Untitled.ipynb

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   "source": [
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "a = np.random.randint(100, size=(4,4))\n",
    "a, plt.boxplot(a)"
   ]
  },
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   "source": [
    "plt.plot(a)"
   ]
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   "execution_count": 1,
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   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'sns' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mNameError\u001B[0m                                 Traceback (most recent call last)",
      "Input \u001B[0;32mIn [1]\u001B[0m, in \u001B[0;36m<cell line: 1>\u001B[0;34m()\u001B[0m\n\u001B[0;32m----> 1\u001B[0m titanic_dataset \u001B[38;5;241m=\u001B[39m sns\u001B[38;5;241m.\u001B[39mload_dataset(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtitanic\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[1;32m      2\u001B[0m titanic_dataset\n",
      "\u001B[0;31mNameError\u001B[0m: name 'sns' is not defined"
     ]
    }
   ],
   "source": [
    "titanic_dataset = sns.load_dataset(\"titanic\")\n",
    "titanic_dataset"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "7d815263",
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