ch06 np.where, pd.rename, pd.apply, pd.astype, pd.get_dummies.ipynb

{
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   "cell_type": "markdown",
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   "source": [
    "# 01 파생변수 개요\n",
    "## 파생변수의 정의\n",
    "- 기존 변수를 조합하여 만들어내는 새로운 변수\n",
    "\n",
    "## 파생변수의 예시\n",
    "- 기온, 습도, 풍속을 조합하여 만든 체감온도 변수\n",
    "- 물건 주문 건수와 환불 건수를 조합하여 만든 환불 비율 변수\n",
    "- 기존 방문 매장 정보를 활용한 주 방문 매장 변수\n",
    "\n",
    "# 02 주요 함수 및 메서드 소개\n",
    "## numpy - where()\n",
    "- 조건에 따라 두 개의 출력을 내는 함수\n",
    "- if() 함수를 대체할 수 있으며 조건, True일 때 반환값, False일 때 반환값을 차례대로 기입"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "99732379",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "876e4680",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"강의자료/실습파일/iris.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "69adbe6f",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "      <th>is_setosa</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species  is_setosa\n",
       "0           5.1          3.5           1.4          0.2  setosa          1\n",
       "1           4.9          3.0           1.4          0.2  setosa          1\n",
       "2           4.7          3.2           1.3          0.2  setosa          1\n",
       "3           4.6          3.1           1.5          0.2  setosa          1\n",
       "4           5.0          3.6           1.4          0.2  setosa          1"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"is_setosa\"] = np.where(df[\"Species\"] == \"setosa\", 1, 0)  # where() : 조건에 따라 두 개의 출력을 내는 함수\n",
    "df.head() # is_setosa 칼럼이 생성된 것을 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f4af582a",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "      <th>is_setosa</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Sepal.Length  Sepal.Width  Petal.Length  Petal.Width    Species  \\\n",
       "145           6.7          3.0           5.2          2.3  virginica   \n",
       "146           6.3          2.5           5.0          1.9  virginica   \n",
       "147           6.5          3.0           5.2          2.0  virginica   \n",
       "148           6.2          3.4           5.4          2.3  virginica   \n",
       "149           5.9          3.0           5.1          1.8  virginica   \n",
       "\n",
       "     is_setosa  \n",
       "145          0  \n",
       "146          0  \n",
       "147          0  \n",
       "148          0  \n",
       "149          0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "673c4c02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>is_setosa</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Species</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>setosa</th>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>versicolor</th>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>virginica</th>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "is_setosa    0   1\n",
       "Species           \n",
       "setosa       0  50\n",
       "versicolor  50   0\n",
       "virginica   50   0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(df[\"Species\"], df[\"is_setosa\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4ce78bbf",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "      <th>is_setosa</th>\n",
       "      <th>is_setosa_2</th>\n",
       "      <th>is_setosa_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species  is_setosa  \\\n",
       "0           5.1          3.5           1.4          0.2  setosa          1   \n",
       "1           4.9          3.0           1.4          0.2  setosa          1   \n",
       "2           4.7          3.2           1.3          0.2  setosa          1   \n",
       "3           4.6          3.1           1.5          0.2  setosa          1   \n",
       "4           5.0          3.6           1.4          0.2  setosa          1   \n",
       "\n",
       "   is_setosa_2  is_setosa_3  \n",
       "0            1            1  \n",
       "1            1            1  \n",
       "2            1            1  \n",
       "3            1            1  \n",
       "4            1            1  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# np.where() 대신 다른 방법, True=1 을 활용 \n",
    "df[\"is_setosa_2\"] = (df[\"Species\"] == \"setosa\") + 0 \n",
    "df[\"is_setosa_3\"] = (df[\"Species\"] == \"setosa\") * 1 \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30fc1ebd",
   "metadata": {},
   "source": [
    "## pandas - rename()\n",
    "- 데이터프레임의 변수명을 변경할 때 사용하는 메서드\n",
    "- columns 인자에 기존 변수명과 신규 변수명의 쌍을 딕셔너리로 구성하여 입력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7aa765ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SL</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "      <th>is_setosa</th>\n",
       "      <th>is_setosa_2</th>\n",
       "      <th>is_setosa_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      SL  Sepal.Width  Petal.Length  Petal.Width    Species  is_setosa  \\\n",
       "0    5.1          3.5           1.4          0.2     setosa          1   \n",
       "1    4.9          3.0           1.4          0.2     setosa          1   \n",
       "2    4.7          3.2           1.3          0.2     setosa          1   \n",
       "3    4.6          3.1           1.5          0.2     setosa          1   \n",
       "4    5.0          3.6           1.4          0.2     setosa          1   \n",
       "..   ...          ...           ...          ...        ...        ...   \n",
       "145  6.7          3.0           5.2          2.3  virginica          0   \n",
       "146  6.3          2.5           5.0          1.9  virginica          0   \n",
       "147  6.5          3.0           5.2          2.0  virginica          0   \n",
       "148  6.2          3.4           5.4          2.3  virginica          0   \n",
       "149  5.9          3.0           5.1          1.8  virginica          0   \n",
       "\n",
