mlessentials/Lab10/Exercise10.03/Exercise10_03.ipynb

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    "colab": {},
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   "source": [
    "import pandas as pd"
   ]
  },
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    "colab": {},
    "colab_type": "code",
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   "source": [
    "file_url = '../dataset/ames_iowa_housing.csv'"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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    "df = pd.read_csv(file_url)"
   ]
  },
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   "source": [
    "num_df = df.select_dtypes(include='number')"
   ]
  },
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   "source": [
    "num_cols = num_df.columns\n",
    "num_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "colab": {},
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   "source": [
    "def describe_numeric(df, col_name):\n",
    "  print(f\"\\nCOLUMN: {col_name}\")\n",
    "  print(f\"Minimum: {df[col_name].min()}\")\n",
    "  print(f\"Maximum: {df[col_name].max()}\")\n",
    "  print(f\"Average: {df[col_name].mean()}\")\n",
    "  print(f\"Standard Deviation: {df[col_name].std()}\")\n",
    "  print(f\"Median: {df[col_name].median()}\")"
   ]
  },
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   "outputs": [],
   "source": [
    "describe_numeric(df, 'SalePrice')"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
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    "outputId": "b3cb94de-20e1-4ad9-cf6e-7951d2c1c5bf"
   },
   "outputs": [],
   "source": [
    "for col_name in num_cols:\n",
    "  describe_numeric(df, col_name)"
   ]
  }
 ],
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