PandasBasic_2_DataFrame.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---  \n",
    "title: \"[Pandas 기초]3.Pandas의 자료구조-DataFrame\"  \n",
    "categories: \"빅데이터분석/Pandas\"   \n",
    "date: \"2019-08-16\"  \n",
    "tags: [\"Pandas\",\"DataFrame\", \"데이터 분석\"]  \n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "안녕하세요. PSYda입니다.  \n",
    "\n",
    "이번 포스팅에서는 Pandas의 DataFrame에 대해 알아보겠습니다.  \n",
    "\n",
    "소개할 내용은 아래와 같습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id = \"summary\"> \n",
    "<ul>\n",
    "    <li>DataFrame <strong><span style = \"color:red\">생성</span></strong></li>\n",
    "    <li>DataFrame에 <strong><span style = \"color:red\">Data추가/삭제/조회</span></strong></li>\n",
    "\n",
    "</div>  \n",
    "  \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DataFrame 이란?\n",
    "\n",
    "<ul>\n",
    "    <li> 2차원 데이터 </li>\n",
    "    <li> 인덱스가 같은 하나 이상의 <strong><u>Series가 모여진 데이터</u></strong> </li>\n",
    "    <li> DBMS 의 관계형 Table 과 매우 유사 </li>\n",
    "</ul>\n",
    "\n",
    "<div class = 'CenterImg'>\n",
    "    <img src =\"./img/DataFrame_1.jpg\" alt = \"DataFrame_1\" />\n",
    "</div>\n",
    "\n",
    "먼저 DataFrame을 사용하기 위해 Pandas 라이브러리를 import 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pandas library import\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1 DataFrame 데이터 생성"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DataFrame을 생성하기 위해 셀에 DataFrame() 이라고 입력하고 괄호 안에서 Shift+tab 을 눌러보면 아래와 같은 정보가 보입니다.  \n",
    "\n",
    "DataFrame(<strong><span style = \"color:red\">data</span></strong>=None, <strong><span style = \"color:red\">index</span></strong>=None, <strong><span style = \"color:red\">columns</span></strong>=None, <strong><span style = \"color:red\">dtype</span></strong>=None, <strong><span style = \"color:red\">copy</span></strong>=False)  \n",
    "\n",
    "값을 입력해줄 수 있고, Default 가 None이기 때문에 값이 없으면 아무 동작도 하지 않습니다. 속성값들을 하나씩 알아보겠습니다.\n",
    "<ul>\n",
    "    <li><strong><span style = \"color:red\">data</span></strong> : 저장되는 데이터</li>\n",
    "    <li><strong><span style = \"color:red\">index</span></strong> : index에 대한 정보(미입력시 0부터 순차적으로 부여)</li>\n",
    "    <li><strong><span style = \"color:red\">columns</span></strong> : 열에 대한 이름값(미입력시 0부터 순차적으로 부여)</li>\n",
    "    <li><strong><span style = \"color:red\">dtype</span></strong> : 데이터에 대한 타입 명시(미입력시 자체적으로 판단)</li>\n",
    "</ul>\n",
    "\n",
    "예제를 확인하겠습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>키</th>\n",
       "      <th>몸무게</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "       키  몸무게\n",
       "사람1  180   75\n",
       "사람2  160   65\n",
       "사람3  170   75\n",
       "사람4  175   80"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data1 = DataFrame([[180,75],[160,65],[170,75], [175,80]], \n",
    "                  index = [\"사람1\",\"사람2\",\"사람3\",\"사람4\"], \n",
    "                  columns = [\"키\",\"몸무게\"])\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "index와 columns의 경우 선언후에도 별도로 입력할 수도 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "     0   1\n",
       "0  180  75\n",
       "1  160  65\n",
       "2  170  75\n",
       "3  175  80"
      ]
     },
     "execution_count": 7,
     "metadata": {},
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   ],
   "source": [
    "Data1 = DataFrame([[180,75],[160,65],[170,75], [175,80]])\n",
    "Data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "        0   1\n",
       "Man1  180  75\n",
       "Man2  160  65\n",
       "Man3  170  75\n",
       "Man4  175  80"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 인덱스 저장\n",
    "Data1.index = [\"Man1\",\"Man2\",\"Man3\",\"Man4\"]\n",
    "Data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight\n",
       "Man1     180      75\n",
       "Man2     160      65\n",
       "Man3     170      75\n",
       "Man4     175      80"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 컬럼명 저장\n",
    "Data1.columns = [\"Height\",\"Weight\"]\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 데이터 추가, 삭제"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2.1 Column 추가"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.1.1 값으로 추가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight  나이\n",
       "Man1     180      75  30\n",
       "Man2     160      65  40\n",
