D35 探索性資料分析(EDA)_數據理解與重覆和遺失值處理 作業.ipynb

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   "source": [
    "## 作業:\n",
    "課程範例以 訓練資料集來檢視，先看一下測試資料特性，再把測試資料集和訓練資料集合併，並回答下列問題，   \n",
    "目的:讓大家熟悉對應這樣的問題，我們要提取怎樣的函數來進行計算。   \n",
    "\n",
    "* Q1: 觀察測試(test)資料集和訓練(Train)資料集的變數的差異性?\n",
    "* Q2: 測試資料集是否有遺失值?\n",
    "* Q3: 從合併資料選取一個變數，嘗試去做各種不同遺失值的處理，並透過圖形或數值來做輔助判斷，補值前與後的差異，你覺得以這個變數而言，試著說明每一個方法的差異。   \n"
   ]
  },
  {
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    "executionInfo": {
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     "status": "ok",
     "timestamp": 1578021044012,
     "user": {
      "displayName": "Mora chen",
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   "source": [
    "#把需要的 library import 進來\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from IPython.display import display\n",
    "#讓圖可以在 jupyter notebook顯示\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#顯示圖形的函數，可不先不用理解，直接用\n",
    "from IPython.display import display\n",
    "from IPython.display import display_html\n",
    "def display_side_by_side(*args):\n",
    "    html_str=''\n",
    "    for df in args:\n",
    "        html_str+=df.to_html()\n",
    "    display_html(html_str.replace('table','table style=\"display:inline\"'),raw=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 把兩個訓練資料集和測試資料集讀進來\n",
    "\n",
    "dftrain = pd.read_csv(\"Titanic_train.csv\")\n",
    "dftest = pd.read_csv(\"Titanic_test.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q1: 判斷 測試資料集和訓練資料集欄位變數是否有差異性?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
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       "      <th>Fare</th>\n",
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       "      <th>Embarked</th>\n",
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       "      <td>Braund, Mr. Owen Harris</td>\n",
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       "      <td>A/5 21171</td>\n",
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       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
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       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
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       "      <td>Heikkinen, Miss. Laina</td>\n",
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       "      <td>S</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
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       "      <th>4</th>\n",
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       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
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   ],
   "source": [
    "# Q1: 判斷 測試資料集和訓練資料集欄位變數是否有差異性?\n",
    "\n",
    "dftrain.head(5)\n"
   ]
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   "metadata": {},
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       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
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       "      <th>0</th>\n",
       "      <td>892</td>\n",
       "      <td>3</td>\n",
       "      <td>Kelly, Mr. James</td>\n",
       "      <td>male</td>\n",
       "      <td>34.5</td>\n",
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       "      <td>Wilkes, Mrs. James (Ellen Needs)</td>\n",
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       "      <td>Wirz, Mr. Albert</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
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       "      <td>8.6625</td>\n",
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       "      <th>4</th>\n",
       "      <td>896</td>\n",
       "      <td>3</td>\n",
       "      <td>Hirvonen, Mrs. Alexander (Helga E Lindqvist)</td>\n",
       "      <td>female</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3101298</td>\n",
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       "   PassengerId  Pclass                                          Name     Sex  \\\n",
       "0          892       3                              Kelly, Mr. James    male   \n",
       "1          893       3              Wilkes, Mrs. James (Ellen Needs)  female   \n",
       "2          894       2                     Myles, Mr. Thomas Francis    male   \n",
       "3          895       3                              Wirz, Mr. Albert    male   \n",
       "4          896       3  Hirvonen, Mrs. Alexander (Helga E Lindqvist)  female   \n",
       "\n",
       "    Age  SibSp  Parch   Ticket     Fare Cabin Embarked  \n",
       "0  34.5      0      0   330911   7.8292   NaN        Q  \n",
       "1  47.0      1      0   363272   7.0000   NaN        S  \n",
       "2  62.0      0      0   240276   9.6875   NaN        Q  \n",
       "3  27.0      0      0   315154   8.6625   NaN        S  \n",
       "4  22.0      1      1  3101298  12.2875   NaN        S  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dftest.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A1 : Test 資料集沒有 'Survived'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q2: 測試資料集是否有遺失值?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   PassengerId  Pclass   Name    Sex    Age  SibSp  Parch  Ticket   Fare  \\\n",
      "0        False   False  False  False  False  False  False   False  False   \n",
      "1        False   False  False  False  False  False  False   False  False   \n",
      "2        False   False  False  False  False  False  False   False  False   \n",
      "3        False   False  False  False  False  False  False   False  False   \n",
      "4        False   False  False  False  False  False  False   False  False   \n",
      "\n",
      "   Cabin  Embarked  \n",
      "0   True     False  \n",
      "1   True     False  \n",
      "2   True     False  \n",
      "3   True     False  \n",
      "4   True     False  \n"
     ]
    }
   ],
   "source": [
    "#可以嘗試用範例的程式\n",
    "\n",
    "print(dftest.isnull().head(5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q3: 從合併資料選取一個變數，嘗試去做各種不同遺失值的處理，並透過圖形來做輔助判斷，補值前與後的差異，你覺得以這個變數而言，試著說明每一個方法的差異。   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#合併資料\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 以 XXX 為例，先看 Cabin  出現值的特性\n",
    "\n"
   ]
  }
 ],
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