REGRESSION_BMI_sone.ipynb

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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bmi = pd.read_csv('bmi.csv')"
      ],
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      "execution_count": 6,
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        "bmi.head()"
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              "   Gender  Height  Weight  Index\n",
              "0    Male     174      96      4\n",
              "1    Male     189      87      2\n",
              "2  Female     185     110      4\n",
              "3  Female     195     104      3\n",
              "4    Male     149      61      3"
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              "      <th>Gender</th>\n",
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        "bmi.shape"
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          "data": {
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              "(500, 4)"
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          "execution_count": 8
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      "source": [
        "bmi.dtypes"
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      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Gender    object\n",
              "Height     int64\n",
              "Weight     int64\n",
              "Index      int64\n",
              "dtype: object"
            ]
          },
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          "execution_count": 10
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 500 entries, 0 to 499\n",
            "Data columns (total 4 columns):\n",
            " #   Column  Non-Null Count  Dtype \n",
            "---  ------  --------------  ----- \n",
            " 0   Gender  500 non-null    object\n",
            " 1   Height  500 non-null    int64 \n",
            " 2   Weight  500 non-null    int64 \n",
            " 3   Index   500 non-null    int64 \n",
            "dtypes: int64(3), object(1)\n",
            "memory usage: 15.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bmi.Gender.nunique()"
      ],
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            "text/plain": [
              "2"
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          "execution_count": 12
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        "bmi.Gender.unique()"
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      "execution_count": 13,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "array(['Male', 'Female'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "plt.style.use('ggplot')\n",
        "# histogram of the weight\n",
        "bmi.Weight.plot(kind='hist', color='blue', edgecolor='black', figsize=(10,7))\n",
        "plt.title('Distribution of Weight', size=24)\n",
        "plt.xlabel('Weight (pounds)', size=18)\n",
        "plt.ylabel('Frequency', size=18);"
      ],
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      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# histogram of the height\n",
        "bmi.Height.plot(kind='hist', color='purple', edgecolor='black', figsize=(10,7))\n",
        "plt.title('Distribution of Height', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Frequency', size=18)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 492
        },
        "id": "zUpuJ9rwhVKQ",
        "outputId": "e43864df-835f-46e9-d9b2-a69beb98decc"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Frequency')"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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FER8fb1+mKg9pvdRyF9ccHx9vb2dgYKDh4eFh3/+vHyRaKjs722jdurV9ufr16xsNGzY0JBnNmzc3FixYUOkDZn/88UfDy8vLkGR4enoa4eHhRosWLYwePXpctk9Lvfzyy/Z9e3h4lKt7woQJFa5XOr+yB7lW9QG/FdmzZ4/RokUL+/o+Pj6Gj4+P/XPz5s2N3bt3X1Fdl+KsJ/8bhmGcOHHC6NGjR5m+DQoKsv9sS/9Nnjy5zHqXephrTk6O0alTpzLHir+/v6H/e3PFxx9/bEgyvLy8yq1bleO8tM/XrFlTZnpRUZHRpk0b+7EdGhpq/106cuTIJfsJcAXOmAFVVFxcbH8cwMmTJ+Xt7a3WrVtr8ODBmjZtmvbv368lS5bYBzJX1fjx4/X3v/9dQ4YM0bXXXivDMHTu3Dldc801uu+++7Ru3TpNnDix3HqTJk3SG2+8oY4dO8owDB06dEiHDh1y2SWZZ599Vp9//rliYmJks9nk7e2trl27auHChZW+JzMwMFAbN27UH/7wB4WHh8tmsyk4OFhjx47Vtm3b7I+GqEhUVJS+/vpr3XbbbfL399fx48d16NChSserVWTq1KlavXq1hgwZopCQEOXn5ys4OFiDBw9WYmLiJd+T6Spt27bV999/r0mTJpV5yGyHDh3sN3lce+21NV6XIxo3bqzk5GQtWrRIAwcOVGhoqE6fPi3pws/toYce0qeffqoJEyZUeZsBAQHasGGDXn31VbVt21aGYcjb21vDhw/Xli1bdP3119uXcyar1arVq1fbH1OTk5Nj/11y9HEogDNYDIMRjwAAc/vggw/0+OOPKyYmRmvXrnV3OYDLcMYMAGBqRUVF9vFqF4+1BGojghkAwO0OHz6sRx99VOvXr9eZM2ckXXig7ZYtW3TrrbcqNTVV/v7+evzxx91cKeBaXMoEALjd3r17FRkZaf8cEBCgwsJC+8OJvb29tXTpUg0aNMhdJQI1ot7kiu5xBwCgBnl7e9vfdlBSUmK/maBVq1a69957tWDBAnXr1s3NVQKuxxkzAAAAk/C8/CJXh9JXwrhKSEiIsrKyXLqPuoh+dQ361TXoV9egX12DfnUNZ/Rr6QPCK8LgfwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASRDMAAAATIJgBgAAYBJue8Ds0aNHFR8fb/+ckZGhYcOGKSYmRvHx8crMzFRoaKjGjx8vX19fd5UJAABQY9wWzMLDwzVz5kxJks1m0xNPPKEuXbooISFBN9xwg4YOHaqEhAQlJCRoxIgR7ioTAACgxpjiUmZqaqrCwsIUGhqqlJQUxcTESJJiYmKUkpLi5uoAAABqhinelblhwwb16NFDkpSXl6fAwEBJUkBAgPLy8ipcJzExUYmJiZKkGTNmKCQkxKU1enp6unwfdRH96hr0q2vQr65Bv7oG/eoaru5XtwezkpISfffdd3rggQfKzbNYLLJYLBWuFxsbq9jYWPtnV7+olZfBugb96hr0q2vQr65Bv7oG/eoatf4l5tu3b1erVq0UEBAgSfL391dOTo4kKScnR35+fu4sDwAAoMa4PZhdfBlTkqKjo5WcnCxJSk5OVufOnd1VGgAAQI1yazArLCzUzp079dvf/tY+bejQodq5c6eeeeYZpaamaujQoW6sEAAAoOa4dYyZt7e3/vnPf5aZ1qhRI02aNMlNFQEAzGz6i9N1cv9Jd5fhFMGtgzVx5kR3lwGTcfvgfwAAqurk/pOK2hzl7jKcIl3p7i4BJuT2MWYAAAC4gGAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAk/B0dwEAANeb/uJ0ndx/0t1lVMhqtaq4uLhKyx7ed1hRinJxRYD7EMwAoA44uf+kojZf/YFmX6N97i4BcCkuZQIAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASRDMAAAATMKtj8s4c+aM3n33XR05ckQWi0WjR49WeHi44uPjlZmZqdDQUI0fP16+vr7uLBMAAKBGuDWYzZs3T506ddLzzz+vkpISnTt3TsuXL9cNN9ygoUOHKiEhQQkJCRoxYoQ7ywQAAKgRbruUefbsWf3444/q16+fJMnT01MNGzZUSkqKYmJiJEkxMTFKSUlxV4kAAAA1ym1nzDIyMuTn56e5c+fq0KFDat26tR555BHl5eUpMDBQkhQQEKC8vLwK109MTFRiYqIkacaMGQoJCXFpvZ6eni7fR11Ev7qGO/t14uiJytiT4ZZ9O1vjyMaa/s50++er+Xi1Wq3uLsEpLBaLu0twGqvV6tLj6Wo+Xs3M1f3qtmB2/vx5HThwQKNGjVJkZKTmzZunhISEMstYLJZKfwljY2MVGxtr/5yVleXSekNCQly+j7qIfnUNd/brL7t+qRWv/pGk9OL0Mv14NR+vVX0XpdkZhuHuEpymuLjYpcfT1Xy8mpkz+jU8PLzSeW67lBkcHKzg4GBFRkZKkrp27aoDBw7I399fOTk5kqScnBz5+fm5q0QAAIAa5bZgFhAQoODgYB09elSSlJqaqmbNmik6OlrJycmSpOTkZHXu3NldJQIAANQot96VOWrUKP39739XSUmJGjdurKeeekqGYSg+Pl5JSUn2x2UAAADUBW4NZi1bttSMGTPKTZ80aZIbqgEAAHAvnvwPAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmISnO3c+ZswYeXt7y8PDQ/Xq1dOMGTOUn5+v+Ph4ZWZmKjQ0VOPHj5evr687ywQAAKgRbg1mkhQXFyc/Pz/754SEBN1www0aOnSoEhISlJCQoBEjRrixQgAAgJphukuZKSkpiomJkSTFxMQoJSXFzRUBAADUDLefMZs2bZok6ZZbblFsbKzy8vIUGBgoSQoICFBeXl6F6yUmJioxMVGSNGPGDIWEhLi0Tk9PT5fvoy6qbr9OHD1RGXsynFiRezSObKzp70x32vbcebxarVa37NcVrFZrmX68mr8HasvPxWKxuLsEp/n18eVsV/Pxamau7le3BrPXXntNQUFBysvL09SpUxUeHl5mvsViqfSXMDY2VrGxsfbPWVlZLq01JCTE5fuoi6rbr7/s+kVRm6OcWJF7pBenO/X4cufxWlxc7Jb9ukJxcXGZfryavwdqy8/FMAx3l+A0vz6+nO1qPl7NzBn9+uu8czG3XsoMCgqSJPn7+6tz587au3ev/P39lZOTI0nKyckpM/4MAACgNnNbMCssLFRBQYH9v3fu3KnmzZsrOjpaycnJkqTk5GR17tzZXSUCAADUKLddyszLy9Obb74pSTp//rx69uypTp06qU2bNoqPj1dSUpL9cRkAAAB1gduCWZMmTTRz5sxy0xs1aqRJkya5oSIAAAD3Mt3jMgAAAOoqghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJuO2VTAD+Z8++PXr+d887bXtWq1XFxcVO254jDu87rChFuWXfwNXE2b/3v1aT3wPBrYM1cebEGtlXbUcwA0zAo9BDUZtrR5jZ12ifu0sArgq16fc+XenuLqHW4FImAACASRDMAAAATIJgBgAAYBIEMwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCR4wWwdNf3G6Tu4/6e4yJFX/ydQ8ZR4AUJsQzOqgk/tP1pqnTfOUeQBAbcKlTAAAAJMgmAEAAJiEw8EsPZ0XlQIAALiCw2PM4uLiFB4ern79+ikmJkZ+fn6uqAsAAKDOcfiM2YMPPihJWrhwoZ588knNmjVLO3bskGEYTi8OAACgLnH4jNngwYM1ePBgpaenKykpSZs3b9aWLVsUFBSkvn37qk+fPmrcuLEragUAAKjVrvhxGVFRUYqKitKoUaO0YcMGJSUl6V//+peWLVumDh06qF+/furSpYs8PXkiBwAAQFVUOzV5e3urf//+uummm7Ro0SKtX79eqampSk1NlZ+fn+68804NGjRIHh7cAAoAAHAp1QpmNptN27ZtU1JSkrZv3y6bzaaoqCj1799fVqtVX375pRYtWqTMzEw99thjzqoZAACgVrqiYHbs2DElJSVp3bp1ys3Nla+vr26//Xb1799fERER9uW6deum999/Xxs2bCCYAQAAXIbDwWzSpEnavXu3JKldu3YaOXKkunbtWulYsqioKH399dfVqxIAAKAOcDiYHT16VIMGDVJsbKyaNm162eU7duyouLi4KyoOAACgLnE4mL377rsO3Wnp5+endu3aObobAACAOsfhWyWzs7O1devWSudv3bpVGRkZ1SoKAACgLnL4jNnixYt18uRJRUdHVzj/iy++UEhIiJ5++ulqF2cmE0dP1C+7fnF3GU5xeN9hRSnK3WUAprdn3x49/7vn7Z+tVquKi4vdWNGV4/ceuDo4HMzS09MVGxtb6fyOHTtq9erV1SrKjDL2ZChqc+34UtvXaJ+7SwCuCh6FHvzeA6hRDl/KPHXqlAICAiqd7+/vr9zc3GoVBQAAUBc5HMx8fHx04sSJSucfP35cDRo0qFZRAAAAdZHDwez666/X6tWrKzwrlpubq6SkJEVF1Y5T/wAAADXJ4TFmd999t7777jv98Y9/1KBBg9SyZUtJ0sGDB/XFF1+osLBQd911l7PrBAAAqPUcDmYtW7bUc889p7lz52rRokVl5jVq1Ejjx49XmzZtnFYgAABAXXFF78q8+eab9c4772jHjh06fvy4JKlp06a68cYb5eXl5dQCAQAA6oorCmaS5OXlpS5dulS7AJvNpgkTJigoKEgTJkxQRkaGZs+erdOnT6t169YaO3asQ28aAAAAuFo5PPjf2f773/8qIiLC/nnhwoW644479NZbb6lhw4ZKSkpyY3UAAAA154pORW3YsEFffvmljh07ptOnT5ebb7FY9Mknn1x2OydPntS2bdt0991364svvpBhGEpLS9O4ceMkSX369NHSpUs1YMCAKykTAADgquJwMPv888+1aNEiNWrUSJGRkWrUqNEV73z+/PkaMWKECgoKJEmnT5+Wj4+P6tWrJ0kKCgpSdnZ2hesmJiYqMTFRkjRjxgyFhIRccR1VYbFYXLr9mkRbzKe2tEOiLWZVW9pSW9oh1a62WK1Wl/8dNgtPT0+XttXhYLZq1SpFRkZq0qRJ1Rro/91338nf31+tW7dWWlqaw+vHxsaWeTVUVlbWFddSFYZhuHT7NYm2mE9taYdEW8yqtrSltrRDql1tKS4udvnfYbMICQmpdlvDw8MrnedwMMvNzdXgwYOrfffl7t27tXXrVm3fvl1FRUUqKCjQ/PnzdfbsWZ0/f1716tVTdna2goKCqrUfAACAq4XDwSwsLExnzpyp9o4feOABPfDAA5KktLQ0rVixQs8884z++te/avPmzerRo4fWrl2r6Ojoau8LAADgauDwXZmDBg3SmjVrVFhY6Ip69OCDD+qLL77Q2LFjlZ+fr379+rlkPwAAAGbj8BkzDw8P+fn56dlnn1Xfvn3VuHFjeXiUz7mw9/kAACAASURBVHcxMTFV3mb79u3Vvn17SVKTJk30+uuvO1oWAADAVc/hYDZ37lz7fy9btqzS5RwJZgAAALiCYBYXF+eKOgAAAOo8h4NZu3btXFEHAABAnVetVzIVFxcrOztbJSUlzqoHAACgzrqiYLZ//35NmTJFDz30kEaPHq309HRJUl5env785z9r586dTi0SAACgLnA4mB08eFBxcXE6ceJEuQH+/v7+KioqUnJystMKBAAAqCscDmZLlixRYGCg/vrXv9ofEHuxDh06aO/evU4pDgAAoC5xOJilp6erf//+8vb2rvAFrCEhIcrJyXFKcQAAAHWJw8GsqKhIPj4+lc4vKCioVkEAAAB1lcPBLCwsTPv37690/g8//KBmzZpVqygAAIC6yOFg1qNHD61bt67COy9XrFihHTt2qHfv3k4pDgAAoC5x+AGzgwcPVmpqqqZNm6aIiAhJ0ocffqhTp04pNzdXHTt21IABA5xeKAAAQG3ncDDz9PTUK6+8opUrV+qbb76Rl5eXjh07pqZNm2rQoEEaOHBghS81BwAAwKU5HMwkqV69eho0aJAGDRrk7HoAAADqLE5tAQAAmITDZ8yq+lT/X78VAAAA1E579u3R87973t1lVFtw62BNnDnRrTU4HMzmzp1bpeUIZgAA1A0ehR6K2hzl7jKqLV3p7i7B8WAWFxdXbtr58+d14sQJrVq1SvXr19f999/vlOIAAADqEoeDWbt27SqcfsMNNygmJkYTJ07UgQMH1KFDh2oXBwAAUJc4dfC/1WpVr1699NVXXzlzswAAAHWC0+/K9PT0VHZ2trM3CwAAUOs5NZjl5OTo66+/VuPGjZ25WQAAgDrB4TFmU6ZMqXB6fn6+jh49qpKSEo0ZM6bahQEAANQ1DgezjIyMctMsFot8fX3VpUsX3XbbbbruuuucUhwAAEBd4nAwmzNnjivqAAAAqPN4JRMAAIBJEMwAAABMwuFLmffdd5/DO7FYLPrkk08cXg8AAKAucTiY9e7dWwcOHNCRI0cUHh6uiIgISdLPP/+sY8eOqXnz5mrVqpXTCwUAAKjtHA5mvXr10rfffqsXX3xR0dHRZeZt2bJFb7/9tkaOHKmOHTs6rUgAAIC6wOExZkuWLFFsbGy5UCZJXbp0UWxsrJYsWeKU4gAAAOoSh4PZoUOHFBYWVun8sLAwHT58uFpFAQAA1EUOB7OGDRvq+++/r3T+jh075OPjU62iAAAA6iKHg1nPnj21detWvfPOO/r5559ls9lks9n0888/a+7cufruu+/Us2dPV9QKAABQqzk8+P/+++/X8ePHtXbtWq1du1YeHheync1mkyTdfPPNuv/++51bJQAAQB3gcDCzWq168cUX9f333yslJcX+7szGjRurc+fOuvHGG51eJAAAQF3gcDArdeONNxLCAAAAnKhar2Q6fvy40tPTdfbsWWfVAwAAUGddUTD77rvvNHbsWI0bN05xcXHav3+/JCkvL09jx47V5s2bnVokAABAXeBwMEtLS9Obb74pX19f3XvvvWXm+fv7KywsTBs2bHBagQAAAHWFw8Hss88+U4sWLTRt2jTdeuut5eZHRkbqwIEDTikOAACgLnE4mO3bt089e/a0Pybj14KDg5Wbm1vtwgAAAOoah4OZYRiyWq2Vzj99+rQ8Pa/4Zk8AAIA6y+EEFRERoR9//LHCy5jShRsDWrRocdntFBUVKS4uTiUlJTp//ry6du2qYcOGKSMjQ7Nnz9bp06fVunVrjR07lqAHAADqBIfPmPXr10/ffvutkpKSZBiGffq5c+f0z3/+Uz/99JNiY2Mvux2r1aq4uDjNnDlTf/nLX7Rjxw799NNPWrhwoe644w699dZbatiwoZKSkhwtEQAA4Krk8KmoAQMGKD09Xf/4xz/00UcfSZL+9re/KT8/XzabTX369FGvXr0uux2LxSJvb29J0vnz53X+/HlZLBalpaVp3LhxkqQ+ffpo6dKlGjBggKNlAgAAXHWu6BrhM888o65du2rdunU6evSoDMNQZGSkevfura5du1Z5OzabTS+99JKOHz+uW2+9VU2aNJGPj4/q1asnSQoKClJ2dnaF6yYmJioxMVGSNGPGDIWEhFxJU6rMYrG4dPs1ibaYT21ph0RbzKq2tKW2tEOiLWZktVovmyc8PT1dmjkcCmZFRUXatGmTwsPD1aVLF3Xp0qVaO/fw8NDMmTN15swZvfnmmzp69GiV142NjS1zyTQrK6tatVzOxZdtr3a0xXxqSzsk2mJWtaUttaUdEm0xo+Li4svmiZCQkGpnjvDw8ErnOTTGzNPTU//4xz+c/pyyhg0bqn379vrpp5909uxZnT9/XpKUnZ2toKAgp+4LAADArBwKZh4eHgoODlZBQUG1d3zq1CmdOXNG0oUzcTt37lRERITat29vf6XT2rVrFR0dXe19AQAAXA0cHmMWExOjdevWaeDAgZd8ntnl5OTkaM6cObLZbDIMQ926ddPNN9+sZs2aafbs2frkk0/UqlUr9evX74r3AQAAcDVxOJhdd9112rJli/74xz9qwIABatq0qby8vMot165du0tup0WLFvrLX/5SbnqTJk30+uuvO1oWAADAVc/hYDZ16lT7f8+fP7/S5ZYsWXJFBQEAANRVVQpme/fuVVhYmHx9fTV69GhX1wQAAFAnVSmYvfzyyxo7dqx69uypPn36qLCwUP/4xz/0u9/9Ts2aNXN1jQAAAHWCw69kki4852Pjxo3Kzc11dj0AAAB11hUFMwAAADgfwQwAAMAkCGYAAAAmUeXHZWzbts0+puzcuXOSpE2bNungwYMVLj9o0KDqVwcAAFCHVDmYbdiwQRs2bCgzLTExsdLlCWYAAACOqVIwi4uLc3UdAAAAdV6VgtnlXq8EAACA6mPwPwAAgEkQzAAAAEyCYAYAAGASBDMAAACTIJgBAACYBMEMAADAJAhmAAAAJkEwAwAAMAmCGQAAgEkQzAAAAEyCYAYAAGASBDMAAACTIJgBAACYBMEMAADAJAhmAAAAJkEwAwAAMAmCGQAAgEkQzAAAAEyCYAYAAGASBDMAAACTIJgBAACYBMEMAADAJAhmAAAAJkEwAwAAMAmCGQAAgEkQzAAAAEyCYAYAAGASBDMAAACTIJgBAACYBMEMAADAJAhmAAAAJkEwAwAAMAmCGQAAgEl4umvHWVlZmjNnjnJzc2WxWBQbG6uBAwcqPz9f8fHxyszMVGhoqMaPHy9fX193lQkAAFBj3BbM6tWrp5EjR6p169YqKCjQhAkT1LFjR61du1Y33HCDhg4dqoSEBCUkJGjEiBHuKhMAAKDGuO1SZmBgoFq3bi1JatCggSIiIpSdna2UlBTFxMRIkmJiYpSSkuKuEgEAAGqU286YXSwjI0MHDhxQ27ZtlZeXp8DAQElSQECA8vLyKlwnMTFRiYmJkqQZM2YoJCTEpTVaLBaXbr8m0RbzqS3tkGiLWdWWttSWdki0xYysVutl84Snp6dLM4fbg1lhYaFmzZqlRx55RD4+PmXmWSyWSn/YsbGxio2NtX/OyspyaZ2GYbh0+zWJtphPbWmHRFvMqra0pba0Q6ItZlRcXHzZPBESElLtzBEeHl7pPLfelVlSUqJZs2apV69e+u1vfytJ8vf3V05OjiQpJydHfn5+7iwRAACgxrgtmBmGoXfffVcREREaNGiQfXp0dLSSk5MlScnJyercubO7SgQAAKhRbruUuXv3bq1bt07NmzfXiy++KEkaPny4hg4dqvj4eCUlJdkflwEAAFAXuC2YRUVF6dNPP61w3qRJk2q4GgAAAPfjyf8AAAAmQTADAAAwCYIZAACASRDMAAAATIJgBgAAYBIEMwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASRDMAAAATIJgBgAAYBIEMwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASRDMAAAATIJgBgAAYBIEMwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASRDMAAAATIJgBgAAYBIEMwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASRDMAAAATIJgBgAAYBIEMwAAAJMgmAEAAJgEwQwAAMAkCGYAAAAmQTADAAAwCYIZAACASXi6a8dz587Vtm3b5O/vr1mzZkmS8vPzFR8fr8zMTIWGhmr8+PHy9fV1V4kAAAA1ym1nzPr06aOJEyeWmZaQkKAbbrhBf//733XDDTcoISHBTdUBAADUPLcFs3bt2pU7G5aSkqKYmBhJUkxMjFJSUtxRGgAAgFu47VJmRfLy8hQYGChJCggIUF5eXqXLJiYmKjExUZI0Y8YMhYSEuLQ2i8Xi0u3XJNpiPrWlHRJtMava0pba0g6JtpiR1Wq9bJ7w9PR0aeYwVTC7mMViueQPOjY2VrGxsfbPWVlZLq3HMAyXbr8m0RbzqS3tkGiLWdWWttSWdki0xYyKi4svmydCQkKqnTnCw8MrnWequzL9/f2Vk5MjScrJyZGfn5+bKwIAAKg5pgpm0dHRSk5OliQlJyerc+fObq4IAACg5rjtUubs2bO1a9cunT59Wk8++aSGDRumoUOHKj4+XklJSfbHZQAAANQVbgtmzz77bIXTJ02aVMOVAAAAmIOpLmUCAADUZQQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQIZgAAACZBMAMAADAJghkAAIBJEMwAAABMgmAGAABgEgQzAAAAkyCYAQAAmATBDAAAwCQ83V1ARXbs2KF58+bJZrOpf//+Gjp0qLtLAgAAcDnTnTGz2Wz64IMPNHHiRMXHx2vDhg36+eef3V0WAACAy5kumO3du1dhYWFq0qSJPD091b17d6WkpLi7LAAAAJezGIZhuLuIi23evFk7duzQk08+KUlat26d9uzZo8cee6zMcomJiUpMTJQkzZgxo8brBAAAcDbTnTGrqtjYWM2YMaPGQtmECRNqZD91Df3qGvSra9CvrkG/ugb96hqu7lfTBbOgoCCdPHnS/vnkyZMKCgpyY0UAAAA1w3TBrE2bNjp27JgyMjJUUlKijRs3Kjo62t1lAQAAuFy9yZMnT3Z3ERfz8PBQWFiY3nrrLX355Zfq1auXunbt6u6yJEmtW7d2dwm1Ev3qGvSra9CvrkG/ugb96hqu7FfTDf4HAACoq0x3KRMAAKCuIpgBAACYhClfyeQOc+fO1bZt2+Tv769Zs2aVmbdixQotWLBA77//vvz8/GQYhubNm6ft27erfv36euqpp7iOX4mK+vXTTz/V6tWr5efnJ0kaPny4brrpJknS8uXLlZSUJA8PDz366KPq1KmT22o3s8qO15UrV2rVqlXy8PDQTTfdpBEjRkiiX6uqon6Nj4/X0aNHJUlnz56Vj4+PZs6cKYl+raqK+vXgwYN67733VFRUpHr16unxxx9X27Zt+X51wKX6tbCwUKGhoXrmmWfk4+MjieO1KrKysjRnzhzl5ubKYrEoNjZWAwcOVH5+vuLj45WZmanQ0FCNHz9evr6+rjleDRiGYRhpaWnGvn37jOeee67M9MzMTGPq1KnG6NGjjby8PMMwDOO7774zpk2bZthsNmP37t3Gn/70J3eUfFWoqF+XLFli/Pvf/y637JEjR4wXXnjBKCoqMk6cOGE8/fTTxvnz52uy3KtGRf2amppq/PnPfzaKiooMwzCM3NxcwzDoV0dU9j1Q6sMPPzSWLl1qGAb96oiK+vW1114ztm3bZhjGhe/UuLg4+3/z/Vo1FfXrhAkTjLS0NMMwDGP16tXG4sWLDcPgeK2q7OxsY9++fYZhGMbZs2eNZ555xjhy5IixYMECY/ny5YZhGMby5cuNBQsWGIbhmuOVS5n/p127dvL19S03/cMPP9SDDz4oi8Vin7Z161b17t1bFotF1157rc6cOaOcnJyaLPeqUVm/ViQlJUXdu3eX1WpV48aNFRYWpr1797q4wqtTRf361VdfaciQIbJarZIkf39/SfSrIy51vBqGoU2bNqlHjx6S6FdHVNSvFotFBQUFki6ciQwMDJTE96sjKurXo0eP6vrrr5ckdezYUd9++60kjteqCgwMtJ/xatCggSIiIpSdna2UlBTFxMRIkmJiYuyvinTF8Uowu4SUlBQFBQWpZcuWZaZnZ2crJCTE/jk4OFjZ2dk1XN3VbdWqVXrhhRc0d+5c5efnS7rQr8HBwfZlgoKC6FcHHDt2TOnp6Zo4caLi4uLsX7r0q3P8+OOP8vf3V9OmTSXRr9X18MMPa8GCBRo9erQWLFigBx54QBLfr9V1zTXX2EPD5s2b7Q9s53h1XEZGhg4cOKC2bdsqLy/P/j8PAQEBysvLk+Sa45VgVolz585p+fLluu+++9xdSq0zYMAAvfXWW/rLX/6iwMBAffTRR+4uqVaw2WzKz8/XtGnTNHLkSMXHx8vgaThOs2HDBvvZMlTfV199pYcffljvvPOOHn74Yb377rvuLqlWGD16tL766iu99NJLKigokKcnQ8mvRGFhoWbNmqVHHnnEPkavlMViKXMVzdkIZpU4ceKEMjIy9OKLL2rMmDE6efKkXnrpJeXm5iooKEhZWVn2ZXltlGMCAgLk4eEhDw8P9e/fX/v27ZNU/nVc2dnZ9KsDgoKC1KVLF1ksFrVt21YeHh46ffo0/eoE58+f15YtW9S9e3f7NPq1epKTk/Xb3/5WktStWzf7GV6+X6snIiJCr7zyit544w316NFDTZo0kcTx6oiSkhLNmjVLvXr1sh+j/v7+9kuUOTk59pvXXHG8Eswq0bx5c73//vuaM2eO5syZo+DgYL3xxhsKCAhQdHS01q1bJ8Mw9NNPP8nHx8d+ihOXd/H19y1btuiaa66RJEVHR2vjxo0qLi5WRkaGjh07prZt27qrzKtO586dlZaWJunCOJOSkhI1atSIfnWC1NRUhYeHl7kURL9WT1BQkHbt2iVJ+uGHHxQWFiZJfL9WU+klNpvNpmXLlumWW26RxPFaVYZh6N1331VERIQGDRpknx4dHa3k5GRJF/6nonPnzvbpzj5eefL//5k9e7Z27dql06dPy9/fX8OGDVO/fv3s88eMGaPXX3/d/riMDz74QN9//728vLz01FNPqU2bNm6s3rwq6te0tDQdPHhQFotFoaGh+sMf/mA/kJctW6Y1a9bIw8NDjzzyiH7zm9+4uQXmVFG/9u7dW3PnztWhQ4fk6empkSNHqkOHDpLo16qq7Htgzpw5ioyM1IABA8osT79WTUX9Gh4ernnz5slms8lqterxxx9X69at+X51QEX9WlhYqFWrVkmSunTpogceeMB+2Y3j9fLS09M1adIkNW/e3N5vw4cPV2RkpOLj45WVlVXucRnOPl4JZgAAACbBpUwAAACTIJgBAACYBMEMAADAJAhmAAAAJkEwAwAAMAmCGYAaNWfOHA0bNuyK109LS9OwYcO0du1a5xVVgaKiIo0ZM0aLFy8uM33YsGGaM2eOS/ctSZMnT9aYMWNcvp+KGIahl156SXPnznXL/oG6jGAGwK409Hz++eeVLjNs2DDNmDGjBquqnv/85z9XFOK++OILnTlzRnfeeafzizI5i8Wie++9V8nJyTp48KC7ywHqFIIZgBr1xBNPaOHChTW2v//+978OB7OioiKtWLFCffr0ka+vb5l5Cxcu1BNPPOHECs0pOjpajRs31rJly9xdClCnEMwA1ChPT095eXm5u4xL+uabb3TmzBnFxMSUm+fl5VVnXgzdq1cvpaSkKDc3192lAHVG3fh2AeBy+/bt07Jly5Senq6CggKFhoYqJiZGQ4YMUb169ezLzZkzR8nJyfr000/LrL9r1y4tWrRIBw8elI+Pj7p3767Y2Fg9//zzuueeeyocl7ZmzRqtWLFCx48fV0BAgG699VYNGTLEPr90nczMzDLrv/3222rcuHGlbdm0aZMCAgLUqlWrcvOGDRummJiYMuO/SqfdcsstWrRokfbv3y+r1aouXbrokUcekbe3d5lt5ObmatmyZdq2bZuys7Pl4+OjFi1aaMiQIerYsWOZZbOzs/XRRx/p+++/V3Fxsa6//no9+uijCg8PL7NccXGxVqxYoW+++UYnTpyQ1WpVVFSU7rvvvjLtsNlsWrlypdasWaOMjAxZLBYFBAQoKipKv//978uEzk6dOumzzz7Tli1byr2OCoBrEMwAlFNUVKRTp05Veflt27bpzTffVFhYmAYNGiRfX1/99NNPWrJkiQ4ePKjnnnvukuunp6dr6tSpatiwoYYOHaqGDRtq06ZNlxxk//XXXys3N1f9+vVTw4YNtX79ei1atEjBwcHq2bOnJOnpp5/Whx9+KD8/P9111132df38/Crdrs1m0+7du+3vGa2qgwcPasaMGerTp4969uyptLQ0JSUlyWKxlLn0mZGRoVdffVV5eXnq3bu32rRpo3Pnzumnn37Szp07ywSzwsJCxcXFKTIyUsOHD1dGRob++9//aubMmZo1a5Y8PC5c9CgpKdH06dO1e/du9e7dW7fddpvOnj2r1atX69VXX9WUKVPs7+9btmyZPv30U91888265ZZb5OHhoYyMDG3dulUlJSVlglnr1q1ltVq1a9cughlQQwhmAMr59NNPy53RqkxRUZHeeecdRUZGatKkSfazY7fccotatGihjz76SGlpaWrfvn2l2/jwww9lsVg0depUNWnSRJI0YMAATZkypdJ1srKyFB8fLx8fH0lS37599dRTT2nlypX2YNa7d28tWbJE/v7+6t27d5Xak5WVpcLCQnsdVXX48GFNnTpVkZGRki60v6CgQGvXrtXDDz9sP2v2wQcfKCcnRxMnTlSnTp3KbMNms5X5fPr0aQ0ePLjMWUA/Pz8tXLhQO3futK//5ZdfKi0trdw2BwwYoOeff14LFizQ5MmTJUkpKSmKiIjQSy+9VGZfDz74YLk2eXp6KigoSEeOHHGoLwBcOYIZgHJiY2PVtWvXCudNnTq1zOedO3cqLy9PDzzwgM6cOVNm3k033WS/DFdZMMvNzdW+ffvUrVu3MmHI09NTt99+u3bv3l3hen369LGHMkmqX7++IiMjtWfPniq1sTKlZwp/Pej/cq699lp7KCvVoUMHbd++XRkZGWrevLny8/O1Y8cOderUqVwok2Q/A1bKYrHo9ttvL7dNSTp+/Lh92vr16xUREaHWrVuXO9PZsWNHJScnq6ioSF5eXvLx8dHx48eVnp6uqKioy7arUaNGyszMvOxyAJyDYAagnLCwsHJjnSrzyy+/SJLeeeedSpfJy8urdF5GRoYklRszVdm0UhWd0WrUqJFOnz5d6TqOMAzDoeUrGrPWqFEjSVJ+fr6kC2HKMAy1bNmyStsMCgoqd6NEaWC8uJ2//PKLioqK9Pjjj1e6rVOnTikkJETDhw/XzJkzNWnSJAUGBqp9+/a66aab1LVr1wpvanC0HwBUD8EMQLWU/uEeMWJEpYEjKCjI6fv99dklZykdf1YapqrqUvVcabip6jYNw1Dz5s310EMPVbp8abuuvfZavfXWW9qxY4fS0tKUlpamb775Rv/617/02muvlTtTmJ+ff8kxeQCci2AGoFqaNm0qSfL29q7yWbaLlZ5pOnr0aLl5FU1ztZCQEDVo0KDMpUJnCQsLk8Vi0aFDh5y63aZNm+rUqVPq0KFDlQKrt7e3unbtar9cvWrVKn3wwQdKSkrS4MGD7csVFxfr5MmT6tKli1PrBVA5nmMGoFpuvPFG+fv7KyEhocKzTEVFRSooKKh0/YCAALVp00Zbt27ViRMn7NNLSkq0cuXKatfn7e3t0NkvDw8PXX/99dUeq1YRX19fderUSdu3b9fOnTvLzb/SM2u9e/dWbm6uvvjiiwrnX/wcsoruti19nMav++nAgQMqKSlRu3btrqguAI7jjBmAavH29taYMWM0c+ZMjRs3Tn379lVYWJjOnj2rX375RVu2bNELL7xwybsyR44cqddee02vvPKKbr31Vvn4+GjTpk0qKSmRdGEQ/JWKjIzUmjVr9Mknn6hZs2ayWCy6+eabyz1b7GJdu3bVtm3btHfvXrVt2/aK912Rxx57TK+88opef/11xcTEqHXr1ioqKtKePXsUGhqqESNGOLzNgQMHKjU1VQsXLrTfAevj46OsrCylpqbKy8tLcXFxkqTx48crMjJSkZGRCgwMVG5urhITE+Xp6anu3buX2e727dtVr149zpgBNYhgBqDaOnXqpNdff10JCQlav369Tp06JV9fXzVp0kR33HGHWrRoccn127Vrp5dfflmLFy/W8uXL7Q+Y7dmzp15++eVqvSlg+PDhys/P16pVq3T27FkZhqG33377ksGse/fu+uijj7Ru3TqnB7PGjRtrxowZ+uyzz7R9+3YlJyfL19dXLVq0UGxs7BVt09PTUxMmTNCqVau0fv16LV26VJIUGBiotm3blnmDwZ133qnt27dr5cqVOnv2rPz9/RUZGamhQ4eWGyO4fv16de7cWQEBAVfcXgCOsRjccgPApDZv3qy//vWvGjdunHr06FGj+05ISNDy5cs1Z84chx+dURukpKTozTff1BtvvFHlu0gBVB9jzAC4nWEYKioqKjOtpKRE//nPf1SvXr1LXgZ1lYEDSvx6jgAAAKVJREFUB8rX11eff/55je/b3QzD0NKlSxUTE0MoA2oYZ8wAuF1RUZHGjBmjnj17Kjw8XKdPn9amTZt06NAhDRkypMKn0gNAbcQYMwBu5+npqd/85jfaunWrcnJyZBiGwsPD9dhjj+nWW291d3kAUGM4YwYAAGASjDEDAAAwCYIZAACASRDMAAAATIJgBgAA8P/brWMBAAAAgEH+1tPYURRNiBkAwETvkqvXdS7pKwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# histogram of the height - males and females\n",
        "bmi[bmi['Gender'] == 'Male'].Height.plot(kind='hist', color='blue', edgecolor='black', alpha=0.5, figsize=(10, 7))\n",
        "bmi[bmi['Gender'] == 'Female'].Height.plot(kind='hist', color='magenta', edgecolor='black', alpha=0.5, figsize=(10, 7))\n",
        "plt.legend(labels=['Males', 'Females'])\n",
        "plt.title('Distribution of Height', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Frequency', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        },
        "id": "C1v9M4CGhayF",
        "outputId": "4c9d6b4c-dddb-472f-d785-942adffb5538"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# histogram of the weight - males and females\n",
        "bmi[bmi['Gender'] == 'Male'].Weight.plot(kind='hist', color='blue', edgecolor='black', alpha=0.5, figsize=(10, 7))\n",
        "bmi[bmi['Gender'] == 'Female'].Weight.plot(kind='hist', color='magenta', edgecolor='black', alpha=0.5, figsize=(10, 7))\n",
        "plt.legend(labels=['Males', 'Females'])\n",
        "plt.title('Distribution of Weight', size=24)\n",
        "plt.xlabel('Weight (pounds)', size=18)\n",
        "plt.ylabel('Frequency', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        },
        "id": "akpjSNy1hzus",
        "outputId": "dedffdb6-8baa-46d2-9dd2-fd68e7eabde6"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Descriptive statistics male\n",
        "statistics_male = bmi[bmi['Gender'] == 'Male'].describe()\n",
        "statistics_male.rename(columns=lambda x: x + '_male', inplace=True)\n",
        "# Descriptive statistics female\n",
        "statistics_female = bmi[bmi['Gender'] == 'Female'].describe()\n",
        "statistics_female.rename(columns=lambda x: x + '_female', inplace=True)\n",
        "# Dataframe that contains statistics for both male and female\n",
        "statistics = pd.concat([statistics_male, statistics_female], axis=1)\n",
        "statistics"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "ZT_SKr5kh-RL",
        "outputId": "8631c951-33a4-43b6-fa6c-7af3f7bbc1e6"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Height_male  Weight_male  Index_male  Height_female  Weight_female  \\\n",
              "count   245.000000   245.000000  245.000000     255.000000     255.000000   \n",
              "mean    169.648980   106.314286    3.787755     170.227451     105.698039   \n",
              "std      17.065665    31.832734    1.386355      15.711825      32.962025   \n",
              "min     140.000000    50.000000    0.000000     140.000000      50.000000   \n",
              "25%     154.000000    80.000000    3.000000     157.000000      79.000000   \n",
              "50%     171.000000   105.000000    4.000000     170.000000     106.000000   \n",
              "75%     183.000000   137.000000    5.000000     184.000000     135.000000   \n",
              "max     199.000000   160.000000    5.000000     199.000000     160.000000   \n",
              "\n",
              "       Index_female  \n",
              "count    255.000000  \n",
              "mean       3.709804  \n",
              "std        1.325886  \n",
              "min        0.000000  \n",
              "25%        3.000000  \n",
              "50%        4.000000  \n",
              "75%        5.000000  \n",
              "max        5.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f2992d36-7456-4f95-a089-51c5833ccceb\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Height_male</th>\n",
              "      <th>Weight_male</th>\n",
              "      <th>Index_male</th>\n",
              "      <th>Height_female</th>\n",
              "      <th>Weight_female</th>\n",