       "Man3     170      75  32\n",
       "Man4     175      80  33"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data1[\"나이\"] = [30,40,32,33]\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.1.2 Series 또는 DataFrame에서 추가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "      <td>23.148148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "      <td>25.390625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "      <td>25.951557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "      <td>26.122449</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight  나이        BMI\n",
       "Man1     180      75  30  23.148148\n",
       "Man2     160      65  40  25.390625\n",
       "Man3     170      75  32  25.951557\n",
       "Man4     175      80  33  26.122449"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bmi = 몸무게(kg) / 키(m)*키(m)\n",
    "Data1[\"BMI\"] = Data1[\"Weight\"] / ((Data1[\"Height\"] / 100) * (Data1[\"Height\"] / 100))\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2.2  행 추가"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "append 함수를 이용해서 행기준으로 데이터를 추가 할 수 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.2.1 Series와 List를 이용한 행추가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "      <td>23.148148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "      <td>25.390625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "      <td>25.951557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "      <td>26.122449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>187</td>\n",
       "      <td>85</td>\n",
       "      <td>34</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>183</td>\n",
       "      <td>80</td>\n",
       "      <td>32</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight  나이        BMI\n",
       "Man1     180      75  30  23.148148\n",
       "Man2     160      65  40  25.390625\n",
       "Man3     170      75  32  25.951557\n",
       "Man4     175      80  33  26.122449\n",
       "0        187      85  34   0.000000\n",
       "1        183      80  32   0.000000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listOfSeries = [pd.Series([187, 85, 34, 0], index = Data1.columns),\n",
    "               pd.Series([183, 80, 32, 0], index = Data1.columns)]\n",
    "Data1 = Data1.append(listOfSeries)\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.2.2 DataFrame을 행기준으로 추가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람5</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람6</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Height  Weight  나이  BMI\n",
       "사람5     180      75  30   33\n",
       "사람6     160      65  40   22"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = DataFrame([[180,75,30,33],[160,65,40,22]], \n",
    "               index = [\"사람5\",\"사람6\"], \n",
    "               columns = [\"Height\",\"Weight\",\"나이\",\"BMI\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "      <td>23.148148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "      <td>25.390625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "      <td>25.951557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "      <td>26.122449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>187</td>\n",
       "      <td>85</td>\n",
       "      <td>34</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>183</td>\n",
       "      <td>80</td>\n",
       "      <td>32</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람5</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "      <td>33.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람6</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight  나이        BMI\n",
       "Man1     180      75  30  23.148148\n",
       "Man2     160      65  40  25.390625\n",
       "Man3     170      75  32  25.951557\n",
       "Man4     175      80  33  26.122449\n",
       "0        187      85  34   0.000000\n",
       "1        183      80  32   0.000000\n",
       "사람5      180      75  30  33.000000\n",
       "사람6      160      65  40  22.000000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data1.append(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2.3 데이터 삭제"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "drop 함수를 쓰면 행과 열을 삭제 할 수 있습니다.\n",
    "\n",
    "axis option\n",
