01_0_데이터_불러오기_수정.ipynb

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    "<a href=\"https://colab.research.google.com/github/ralbu85/DataScience_2022S/blob/master/01_%EB%8D%B0%EC%9D%B4%ED%84%B0_%EB%B6%88%EB%9F%AC%EC%98%A4%EA%B8%B0_%EC%88%98%EC%A0%95.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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  {
   "cell_type": "markdown",
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   "source": [
    "## pandas 모듈"
   ]
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   "execution_count": null,
   "metadata": {
    "id": "b9ROBO3Nj_i-"
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   "source": [
    "# 모듈 불러오기\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "yJC-L49HkerP"
   },
   "outputs": [],
   "source": [
    "# heart.csv 파일 불러오기\n",
    "df = pd.read_csv('heart.csv')"
   ]
  },
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       "\n",
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       "  </div>\n"
      ],
      "text/plain": [
       "     Age  Sex     ChestPain  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  \\\n",
       "0     63    1       typical     145   233    1        2    150      0   \n",
       "1     67    1  asymptomatic     160   286    0        2    108      1   \n",
       "2     67    1  asymptomatic     120   229    0        2    129      1   \n",
       "3     37    1    nonanginal     130   250    0        0    187      0   \n",
       "4     41    0    nontypical     130   204    0        2    172      0   \n",
       "..   ...  ...           ...     ...   ...  ...      ...    ...    ...   \n",
       "298   45    1       typical     110   264    0        0    132      0   \n",
       "299   68    1  asymptomatic     144   193    1        0    141      0   \n",
       "300   57    1  asymptomatic     130   131    0        0    115      1   \n",
       "301   57    0    nontypical     130   236    0        2    174      0   \n",
       "302   38    1    nonanginal     138   175    0        0    173      0   \n",
       "\n",
       "     Oldpeak  Slope   Ca        Thal  AHD  \n",
       "0        2.3      3  0.0       fixed   No  \n",
       "1        1.5      2  3.0      normal  Yes  \n",
       "2        2.6      2  2.0  reversable  Yes  \n",
       "3        3.5      3  0.0      normal   No  \n",
       "4        1.4      1  0.0      normal   No  \n",
       "..       ...    ...  ...         ...  ...  \n",
       "298      1.2      2  0.0  reversable  Yes  \n",
       "299      3.4      2  2.0  reversable  Yes  \n",
       "300      1.2      2  1.0  reversable  Yes  \n",
       "301      0.0      2  1.0      normal  Yes  \n",
       "302      0.0      1  NaN      normal   No  \n",
       "\n",
       "[303 rows x 14 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 226
    },
    "id": "n8Ss_W27mOpO",
    "outputId": "d8f146f9-0372-41a4-d98d-c5103b3e3405"
   },
   "outputs": [
    {
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       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-bfd58482-ed83-4d11-a635-cfff96f2c1f1 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "     Age  Sex     ChestPain  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  \\\n",
       "298   45    1       typical     110   264    0        0    132      0   \n",
       "299   68    1  asymptomatic     144   193    1        0    141      0   \n",
       "300   57    1  asymptomatic     130   131    0        0    115      1   \n",
       "301   57    0    nontypical     130   236    0        2    174      0   \n",
       "302   38    1    nonanginal     138   175    0        0    173      0   \n",
       "\n",
       "     Oldpeak  Slope   Ca        Thal  AHD  \n",
       "298      1.2      2  0.0  reversable  Yes  \n",
       "299      3.4      2  2.0  reversable  Yes  \n",
       "300      1.2      2  1.0  reversable  Yes  \n",
       "301      0.0      2  1.0      normal  Yes  \n",
       "302      0.0      1  NaN      normal   No  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "B0PRnk8znB76"
   },
   "source": [
    "## 3. 열의 선택"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "rNcCp4jMmOqd",
    "outputId": "069504b1-b714-4554-d0c6-287b80dd531a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      63\n",
       "1      67\n",
       "2      67\n",
       "3      37\n",
       "4      41\n",
       "       ..\n",
       "298    45\n",
       "299    68\n",
       "300    57\n",
       "301    57\n",
       "302    38\n",
       "Name: Age, Length: 303, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age'] # Age 변수 선택"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 423
    },
    "id": "BLDW30Aenf0l",