              "      <th>Index_female</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>245.000000</td>\n",
              "      <td>245.000000</td>\n",
              "      <td>245.000000</td>\n",
              "      <td>255.000000</td>\n",
              "      <td>255.000000</td>\n",
              "      <td>255.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>169.648980</td>\n",
              "      <td>106.314286</td>\n",
              "      <td>3.787755</td>\n",
              "      <td>170.227451</td>\n",
              "      <td>105.698039</td>\n",
              "      <td>3.709804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>17.065665</td>\n",
              "      <td>31.832734</td>\n",
              "      <td>1.386355</td>\n",
              "      <td>15.711825</td>\n",
              "      <td>32.962025</td>\n",
              "      <td>1.325886</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>140.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>154.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>157.000000</td>\n",
              "      <td>79.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>171.000000</td>\n",
              "      <td>105.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>170.000000</td>\n",
              "      <td>106.000000</td>\n",
              "      <td>4.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>183.000000</td>\n",
              "      <td>137.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>184.000000</td>\n",
              "      <td>135.000000</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>199.000000</td>\n",
              "      <td>160.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>199.000000</td>\n",
              "      <td>160.000000</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f2992d36-7456-4f95-a089-51c5833ccceb')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f2992d36-7456-4f95-a089-51c5833ccceb button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f2992d36-7456-4f95-a089-51c5833ccceb');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Scatter plot of Height and Weight\n",
        "ax1 = bmi[bmi['Gender'] == 'Male'].plot(kind='scatter', x='Height', y='Weight', color='blue', alpha=0.5, figsize=(10, 7))\n",
        "bmi[bmi['Gender'] == 'Female'].plot(kind='scatter', x='Height', y='Weight', color='magenta', alpha=0.5, figsize=(10 ,7), ax=ax1)\n",
        "plt.legend(labels=['Males', 'Females'])\n",
        "plt.title('Relationship between Height and Weight', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        },
        "id": "1JxcBdDSiVml",
        "outputId": "1f0cc6a7-b85c-44bc-ed22-ec974d65a51f"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Scatter plot of 50 females\n",
        "sample_females = bmi[bmi['Gender'] == 'Female'].sample(50)\n",
        "sample_females.plot(kind='scatter', x='Height', y='Weight', color='magenta', alpha=0.5, figsize=(10, 7))\n",
        "plt.legend(labels=['Females'])\n",
        "plt.title('Relationship between Height and Weight (sample of 500 females)', size=20)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 471
        },
        "id": "RNj46OjYiv0s",
        "outputId": "4f91b008-c1cb-455a-a78f-e379ce36d942"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# best fit polynomials\n",
        "bmi_males = bmi[bmi['Gender'] == 'Male']\n",
        "bmi_females = bmi[bmi['Gender'] == 'Female']\n",
        "# polynomial - males\n",
        "male_fit = np.polyfit(bmi_males.Height, bmi_males.Weight, 1)\n",
        "# array([   5.96177381, -224.49884071])\n",
        "# polynomial - females\n",
        "female_fit = np.polyfit(bmi_females.Height, bmi_females.Weight, 1)\n",
        "# array([   5.99404661, -246.01326575])"
      ],
      "metadata": {
        "id": "agV002OJi_T2"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plots and regression lines\n",
        "# males and females dataframes\n",
        "bmi_males = bmi[bmi['Gender'] == 'Male']\n",
        "bmi_females = bmi[bmi['Gender'] == 'Female']\n",
        "# Scatter plots.\n",
        "ax1 = bmi_males.plot(kind='scatter', x='Height', y='Weight', color='blue', alpha=0.5, figsize=(10, 7))\n",
        "bmi_females.plot(kind='scatter', x='Height', y='Weight', color='magenta', alpha=0.5, figsize=(10, 7), ax=ax1)\n",
        "# regression lines\n",
        "plt.plot(bmi_males.Height, male_fit[0] * bmi_males.Height + male_fit[1], color='darkblue', linewidth=2)\n",
        "plt.plot(bmi_females.Height, female_fit[0] * bmi_females.Height + female_fit[1], color='deeppink', linewidth=2)\n",
        "# regression equations\n",
        "plt.text(65, 230, 'y={:.2f}+{:.2f}*x'.format(male_fit[1], male_fit[0]), color='darkblue', size=12)\n",
