Day_004_HW.ipynb

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   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
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    "# 設定 data_path, 並讀取 app_train\n",
    "dir_data = './data/'\n",
    "f_app_train = os.path.join(dir_data, 'application_train.csv')\n",
    "app_train = pd.read_csv(f_app_train)"
   ]
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   "source": [
    "## 作業\n",
    "將下列部分資料片段 sub_train 使用 One Hot encoding, 並觀察轉換前後的欄位數量 (使用 shape) 與欄位名稱 (使用 head) 變化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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     "output_type": "stream",
     "text": [
      "(307511, 1)\n"
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    {
     "data": {
      "text/html": [
       "<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>WEEKDAY_APPR_PROCESS_START</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MONDAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MONDAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WEDNESDAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>THURSDAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  WEEKDAY_APPR_PROCESS_START\n",
       "0                  WEDNESDAY\n",
       "1                     MONDAY\n",
       "2                     MONDAY\n",
       "3                  WEDNESDAY\n",
       "4                   THURSDAY"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_train = pd.DataFrame(app_train['WEEKDAY_APPR_PROCESS_START'])\n",
    "print(sub_train.shape)\n",
    "sub_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Your Code Here\n",
    "\"\"\"\n",
    "sub_train = pd.get_dummies(sub_train)\n",
    "print(sub_train['WEEKDAY_APPR_PROCESS_START_MONDAY'].head())\n",
    "print(sub_train['WEEKDAY_APPR_PROCESS_START_WEDNESDAY'].head())\n",
    "print(sub_train['WEEKDAY_APPR_PROCESS_START_THURSDAY'].head())"
   ]
  }
 ],
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