Solution/Day_11_Solution_v2.ipynb

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    "# [作業目標]\n",
    "\n",
    "1. 根據題目給的 DataFrame 完成下列操作：\n",
    "\n",
    "```\n",
    "- 計算每個不同種類 animal 的 age 的平均數\n",
    "- 計算每個不同種類 animal 的 age 的平均數\n",
    "- 將資料依照 Age 欄位由小到大排序，再依照 visits 欄位由大到小排序\n",
    "- 將 priority 欄位中的 yes 和 no 字串，換成是布林值 的 True 和 False\n",
    "```\n",
    "\n",
    "\n",
    "2. 一個包含兩個欄位的 DataFrame，將每個數字減去\n",
    "\n",
    "```\n",
    "* 1) 該欄位的平均數\n",
    "* 2) 該筆資料平均數\n",
    "```\n",
    "\n",
    "3. 承上題，請問：\n",
    "\n",
    "```\n",
    "* 1) 哪一比的資料總合最小\n",
    "* 2) 哪一欄位的資料總合最小\n",
    "```\n"
   ]
  },
  {
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   "source": [
    "# 作業 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 根據題目給的 DataFrame 完成下列操作：\n",
    "\n",
    "```\n",
    "- 計算每個不同種類 animal 的 age 的平均數\n",
    "- 計算每個不同種類 animal 的 age 的平均數\n",
    "- 將資料依照 Age 欄位由小到大排序，再依照 visits 欄位由大到小排序\n",
    "- 將 priority 欄位中的 yes 和 no 字串，換成是布林值 的 True 和 False\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 記得先 Import 正確的套件\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>animal</th>\n",
       "      <th>age</th>\n",
       "      <th>visits</th>\n",
       "      <th>priority</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>cat</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>cat</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>snake</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>dog</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>dog</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>cat</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>snake</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>cat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>dog</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>dog</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  animal  age  visits priority\n",
       "a    cat  2.5       1      yes\n",
       "b    cat  3.0       3      yes\n",
       "c  snake  0.5       2       no\n",
       "d    dog  NaN       3      yes\n",
       "e    dog  5.0       2       no\n",
       "f    cat  2.0       3       no\n",
       "g  snake  4.5       1       no\n",
       "h    cat  NaN       1      yes\n",
       "i    dog  7.0       2       no\n",
       "j    dog  3.0       1       no"
      ]
     },
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   "source": [
    "data = {\n",
    "    'animal': ['cat', 'cat', 'snake', 'dog', 'dog', 'cat', 'snake', 'cat', 'dog', 'dog'],\n",
    "    'age': [2.5, 3, 0.5, np.nan, 5, 2, 4.5, np.nan, 7, 3],\n",
    "    'visits': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],\n",
    "    'priority': ['yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'yes', 'no', 'no']\n",
    "}\n",
    "\n",
    "labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']\n",
    "df = pd.DataFrame(data, index=labels)\n",
    "df"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 一個包含兩個欄位的 DataFrame，將每個數字減去\n",
    "\n",
    "* 1) 該欄位的平均數\n",
    "* 2) 該筆資料平均數"
   ]
  },
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    "df = pd.DataFrame(np.random.random(size=(5, 3)))\n",
    "df"
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   "source": [
    "df - df.mean()"
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    "df.sub(df.mean(axis=1) ,axis=0)"
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   "source": [
    "### 3. 承上題，請問：\n",
    "\n",
    "1) 哪一比的資料總合最小\n",
    "2) 哪一欄位的資料總合最小\n",
    "\n"
   ]
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      "/Users/wei/.virtualenvs/py3/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: 'argmax' is deprecated, use 'idxmax' instead. The behavior of 'argmax'\n",
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      "/Users/wei/.virtualenvs/py3/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: 'argmax' is deprecated, use 'idxmax' instead. The behavior of 'argmax'\n",
      "will be corrected to return the positional maximum in the future.\n",
      "Use 'series.values.argmax' to get the position of the maximum now.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
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