        "plt.text(70, 130, 'y={:.2f}+{:.2f}*x'.format(female_fit[1], female_fit[0]), color='deeppink', size=12)\n",
        "# legend, title and labels.\n",
        "plt.legend(labels=['Males Regresion Line', 'Females Regresion Line', 'Males', 'Females'])\n",
        "plt.title('Relationship between Height and Weight', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "id": "y0P7h8fBjrpS",
        "outputId": "ef2676fe-f1d7-4ce2-80a5-f91ac1859261"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "# regression plot using seaborn\n",
        "fig = plt.figure(figsize=(10, 7))\n",
        "sns.regplot(x=bmi_males.Height, y=bmi_males.Weight, color='blue', marker='+')\n",
        "sns.regplot(x=bmi_females.Height, y=bmi_females.Weight, color='magenta', marker='+')\n",
        "# Legend, title and labels.\n",
        "plt.legend(labels=['Males', 'Females'])\n",
        "plt.title('Relationship between Height and Weight', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        },
        "id": "wkg4I7VykigZ",
        "outputId": "ca919a2f-61f6-4ee3-fbe3-5ccbcf03c9af"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib.blocking_input import BlockingMouseInput\n",
        "# 300 random samples\n",
        "bmi_males_sample = bmi[bmi['Gender'] == 'Male'].sample(30)\n",
        "bmi_females_sample = bmi[bmi['Gender'] == 'Female'].sample(30)\n",
        "# regression plot using seaborn\n",
        "fig = plt.figure(figsize=(10, 7))\n",
        "sns.regplot(x=bmi_males_sample.Height, y=bmi_males_sample.Weight, color='blue', marker='+')\n",
        "sns.regplot(x=bmi_females_sample.Height, y=bmi_females_sample.Weight, color='magenta', marker='+')\n",
        "# legend, title, and labels.\n",
        "plt.legend(labels=['Males', 'Females'])\n",
        "plt.title('Relationship between Height and Weight', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        },
        "id": "uAUtja6Hk8oV",
        "outputId": "4befa3e1-7c34-4ed9-92b8-9fa9b2cefae8"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "bmi_males = bmi[bmi['Gender'] == 'Male']\n",
        "# create linear regression object\n",
        "lr_males = LinearRegression()\n",
        "# fit linear regression\n",
        "lr_males.fit(bmi_males[['Height']], bmi_males['Weight'])\n",
        "# get the slope and intercept of the line best fit\n",
        "print(lr_males.intercept_)\n",
        "# -224.49884070545772\n",
        "print(lr_males.coef_)\n",
        "# 5.96177381\n",
        "bmi_females = bmi[bmi['Gender'] == 'Female']\n",
        "# create linear regression object\n",
        "lr_females = LinearRegression()\n",
        "# fit linear regression\n",
        "lr_females.fit(bmi_females[['Height']], bmi_females['Weight'])\n",
        "# get the slope and intercept of the line best fit\n",
        "print(lr_females.intercept_)\n",
        "# -246.01326574667277\n",
        "print(lr_females.coef_)\n",
        "# 5.99404661"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m1ZFaDzellp6",
        "outputId": "9c17f5e6-5d82-4043-b2ae-66898d31cb9f"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "114.58397655987221\n",
            "[-0.04874589]\n",
            "95.85267170072629\n",
            "[0.05783654]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bmi_females = bmi[bmi['Gender'] == 'Female']\n",
        "# fit the model using numpy\n",
        "female_fit = np.polyfit(bmi_females.Height, bmi_females.Weight, 1)\n",
        "# predictions using numpy\n",
        "print(np.polyval(female_fit, [60]))\n",
        "# [113.62953114]\n",
        "# fit the model using scikit learn\n",
        "lr_females = LinearRegression()\n",
        "lr_females.fit(bmi_females[['Height']], bmi_females['Weight'])\n",
        "# predictions using scikit learn\n",
        "print(lr_females.predict([[60]]))\n",
        "# [113.62953114]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zURC6FWOmccC",
        "outputId": "b6497a89-a486-4615-a11a-9813a757b614"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[99.32286436]\n",
            "[99.32286436]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but LinearRegression was fitted with feature names\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Pearson correlation coefficient\n",
        "# dataframe containing only females\n",
        "bmi_females = bmi[bmi['Gender'] == 'Female']\n",
        "# correlation coefficients \n",
        "bmi_females.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "Wpwqn2pQm3wN",
        "outputId": "776b4038-c8df-4050-fdaa-7d5fe724bf0e"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          Height    Weight     Index\n",
              "Height  1.000000  0.027569 -0.362132\n",
              "Weight  0.027569  1.000000  0.819280\n",