    "<ul>\n",
    "<li>0 : 행 기준 삭제</li>\n",
    "<li>1 : 열 기준 삭제</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.3.1 열 삭제"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>187</td>\n",
       "      <td>85</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>183</td>\n",
       "      <td>80</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight  나이\n",
       "Man1     180      75  30\n",
       "Man2     160      65  40\n",
       "Man3     170      75  32\n",
       "Man4     175      80  33\n",
       "0        187      85  34\n",
       "1        183      80  32"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data1 = Data1.drop(\"BMI\", axis = 1)\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.3.2 행 삭제"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Man2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Man4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>187</td>\n",
       "      <td>85</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>183</td>\n",
       "      <td>80</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Height  Weight  나이\n",
       "Man2     160      65  40\n",
       "Man3     170      75  32\n",
       "Man4     175      80  33\n",
       "0        187      85  34\n",
       "1        183      80  32"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data1 = Data1.drop(\"Man1\", axis = 0)\n",
    "Data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3 DataFrame 조회"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게  나이\n",
       "사람1  180   75  30\n",
       "사람2  160   65  40\n",
       "사람3  170   75  32\n",
       "사람4  175   80  33"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 예제를 위한 데이터 생성\n",
    "Data2 = DataFrame([[180,75,30],[160,65,40],[170,75,32], [175,80,33]], \n",
    "                  index = [\"사람1\",\"사람2\",\"사람3\",\"사람4\"], \n",
    "                  columns = [\"키\",\"몸무게\",\"나이\"])\n",
    "Data2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.1 Column 조회"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<strong><span style = \"color:red\">DataFrame명[\"속성명\"]</span></strong> 또는 <strong><span style = \"color:red\">DataFrame명.속성명</span></strong>을 통해 <strong><u>특정 속성명만 조회</u></strong> 할 수 있다.\n",
    "\n",
    "하나의 속성명을 조회 하면 SeriesType, 여러 속성명을 조회 하면 DataFrame으로 출력된다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "사람1    180\n",
       "사람2    160\n",
       "사람3    170\n",
       "사람4    175\n",
       "Name: 키, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 키 Column 만 조회\n",
    "Data2[\"키\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Type 은 Series\n",
    "type(Data2.몸무게)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게\n",
       "사람1  180   75\n",
       "사람2  160   65\n",
       "사람3  170   75\n",
       "사람4  175   80"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 두 개 이상 컬럼 조회\n",
    "Data2[[\"키\", \"몸무게\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.2 Index 조회"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ul>\n",
    "    <li><strong><span style = \"color:red\">DataFrame명.loc[\"index명\"]</span></strong> 을 통해 특정 index만 조회 가능하다.</li>\n",
    "    <li><strong><span style = \"color:red\">DataFrame명.iloc[index번호]</span></strong> 를 통해 특정 index만 조회 가능하다.</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "마찬가지로 하나의 index만 조회 할 경우 Series Type, 여러 index의 경우 DataFrame Type으로 출력한다.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "키      180\n",
       "몸무게     75\n",
       "나이      30\n",
       "Name: 사람1, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data2.loc[\"사람1\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "키      160\n",
       "몸무게     65\n",
       "나이      40\n",
       "Name: 사람2, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1번 인덱스 --> 사람2의 정보만 출력\n",
    "Data2.iloc[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게  나이\n",
       "사람1  180   75  30\n",
       "사람2  160   65  40"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 두 개 index를 index명으로 조회\n",
    "Data2.loc[[\"사람1\",\"사람2\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게  나이\n",
       "사람2  160   65  40\n",
       "사람3  170   75  32"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 여러 개의 index를 index번호로 조회\n",