       "     is_setosa_2  is_setosa_3  \n",
       "0              1            1  \n",
       "1              1            1  \n",
       "2              1            1  \n",
       "3              1            1  \n",
       "4              1            1  \n",
       "..           ...          ...  \n",
       "145            0            0  \n",
       "146            0            0  \n",
       "147            0            0  \n",
       "148            0            0  \n",
       "149            0            0  \n",
       "\n",
       "[150 rows x 8 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(columns = {\"Sepal.Length\": \"SL\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c59c4ca1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "      <th>is_setosa</th>\n",
       "      <th>is_setosa_2</th>\n",
       "      <th>is_setosa_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species  is_setosa  \\\n",
       "0           5.1          3.5           1.4          0.2  setosa          1   \n",
       "1           4.9          3.0           1.4          0.2  setosa          1   \n",
       "2           4.7          3.2           1.3          0.2  setosa          1   \n",
       "3           4.6          3.1           1.5          0.2  setosa          1   \n",
       "4           5.0          3.6           1.4          0.2  setosa          1   \n",
       "\n",
       "   is_setosa_2  is_setosa_3  \n",
       "0            1            1  \n",
       "1            1            1  \n",
       "2            1            1  \n",
       "3            1            1  \n",
       "4            1            1  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head() #rename()은 덮어쓰지 않음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c10d98dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SL</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "      <th>is_setosa</th>\n",
       "      <th>is_setosa_2</th>\n",
       "      <th>is_setosa_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SL  Sepal.Width  Petal.Length  Petal.Width Species  is_setosa  \\\n",
       "0  5.1          3.5           1.4          0.2  setosa          1   \n",
       "1  4.9          3.0           1.4          0.2  setosa          1   \n",
       "2  4.7          3.2           1.3          0.2  setosa          1   \n",
       "3  4.6          3.1           1.5          0.2  setosa          1   \n",
       "4  5.0          3.6           1.4          0.2  setosa          1   \n",
       "\n",
       "   is_setosa_2  is_setosa_3  \n",
       "0            1            1  \n",
       "1            1            1  \n",
       "2            1            1  \n",
       "3            1            1  \n",
       "4            1            1  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.rename(columns = {\"Sepal.Length\": \"SL\"})  #기존 df에 넣어야 덮어써짐\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f43d910d",
   "metadata": {},
   "source": [
    "## pandas - apply()\n",
    "- row 또는 column 방향으로 일괄 계산하는 메서드\n",
    "- axis 인자 설정으로 연산 방향 설정 가능(axis = 0은 row, axis = 1은 column 방향)\n",
    "- 사용자 정의 함수 또는 lambda 함수(일회성 함수)로 복잡한 연산 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "17cc5451",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>datetime</th>\n",
       "      <th>season</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weather</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>humidity</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01 00:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-01 01:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0  2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1  2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count  \n",
       "0        81        0.0       3          13     16  \n",
       "1        80        0.0       8          32     40  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike = pd.read_csv(\"강의자료/실습파일/bike.csv\")\n",
    "bike.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f11acdf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['datetime', 'season', 'holiday', 'workingday', 'weather', 'temp',\n",
       "       'atemp', 'humidity', 'windspeed', 'casual', 'registered', 'count'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike.columns # 변수명 확인 casula 9 registered 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "63bb772e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   casual  registered\n",
       "0       3          13\n",
       "1       8          32\n",
       "2       5          27\n",
       "3       3          10\n",
       "4       0           1"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub = bike.iloc[:, 9:11]  # iloc는 index번호로 불러옴\n",
    "bike_sub.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "410498d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>casual</th>\n",
       "      <th>registered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   casual  registered\n",
       "0       3          13\n",
       "1       8          32\n",
       "2       5          27\n",
       "3       3          10\n",
       "4       0           1"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub = bike.loc[:, [\"casual\", \"registered\"]]\n",
    "bike_sub.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3abd19ee",
   "metadata": {},
   "outputs": [
    {
     "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>casual</th>\n",
       "      <th>registered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   casual  registered\n",
       "0       3          13\n",
       "1       8          32\n",
       "2       5          27\n",
       "3       3          10\n",
       "4       0           1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub = bike.loc[:, \"casual\": \"registered\"]\n",
    "bike_sub.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2c870648",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "casual         392135\n",