              "Index  -0.362132  0.819280  1.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4b21f26f-7c04-4848-82bd-87ddea37fb72\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Height</th>\n",
              "      <th>Weight</th>\n",
              "      <th>Index</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Height</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.027569</td>\n",
              "      <td>-0.362132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Weight</th>\n",
              "      <td>0.027569</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.819280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Index</th>\n",
              "      <td>-0.362132</td>\n",
              "      <td>0.819280</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4b21f26f-7c04-4848-82bd-87ddea37fb72')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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            ]
          },
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# dataframe containing only males\n",
        "bmi_males = bmi[bmi['Gender'] == 'Male']\n",
        "\n",
        "# correlation coefficients \n",
        "bmi_males.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
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        "outputId": "2769ed6f-48aa-41dc-cf2b-2d25d4004233"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          Height    Weight     Index\n",
              "Height  1.000000 -0.026133 -0.476934\n",
              "Weight -0.026133  1.000000  0.790888\n",
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              "      <th>Index</th>\n",
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              "      <td>-0.476934</td>\n",
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              "    <tr>\n",
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              "      <td>-0.026133</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.790888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Index</th>\n",
              "      <td>-0.476934</td>\n",
              "      <td>0.790888</td>\n",
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              "\n",
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              "\n",
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              "    }\n",
              "  </style>\n",
              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-f3964247-82a4-44f6-b671-1d5a4cce16f3 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f3964247-82a4-44f6-b671-1d5a4cce16f3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Correlation from Scipy\n",
        "from scipy import stats\n",
        "# dataframe containing only females\n",
        "bmi_females = bmi[bmi['Gender'] == 'Female']\n",
        "# pearson correlation coefficient and p-value\n",
        "pearson_coef, p_value = stats.pearsonr(bmi_females.Height, bmi_females.Weight)\n",
        "print(pearson_coef)\n",
        "# 0.849608591418601\n",
        "# dataframe containing only males\n",
        "bmi_males = bmi[bmi['Gender'] == 'Male']\n",
        "# pearson correlation coefficient and p-value\n",
        "pearson_coef, p_value = stats.pearsonr(bmi_males.Height, bmi_males.Weight)\n",
        "print(pearson_coef)\n",
        "# 0.8629788486163176"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wqNgfBPinW1t",
        "outputId": "aa798006-82a6-4493-ab0b-7ee4148c3f3e"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.027568624092019232\n",
            "-0.026132882097317366\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Residual plots\n",
        "# dataframe containing only females\n",
        "bmi_females = bmi[bmi['Gender'] == 'Female'].sample(50)\n",
        "# residual plot 500 females\n",
        "fig = plt.figure(figsize = (10, 7))\n",
        "sns.residplot(bmi_females.Height, bmi_females.Weight, color='magenta')\n",
        "# title and labels\n",
        "plt.title('Residual plot 50 females', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "uL0ISmwyn79I",
        "outputId": "0dd9510e-46b4-45a5-d00c-cd0c311e659d"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# dataframe containing only males\n",
        "bmi_males = bmi[bmi['Gender'] == 'Male'].sample(50)\n",
        "# residual plot 500 males\n",
        "fig = plt.figure(figsize=(10, 7))\n",
        "sns.residplot(bmi_males.Height, bmi_males.Weight, color='blue')\n",
        "# title and labels\n",
        "plt.title('Residual plot 50 males', size=24)\n",
        "plt.xlabel('Height (inches)', size=18)\n",
        "plt.ylabel('Weight (pounds)', size=18);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "HkRwoeSwoWhU",
        "outputId": "6bbcc428-e8de-4477-cf76-2ca75b7b650c"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}