee       1.00      0.06      0.11        17\n",
            "      cotton       1.00      0.18      0.30        17\n",
            "      grapes       1.00      0.07      0.13        14\n",
            "        jute       1.00      0.04      0.08        23\n",
            " kidneybeans       0.00      0.00      0.00        20\n",
            "      lentil       0.03      1.00      0.05        11\n",
            "       maize       0.00      0.00      0.00        21\n",
            "       mango       1.00      0.11      0.19        19\n",
            "   mothbeans       0.00      0.00      0.00        24\n",
            "    mungbean       1.00      0.11      0.19        19\n",
            "   muskmelon       1.00      0.59      0.74        17\n",
            "      orange       0.00      0.00      0.00        14\n",
            "      papaya       0.00      0.00      0.00        23\n",
            "  pigeonpeas       0.00      0.00      0.00        23\n",
            " pomegranate       1.00      0.04      0.08        23\n",
            "        rice       0.00      0.00      0.00        19\n",
            "  watermelon       1.00      0.05      0.10        19\n",
            "\n",
            "    accuracy                           0.09       440\n",
            "   macro avg       0.59      0.12      0.12       440\n",
            "weighted avg       0.59      0.09      0.11       440\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n",
            "/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n",
            "/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py:1318: UndefinedMetricWarning:\n",
            "\n",
            "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "score = cross_val_score(SVM,features,y,cv=5)\n",
        "print('Cross validation score: ',score)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FSR-rqRU0oZD",
        "outputId": "6913501d-0ab6-4f9b-e8dc-42c2a079a13b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cross validation score:  [0.27727273 0.28863636 0.29090909 0.275      0.26818182]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "svm_train_accuracy =SVM.score(X_train,y_train)\n",
        "print(\"Training accuracy = \",svm_train_accuracy)\n",
        "svm_test_accuracy = SVM.score(X_test,y_test)\n",
        "print(\"Testing accuracy = \",svm_test_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "atptxU850o42",
        "outputId": "1b0c4e96-a447-4210-c2ed-1ebe080cd14c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training accuracy =  1.0\n",
            "Testing accuracy =  0.09090909090909091\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = SVM.predict(X_test)\n",
        "y_true = y_test\n",
        "cm_rf = confusion_matrix(y_true,y_pred)\n",
        "f, ax = plt.subplots(figsize=(15,10))\n",
        "sns.heatmap(cm_rf, annot=True, linewidth=0.5, fmt=\".0f\",  cmap='viridis', ax = ax)\n",
        "plt.xlabel(\"Predicted\")\n",
        "plt.ylabel(\"Actual\")\n",
        "plt.title('Predicted vs actual')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "DrKf1Zma1BjL",
        "outputId": "a6262fb6-4594-4948-e789-bb699af0e0c5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Logistic Regression"
      ],
      "metadata": {
        "id": "WEoBYkRA3b5f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "LogReg = LogisticRegression(random_state=2)\n",
        "LogReg.fit(X_train,y_train)\n",
        "predicted_values = LogReg.predict(X_test)\n",
        "x = metrics.accuracy_score(y_test, predicted_values)\n",
        "acc.append(x)\n",
        "model.append('Logistic Regression')\n",
        "print(\"Logistic Regression's Accuracy is: \", x)\n",
        "print(metrics.classification_report(y_test,predicted_values))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eoXN6PKl1v4Z",
        "outputId": "9173d064-cebc-4928-e0e8-aacd8ec6b96f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Logistic Regression's Accuracy is:  0.9454545454545454\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        23\n",
            "      banana       0.95      1.00      0.98        21\n",
            "   blackgram       0.83      0.75      0.79        20\n",
            "    chickpea       1.00      1.00      1.00        26\n",
            "     coconut       1.00      1.00      1.00        27\n",
            "      coffee       0.94      1.00      0.97        17\n",
            "      cotton       0.80      0.94      0.86        17\n",
            "      grapes       1.00      1.00      1.00        14\n",
            "        jute       0.91      0.87      0.89        23\n",
            " kidneybeans       1.00      0.95      0.97        20\n",