       "registered    1693341\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a5822b05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         16\n",
       "1         40\n",
       "2         32\n",
       "3         13\n",
       "4          1\n",
       "        ... \n",
       "10881    336\n",
       "10882    241\n",
       "10883    168\n",
       "10884    129\n",
       "10885     88\n",
       "Length: 10886, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub.sum(axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e1b7d4e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "casual         392135\n",
       "registered    1693341\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub.apply(func = sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6f78c8f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         16\n",
       "1         40\n",
       "2         32\n",
       "3         13\n",
       "4          1\n",
       "        ... \n",
       "10881    336\n",
       "10882    241\n",
       "10883    168\n",
       "10884    129\n",
       "10885     88\n",
       "Length: 10886, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub.apply(func = sum, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "df14a446",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "casual         36\n",
       "registered    156\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub.apply(func = lambda x: round(x.mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e53ba72",
   "metadata": {},
   "source": [
    "## pandas - astype()\n",
    "- 시리즈의 속성을 변경할 때 사용하는 메서드\n",
    "- int / float / str 은 각각 정수 / 실수 / 문자열을 뜻하며 원하는 속성을 지정 및 변경"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ff4ce9eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10886 entries, 0 to 10885\n",
      "Data columns (total 2 columns):\n",
      " #   Column      Non-Null Count  Dtype\n",
      "---  ------      --------------  -----\n",
      " 0   casual      10886 non-null  int64\n",
      " 1   registered  10886 non-null  int64\n",
      "dtypes: int64(2)\n",
      "memory usage: 170.2 KB\n"
     ]
    }
   ],
   "source": [
    "bike_sub.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2274e67e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         3\n",
       "1         8\n",
       "2         5\n",
       "3         3\n",
       "4         0\n",
       "         ..\n",
       "10881     7\n",
       "10882    10\n",
       "10883     4\n",
       "10884    12\n",
       "10885     4\n",
       "Name: casual, Length: 10886, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub[\"casual\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "964b95f4",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for +: 'int' and 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_42840\\1977721526.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;36m3\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\"대\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
     ]
    }
   ],
   "source": [
    "3 + \"대\"  # 정수와 문자열은 더할 수 없음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b4ac008a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3대'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"3\" + \"대\" # 문자열끼리는 더할 수 있음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7f8a8a39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         3대\n",
       "1         8대\n",
       "2         5대\n",
       "3         3대\n",
       "4         0대\n",
       "        ... \n",
       "10881     7대\n",
       "10882    10대\n",
       "10883     4대\n",
       "10884    12대\n",
       "10885     4대\n",
       "Name: casual, Length: 10886, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_sub[\"casual\"].astype(\"str\") + \"대\" #문자열로 변경하여 '단위'를 붙여줌"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0e7cda60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2011-01-01 00:00:00\n",
       "1    2011-01-01 01:00:00\n",
       "2    2011-01-01 02:00:00\n",
       "Name: datetime, dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike[\"datetime\"][:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "fc0e40ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2011\n",
       "1    2011\n",
       "2    2011\n",
       "Name: datetime, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike[\"datetime\"][:3].str.slice(0, 4)  # 연도만 뽑음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8f71a175",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    01\n",
       "1    01\n",
       "2    01\n",
       "Name: datetime, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike[\"datetime\"][:3].str.slice(5, 7)  # 월만 뽑음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "81ac939f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2011-01-01 00:00:00\n",
       "1   2011-01-01 01:00:00\n",
       "2   2011-01-01 02:00:00\n",
       "Name: datetime, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_time = pd.to_datetime(bike[\"datetime\"][:3])  # 데이터 타입을 datetime으로 변경 \n",
    "bike_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ca4101a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2011\n",
       "1    2011\n",
       "2    2011\n",
       "Name: datetime, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_time.dt.year # 바로 연 / 월 / 일 등 확인 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b6688e61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    1\n",
       "2    1\n",
       "Name: datetime, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_time.dt.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "234e3b66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0\n",
       "1    1\n",
       "2    2\n",
       "Name: datetime, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_time.dt.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b235210b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5\n",
       "1    5\n",
