cslab3.ipynb

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        "<a href=\"https://colab.research.google.com/github/Ganesh-Borkar/CSLab/blob/main/cslab3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "\n",
        "# ***Borkar Ganesh Prakash***\n",
        "# ***Roll No-20***"
      ],
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        "id": "CrovZFdAgrZ1"
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      "source": [
        "# ***Assignment No 4***\n",
        "Apply Basic PCA on the iris dataset. The data set is available at:\n",
        "https://raw.github.com/neurospin/pystatsml/master/datasets/iris.csv\n",
        "• Describe the data set. Should the dataset been standardized?\n",
        "• Describe the structure of correlations among variables.\n",
        "• Compute a PCA with the maximum number of components\n",
        ".• Compute the cumulative explained variance ratio. Determine the number of\n",
        "components𝐾by your computed values.\n",
        "• Print the𝐾principal components directions and correlations of the𝐾principal\n",
        "compo-nents with the original variables. Interpret the contribution of the original\n",
        "variables into the PC.\n",
        "• Plot the samples projected into the𝐾first PCs.\n",
        "• Color samples by their species."
      ],
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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.decomposition import PCA\n",
        "%matplotlib inline\n"
      ]
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    {
      "cell_type": "code",
      "source": [
        "iris=pd.read_csv(\"/content/iris.csv\")"
      ],
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        "id": "GspvQSgzlsTx"
      },
      "execution_count": 4,
      "outputs": []
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      "source": [
        "iris.head()\n"
      ],
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          "height": 206
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      "execution_count": 5,
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              "   sepal.length  sepal.width  petal.length  petal.width variety\n",
              "0           5.1          3.5           1.4          0.2  Setosa\n",
              "1           4.9          3.0           1.4          0.2  Setosa\n",
              "2           4.7          3.2           1.3          0.2  Setosa\n",
              "3           4.6          3.1           1.5          0.2  Setosa\n",
              "4           5.0          3.6           1.4          0.2  Setosa"
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              "      <th>sepal.length</th>\n",
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              "      <th>petal.length</th>\n",
              "      <th>petal.width</th>\n",
              "      <th>variety</th>\n",
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              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Setosa</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Setosa</td>\n",
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              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
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              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Setosa</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
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              "      <th>4</th>\n",
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        "\n",
        "iris.info()"
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 150 entries, 0 to 149\n",
            "Data columns (total 5 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   sepal.length  150 non-null    float64\n",
            " 1   sepal.width   150 non-null    float64\n",
            " 2   petal.length  150 non-null    float64\n",
            " 3   petal.width   150 non-null    float64\n",
            " 4   variety       150 non-null    object \n",
            "dtypes: float64(4), object(1)\n",
            "memory usage: 6.0+ KB\n"
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            "text/plain": [
              "       sepal.length  sepal.width  petal.length  petal.width\n",
              "count    150.000000   150.000000    150.000000   150.000000\n",
              "mean       5.843333     3.057333      3.758000     1.199333\n",
              "std        0.828066     0.435866      1.765298     0.762238\n",
              "min        4.300000     2.000000      1.000000     0.100000\n",
              "25%        5.100000     2.800000      1.600000     0.300000\n",
              "50%        5.800000     3.000000      4.350000     1.300000\n",
              "75%        6.400000     3.300000      5.100000     1.800000\n",
              "max        7.900000     4.400000      6.900000     2.500000"
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              "      <th>count</th>\n",
              "      <td>150.000000</td>\n",
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              "      <td>150.000000</td>\n",
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              "      <th>mean</th>\n",
              "      <td>5.843333</td>\n",
              "      <td>3.057333</td>\n",
              "      <td>3.758000</td>\n",
              "      <td>1.199333</td>\n",
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              "      <th>std</th>\n",
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              "      <td>0.762238</td>\n",
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              "      <th>min</th>\n",
              "      <td>4.300000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.100000</td>\n",
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              "      <th>25%</th>\n",
              "      <td>5.100000</td>\n",
              "      <td>2.800000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>0.300000</td>\n",
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              "      <th>50%</th>\n",
              "      <td>5.800000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>4.350000</td>\n",
              "      <td>1.300000</td>\n",
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              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>6.400000</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>5.100000</td>\n",
              "      <td>1.800000</td>\n",
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              "      <th>max</th>\n",
              "      <td>7.900000</td>\n",
              "      <td>4.400000</td>\n",
              "      <td>6.900000</td>\n",
              "      <td>2.500000</td>\n",
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              "<Figure size 432x288 with 2 Axes>"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca = PCA()\n",
        "x_new1 =pca.fit_transform(iris.drop([\"variety\"],axis =1))\n",
        "x_new1[:5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "PedE_-4yFWDQ",
        "outputId": "db313424-d41e-4a9c-8ec3-12fe1104e265"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-2.68412563e+00,  3.19397247e-01, -2.79148276e-02,\n",
              "        -2.26243707e-03],\n",
              "       [-2.71414169e+00, -1.77001225e-01, -2.10464272e-01,\n",
              "        -9.90265503e-02],\n",
              "       [-2.88899057e+00, -1.44949426e-01,  1.79002563e-02,\n",
              "        -1.99683897e-02],\n",
              "       [-2.74534286e+00, -3.18298979e-01,  3.15593736e-02,\n",
              "         7.55758166e-02],\n",
              "       [-2.72871654e+00,  3.26754513e-01,  9.00792406e-02,\n",
              "         6.12585926e-02]])"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "explained_variance= pca.explained_variance_ratio_\n",
        "\n",
        "explained_variance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "8xh1SvjkHYVM",
        "outputId": "4d98e5da-4b44-42dc-c007-c98d1d302c7c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.92461872, 0.05306648, 0.01710261, 0.00521218])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize =(10,6))\n",
        "plt.bar(range(4),explained_variance, alpha=0.5, align='center', label =\"Individual Explained Variance\", color =\"darkred\")\n",
        "plt.ylabel(\"Explained Variance Ratio\")\n",
        "plt.xlabel(\"Principal Component\")\n",
        "plt.legend(loc =\"best\")\n",
        "plt.tight_layout()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "QBu6D4UUHz6E",
        "outputId": "7d29ca89-2b31-4dd6-da0a-7f7f59832552"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca  = PCA(n_components=3)\n",
        "x_new =pca.fit_transform(iris.drop(['variety'],axis =1))\n",
        "x_new[:5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "xH_TK2GwH4Xw",
        "outputId": "fb7ef404-9665-468d-b823-7691a5b5b1d7"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-2.68412563,  0.31939725, -0.02791483],\n",
              "       [-2.71414169, -0.17700123, -0.21046427],\n",
              "       [-2.88899057, -0.14494943,  0.01790026],\n",
              "       [-2.74534286, -0.31829898,  0.03155937],\n",
              "       [-2.72871654,  0.32675451,  0.09007924]])"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "categ_num ={\"variety\":{\"setosa\":0,\"versicolor\":1,\"virginica\":2}}\n",
        "iris1 = iris.replace(categ_num)\n",
        "columns = list(iris.columns[:4])"
      ],
      "metadata": {
        "id": "wJvWYUHxIkdb"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axes =plt.subplots(3,4,figsize =(15,10))\n",
        "k= 0\n",
        "for i in range(axes.shape[0]):\n",
        "    for j in range(axes.shape[1]):\n",
        "        axes[i,j].scatter(x_new[:,i],iris[columns[j]],c =\"r\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 594
        },
        "id": "zmeFrXtDIuBa",
        "outputId": "a488ad5a-9d95-45a8-eacc-af6cd106d546"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 12 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "FjbcrA5zJXif"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}