    "Data2.iloc[1:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.3 Index 와 column 동시 조회"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "하나의 index 명과 컬럼명에 해당하는 하나의 값 찾기\n",
    "<ul>\n",
    "<li> DataFrame명.at[\"index명\",\"컬럼명\"]</li>\n",
    "<li> DataFrame명.loc[\"index명\",\"컬럼명\"]</li>\n",
    "<li> DataFrame명.loc[\"index명\"][\"컬럼명\"]</li>\n",
    "</ul>\n",
    "여러 index명과 컬럼명에 해당하는 여러 값 찾기\n",
    "<ul>\n",
    "<li> DataFrame명.loc[[\"index명1\",\"index명2\"],[\"컬럼명1\",\"컬럼명2\"]]</li>\n",
    "<li> DataFrame명.loc[[\"index명1\",\"index명2\"]][[\"컬럼명1\",\"컬럼명2\"]]</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#사람1의 나이 찾기\n",
    "Data2.loc[\"사람1\",\"나이\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#사람2의 몸무게 찾기\n",
    "Data2.loc[\"사람2\"][\"몸무게\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "170"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#사람3의 키 찾기\n",
    "Data2.at[\"사람3\",\"키\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "사람1    180\n",
       "사람2    160\n",
       "Name: 키, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 사람1, 사람2 의 키 조회\n",
    "Data2.loc[[\"사람1\",\"사람2\"]][\"키\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게\n",
       "사람1  180   75\n",
       "사람2  160   65"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 사람1,사람2 의 키와 몸무게 조회\n",
    "Data2.loc[[\"사람1\",\"사람2\"],[\"키\",\"몸무게\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "하나의 index 번호와 컬럼번호에 해당하는 하나의 값 찾기\n",
    "<ul>\n",
    "<li> DataFrame명.iat[index번호,컬럼번호]</li>\n",
    "<li> DataFrame명.iloc[index번호,컬럼번호]</li>\n",
    "<li> DataFrame명.iloc[index번호][컬럼번호]</li>\n",
    "</ul>\n",
    "여러 index 번호와 컬럼번호에 해당하는 여러 값 찾기\n",
    "<ul>\n",
    "<li> DataFrame명.iloc[index번호1:index번호2,컬럼번호1:컬럼명번호2]</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 사람1의 나이 찾기\n",
    "Data2.iloc[0,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#사람2의 몸무게 찾기\n",
    "Data2.iloc[1][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "170"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#사람3의 키 찾기\n",
    "Data2.iat[2,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "사람1    180\n",
       "사람2    160\n",
       "Name: 키, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 사람1, 사람2 의 키 조회\n",
    "Data2.iloc[0:2,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게\n",
       "사람1  180   75\n",
       "사람2  160   65"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 사람1,사람2 의 키와 몸무게 조회\n",
    "Data2.iloc[0:2,0:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.4 조건 조회"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게  나이\n",
       "사람1  180   75  30\n",
       "사람3  170   75  32\n",
       "사람4  175   80  33"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 키가 170 이상인 사람만 조회\n",
    "Data2[Data2[\"키\"] >= 170]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3.5 상위/하위 데이터 조회"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ul>\n",
    "<li>head(개수) : 위에서부터 개수만큼의 데이터만 출력</li>\n",
    "<li>tail(개수) : 밑에서부터 개수만큼의 데이터만 출력</li>\n",
    "</ul>\n",
    "개수를 쓰지 않을 경우 5개만 출력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람1</th>\n",
       "      <td>180</td>\n",
       "      <td>75</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람2</th>\n",
       "      <td>160</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게  나이\n",
       "사람1  180   75  30\n",
       "사람2  160   65  40"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data2.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>키</th>\n",
       "      <th>몸무게</th>\n",
       "      <th>나이</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>사람3</th>\n",
       "      <td>170</td>\n",
       "      <td>75</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사람4</th>\n",
       "      <td>175</td>\n",
       "      <td>80</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       키  몸무게  나이\n",
       "사람3  170   75  32\n",
       "사람4  175   80  33"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data2.tail(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "위의 Jupyter notebook 내용은 [여기](https://github.com/psyssai/PandasBasic/blob/master/PandasBasic_2_DataFrame.ipynb) Github에서도 확인 할 수 있습니다.  \n",
    "다음에는 Pandas의 두 번째 자료구조이자 가장 중요한 DataFrame에 대해 포스팅 할 예정입니다.\n",
    "\n",
    "감사합니다."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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