       "2    5\n",
       "Name: datetime, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_time.dt.weekday"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d4c301e",
   "metadata": {},
   "source": [
    "## pandas - get_dummies()\n",
    "- 편리한 가변수 생성(One Hot Encoding)을 도와주는 함수\n",
    "- columns 인자에 명목형 변수 지정 및 처리 가능\n",
    "- drop_first 인자에 True를 입력하면 마지막 가변수 제외 후 생성"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e22d4824",
   "metadata": {},
   "outputs": [
    {
     "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>datetime</th>\n",
       "      <th>season</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weather</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>humidity</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01 00:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-01 01:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0  2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1  2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count  \n",
       "0        81        0.0       3          13     16  \n",
       "1        80        0.0       8          32     40  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "8fd222cc",
   "metadata": {},
   "outputs": [
    {
     "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>datetime</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weather</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>humidity</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>count</th>\n",
       "      <th>season_1</th>\n",
       "      <th>season_2</th>\n",
       "      <th>season_3</th>\n",
       "      <th>season_4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01 00:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-01 01:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-01-01 02:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-01 03:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-01 04:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  holiday  workingday  weather  temp   atemp  humidity  \\\n",
       "0  2011-01-01 00:00:00        0           0        1  9.84  14.395        81   \n",
       "1  2011-01-01 01:00:00        0           0        1  9.02  13.635        80   \n",
       "2  2011-01-01 02:00:00        0           0        1  9.02  13.635        80   \n",
       "3  2011-01-01 03:00:00        0           0        1  9.84  14.395        75   \n",
       "4  2011-01-01 04:00:00        0           0        1  9.84  14.395        75   \n",
       "\n",
       "   windspeed  casual  registered  count  season_1  season_2  season_3  \\\n",
       "0        0.0       3          13     16         1         0         0   \n",
       "1        0.0       8          32     40         1         0         0   \n",
       "2        0.0       5          27     32         1         0         0   \n",
       "3        0.0       3          10     13         1         0         0   \n",
       "4        0.0       0           1      1         1         0         0   \n",
       "\n",
       "   season_4  \n",
       "0         0  \n",
       "1         0  \n",
       "2         0  \n",
       "3         0  \n",
       "4         0  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_dum = pd.get_dummies(data = bike, columns = [\"season\"]) # season의 더미 1~4 생성, 첫번재 더미가 기존파일과 같음\n",
    "bike_dum.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4c962f55",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2011-01-01 00:00:00</td>\n",
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       "      <td>2011-01-01 01:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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      "text/plain": [
       "              datetime  holiday  workingday  weather  temp   atemp  humidity  \\\n",
       "0  2011-01-01 00:00:00        0           0        1  9.84  14.395        81   \n",
       "1  2011-01-01 01:00:00        0           0        1  9.02  13.635        80   \n",
       "\n",
       "   windspeed  casual  registered  count  season_2  season_3  season_4  \n",
       "0        0.0       3          13     16         0         0         0  \n",
       "1        0.0       8          32     40         0         0         0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_dum = pd.get_dummies(data = bike, columns = [\"season\"],\n",
    "                         drop_first = True)  # 첫번째 더미를 버림\n",
    "bike_dum.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fac8e960",
   "metadata": {},
   "source": [
    "## Q1. temp변수와 atemp변수 차이의 절대값 평균은?\n",
    "1) bike.csv파일 사용  \n",
    "2) abs()매서드 활용"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b8fcde64",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>season</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weather</th>\n",
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       "      <td>40</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-01-01 02:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-01 03:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-01 04:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0  2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1  2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "2  2011-01-01 02:00:00       1        0           0        1  9.02  13.635   \n",
       "3  2011-01-01 03:00:00       1        0           0        1  9.84  14.395   \n",
       "4  2011-01-01 04:00:00       1        0           0        1  9.84  14.395   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count  \n",
       "0        81        0.0       3          13     16  \n",
       "1        80        0.0       8          32     40  \n",
       "2        80        0.0       5          27     32  \n",
       "3        75        0.0       3          10     13  \n",
       "4        75        0.0       0           1      1  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q1 = pd.read_csv(\"강의자료/실습파일/bike.csv\")\n",