            "      lentil       0.83      0.91      0.87        11\n",
            "       maize       0.94      0.76      0.84        21\n",
            "       mango       0.95      1.00      0.97        19\n",
            "   mothbeans       0.85      0.92      0.88        24\n",
            "    mungbean       0.95      1.00      0.97        19\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        14\n",
            "      papaya       0.95      0.91      0.93        23\n",
            "  pigeonpeas       0.95      0.91      0.93        23\n",
            " pomegranate       1.00      1.00      1.00        23\n",
            "        rice       0.89      0.89      0.89        19\n",
            "  watermelon       1.00      1.00      1.00        19\n",
            "\n",
            "    accuracy                           0.95       440\n",
            "   macro avg       0.94      0.95      0.94       440\n",
            "weighted avg       0.95      0.95      0.94       440\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning:\n",
            "\n",
            "lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "log_train_accuracy =LogReg.score(X_train,y_train)\n",
        "print(\"Training accuracy = \",log_train_accuracy)\n",
        "log_test_accuracy = LogReg.score(X_test,y_test)\n",
        "print(\"Testing accuracy = \",svm_test_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IPjwSRFq1wGW",
        "outputId": "d21f0f3f-cec5-4820-ff7f-d463b773b56d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training accuracy =  0.9761363636363637\n",
            "Testing accuracy =  0.09090909090909091\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = LogReg.predict(X_test)\n",
        "y_true = y_test\n",
        "cm_rf = confusion_matrix(y_true,y_pred)\n",
        "f, ax = plt.subplots(figsize=(15,10))\n",
        "sns.heatmap(cm_rf, annot=True, linewidth=0.5, fmt=\".0f\",  cmap='viridis', ax = ax)\n",
        "plt.xlabel(\"Predicted\")\n",
        "plt.ylabel(\"Actual\")\n",
        "plt.title('Predicted vs actual')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "8gbAqRwL1wUl",
        "outputId": "d675f902-665a-40eb-e07f-f06c8a5a81bb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Accuracy comparison"
      ],
      "metadata": {
        "id": "Y0NzKtQBxFdq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=[15,7],dpi = 100, facecolor='white')\n",
        "plt.title('Accuracy Comparison')\n",
        "plt.xlabel('Accuracy')\n",
        "plt.ylabel('ML Algorithms')\n",
        "sns.barplot(x = acc,y = model,palette='viridis')\n",
        "plt.savefig('plot.png', dpi=300, bbox_inches='tight')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "id": "uTYqxLemxBgJ",
        "outputId": "bf0926e2-8e2b-44d2-df01-de1dafea606b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x700 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "label = ['Decision Tree','Random Forest','Naive Bayes','SVM','Logistic Regression']\n",
        "Test = [dt_test_accuracy,rf_test_accuracy,\n",
        "        nv_test_accuracy,svm_test_accuracy,log_test_accuracy]\n",
        "Train = [ dt_train_accuracy, rf_train_accuracy,\n",
        "         nv_train_accuracy,svm_train_accuracy,log_train_accuracy]\n",
        "f, ax = plt.subplots(figsize=(20,7)) \n",
        "X_axis = np.arange(len(label))\n",
        "plt.bar(X_axis - 0.2,Test, 0.4, label = 'Test', color=('midnightblue'))\n",
        "plt.bar(X_axis + 0.2,Train, 0.4, label = 'Train', color=('mediumaquamarine'))\n",
        "plt.xticks(X_axis, label)\n",
        "plt.xlabel(\"ML algorithms\")\n",
        "plt.ylabel(\"Accuracy\")\n",
        "plt.title(\"Testing vs Training Accuracy\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "y6_Z0G_wxnze",
        "outputId": "d76eb3db-b194-4e62-9b0e-7c473db32504"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "new=RF.predict([[90, 42, 43, 20.879744, 75, 5.5,220]])\n",
        "new"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7tKqMIi6yYYT",
        "outputId": "eaeecb51-3144-40c4-d463-6fa02e483668"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/base.py:450: UserWarning:\n",
            "\n",
            "X does not have valid feature names, but RandomForestClassifier was fitted with feature names\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['rice'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L7puvyivy8io",
        "outputId": "c3c52ab9-4300-4eba-f58a-b99823096abc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['jute'], dtype='<U11')"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "_hzqWP-SzDSt"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}