85 lines (84 with data), 1.9 kB

{
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00b82428",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "    cardio_data = pd.read_csv('cardio_train.csv', sep=';')\n",
    "    print(cardio_data.head())\n",
    "    smokers = cardio_data[cardio_data['smoke'] == 1]\n",
    "    average_age = smokers['age'].mean()\n",
    "    mode_age = smokers['age'].mode()[0]\n",
    "    print('The average age of smokers ', average_age / 365)\n",
    "    print('The most repeated age of smokers ', mode_age / 365)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc7922cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardio_data_2 = pd.read_csv('heart_data.csv')\n",
    "print(cardio_data_2.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bb3ff25",
   "metadata": {},
   "outputs": [],
   "source": [
    "smokers = cardio_data_2[cardio_data_2['Smoking'] == 1]\n",
    "smokers['Heart']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e85f38d",
   "metadata": {},
   "outputs": [],
   "source": [
    "nonsmokers = cardio_data_2[cardio_data_2]['Smoking'==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f1517c9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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