    "Q1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6b27456b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.5091985118501188"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q1[\"diff\"] = Q1[\"temp\"] - Q1[\"atemp\"]\n",
    "Q1[\"diff\"].abs().mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1958311d",
   "metadata": {},
   "source": [
    "## Q2. casual 값의 최대값이 25가 넘은 날은 총 며칠인가?\n",
    "1) bike.csv파일 사용  \n",
    "2) date 어트리뷰트 활용"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "b617be19",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>32</td>\n",
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       "      <th>3</th>\n",
       "      <td>2011-01-01 03:00:00</td>\n",
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       "      <th>4</th>\n",
       "      <td>2011-01-01 04:00:00</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0  2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1  2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "2  2011-01-01 02:00:00       1        0           0        1  9.02  13.635   \n",
       "3  2011-01-01 03:00:00       1        0           0        1  9.84  14.395   \n",
       "4  2011-01-01 04:00:00       1        0           0        1  9.84  14.395   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count  \n",
       "0        81        0.0       3          13     16  \n",
       "1        80        0.0       8          32     40  \n",
       "2        80        0.0       5          27     32  \n",
       "3        75        0.0       3          10     13  \n",
       "4        75        0.0       0           1      1  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q2 = pd.read_csv(\"강의자료/실습파일/bike.csv\")\n",
    "Q2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "0bc8d330",
   "metadata": {},
   "outputs": [
    {
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       "      <th>registered</th>\n",
       "      <th>count</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01 00:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-01 01:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-01-01 02:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-01 03:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-01 04:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0 2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1 2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "2 2011-01-01 02:00:00       1        0           0        1  9.02  13.635   \n",
       "3 2011-01-01 03:00:00       1        0           0        1  9.84  14.395   \n",
       "4 2011-01-01 04:00:00       1        0           0        1  9.84  14.395   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count        date  \n",
       "0        81        0.0       3          13     16  2011-01-01  \n",
       "1        80        0.0       8          32     40  2011-01-01  \n",
       "2        80        0.0       5          27     32  2011-01-01  \n",
       "3        75        0.0       3          10     13  2011-01-01  \n",
       "4        75        0.0       0           1      1  2011-01-01  "
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q2[\"datetime\"] = pd.to_datetime(Q2[\"datetime\"])\n",
    "Q2[\"date\"] = Q2[\"datetime\"].dt.date\n",
    "Q2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "8d6db6ec",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2011-01-01    47\n",
       "2011-01-02    20\n",
       "2011-01-03    14\n",
       "2011-01-04    18\n",
       "2011-01-05    12\n",
       "Name: casual, dtype: int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q2_agg = Q2.groupby(\"date\")[\"casual\"].max() # \"date\" 별 \"casual\"의 최대값\n",
    "Q2_agg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "40116632",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(Q2_agg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "ab522355",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2011-01-01    47\n",
       "2011-01-15    33\n",
       "2011-01-16    35\n",
       "2011-02-06    52\n",
       "2011-02-12    47\n",
       "Name: casual, dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q2_agg_up25 = Q2_agg[Q2_agg > 25]\n",
    "Q2_agg_up25.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c135d71c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "384"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q2_agg_up25.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "f08a2f6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>casual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  casual\n",
       "0  2011-01-01      47\n",
       "1  2011-01-02      20\n",
       "2  2011-01-03      14\n",
       "3  2011-01-04      18\n",
       "4  2011-01-05      12"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 데이터프레임으로 처리하는 방법\n",
    "Q2_agg_v2 = Q2.groupby(\"date\")[\"casual\"].max().reset_index()\n",
    "Q2_agg_v2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52279d86",
   "metadata": {},
   "source": [
    "## Q3. 시간대별 registered 평균을 산출했을 때 값이 가장 큰 시간은?\n",
    "1) bike.csv 파일 사용  \n",
    "2) hour 어트리뷰트 활용"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8e9d8d3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>season</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weather</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01 00:00:00</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-01 01:00:00</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-01-01 02:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.02</td>\n",
       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-01 03:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-01 04:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0  2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1  2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "2  2011-01-01 02:00:00       1        0           0        1  9.02  13.635   \n",
       "3  2011-01-01 03:00:00       1        0           0        1  9.84  14.395   \n",
       "4  2011-01-01 04:00:00       1        0           0        1  9.84  14.395   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count  \n",
       "0        81        0.0       3          13     16  \n",
       "1        80        0.0       8          32     40  \n",
       "2        80        0.0       5          27     32  \n",
       "3        75        0.0       3          10     13  \n",
       "4        75        0.0       0           1      1  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q3 = pd.read_csv(\"강의자료/실습파일/bike.csv\")\n",
    "Q3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "09eee23c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>season</th>\n",
       "      <th>holiday</th>\n",
       "      <th>workingday</th>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>13.635</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-01 03:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.84</td>\n",
       "      <td>14.395</td>\n",
       "      <td>75</td>\n",
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       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-01 04:00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             datetime  season  holiday  workingday  weather  temp   atemp  \\\n",
       "0 2011-01-01 00:00:00       1        0           0        1  9.84  14.395   \n",
       "1 2011-01-01 01:00:00       1        0           0        1  9.02  13.635   \n",
       "2 2011-01-01 02:00:00       1        0           0        1  9.02  13.635   \n",
       "3 2011-01-01 03:00:00       1        0           0        1  9.84  14.395   \n",
       "4 2011-01-01 04:00:00       1        0           0        1  9.84  14.395   \n",
       "\n",
       "   humidity  windspeed  casual  registered  count  hour  \n",
       "0        81        0.0       3          13     16     0  \n",
       "1        80        0.0       8          32     40     1  \n",
       "2        80        0.0       5          27     32     2  \n",
       "3        75        0.0       3          10     13     3  \n",
       "4        75        0.0       0           1      1     4  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q3[\"datetime\"] = pd.to_datetime(Q3[\"datetime\"])\n",
    "Q3[\"hour\"] = Q3[\"datetime\"].dt.hour\n",
    "Q3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "55de0fd9",
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hour</th>\n",
       "      <th>registered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>44.826374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>27.345815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>18.080357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>9.076212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5.144796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>18.311947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>72.109890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>202.202198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>341.226374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>190.824176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>128.973626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>150.621978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>187.677632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>183.728070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>166.853070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>178.269737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>241.289474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>393.324561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>369.462719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>266.203947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>191.785088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>144.802632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>110.973684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>74.046053</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    hour  registered\n",
       "0      0   44.826374\n",
       "1      1   27.345815\n",
       "2      2   18.080357\n",
       "3      3    9.076212\n",
       "4      4    5.144796\n",
       "5      5   18.311947\n",
       "6      6   72.109890\n",
       "7      7  202.202198\n",
       "8      8  341.226374\n",
       "9      9  190.824176\n",
       "10    10  128.973626\n",
       "11    11  150.621978\n",
       "12    12  187.677632\n",
       "13    13  183.728070\n",
       "14    14  166.853070\n",
       "15    15  178.269737\n",
       "16    16  241.289474\n",
       "17    17  393.324561\n",
       "18    18  369.462719\n",
       "19    19  266.203947\n",
       "20    20  191.785088\n",
       "21    21  144.802632\n",
       "22    22  110.973684\n",
       "23    23   74.046053"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q3_agg = Q3.groupby(\"hour\")[\"registered\"].mean().reset_index()\n",
    "Q3_agg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "318aaa27",
   "metadata": {},
   "outputs": [
    {
     "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>hour</th>\n",
       "      <th>registered</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>393.324561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    hour  registered\n",
       "17    17  393.324561"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q3_agg.loc[Q3_agg[\"registered\"] == Q3_agg[\"registered\"].max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "9a404771",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hour           17.000000\n",
       "registered    393.324561\n",
       "Name: 17, dtype: float64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q3_agg.loc[Q3_agg[\"registered\"].idxmax()] # 다른 방법"
   ]
  }
 ],
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