    "outputId": "058a5b79-6ca8-4870-cf02-210016b6954f"
   },
   "outputs": [
    {
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       "type": "dataframe"
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       "\n",
       "  <div id=\"df-cacd63cb-f732-4d98-bffa-d8d2b37db08a\" class=\"colab-df-container\">\n",
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       "<p>303 rows × 2 columns</p>\n",
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       "\n",
       "    .colab-df-convert {\n",
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       "\n",
       "    .colab-df-convert:hover {\n",
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       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
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       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
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       "  </style>\n",
       "\n",
       "    <script>\n",
       "      const buttonEl =\n",
       "        document.querySelector('#df-cacd63cb-f732-4d98-bffa-d8d2b37db08a button.colab-df-convert');\n",
       "      buttonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "      async function convertToInteractive(key) {\n",
       "        const element = document.querySelector('#df-cacd63cb-f732-4d98-bffa-d8d2b37db08a');\n",
       "        const dataTable =\n",
       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                    [key], {});\n",
       "        if (!dataTable) return;\n",
       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
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       "        docLink.innerHTML = docLinkHtml;\n",
       "        element.appendChild(docLink);\n",
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       "\n",
       "\n",
       "<div id=\"df-a3ce1dcb-3d2b-4e7e-819f-d4b55837f183\">\n",
       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a3ce1dcb-3d2b-4e7e-819f-d4b55837f183')\"\n",
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       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
       "      --disabled-bg-color: #DDD;\n",
       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
       "      --fill-color: #D2E3FC;\n",
       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
       "    background-color: var(--bg-color);\n",
       "    border: none;\n",
       "    border-radius: 50%;\n",
       "    cursor: pointer;\n",
       "    display: none;\n",
       "    fill: var(--fill-color);\n",
       "    height: 32px;\n",
       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
       "    background-color: var(--hover-bg-color);\n",
       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "    fill: var(--button-hover-fill-color);\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-a3ce1dcb-3d2b-4e7e-819f-d4b55837f183 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "     Age  AHD\n",
       "0     63   No\n",
       "1     67  Yes\n",
       "2     67  Yes\n",
       "3     37   No\n",
       "4     41   No\n",
       "..   ...  ...\n",
       "298   45  Yes\n",
       "299   68  Yes\n",
       "300   57  Yes\n",
       "301   57  Yes\n",
       "302   38   No\n",
       "\n",
       "[303 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Age와 AHD 두개를 선택할때\n",
    "# 2개 이상을 고를때는 칼럼명으로 구성된 리스트를 넣어준다.\n",
    "df[['Age','AHD']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KNqTI-CXoX6M"
   },
   "source": [
    "## 행선택"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9hYCjSoLoZsL",
    "outputId": "24908dd0-e214-43b8-e69b-52bef021952d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age               63\n",
       "Sex                1\n",
       "ChestPain    typical\n",
       "RestBP           145\n",
       "Chol             233\n",
       "Fbs                1\n",
       "RestECG            2\n",
       "MaxHR            150\n",
       "ExAng              0\n",
       "Oldpeak          2.3\n",
       "Slope              3\n",
       "Ca               0.0\n",
       "Thal           fixed\n",
       "AHD               No\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 163
    },
    "id": "Eaw7E6kpoz1f",
    "outputId": "4b5314c4-add0-4291-81a4-ea1ce6fa6969"
   },
   "outputs": [
    {
     "data": {
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       "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15,\n        \"min\": 37,\n        \"max\": 67,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          67,\n          37,\n          56\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sex\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ChestPain\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"asymptomatic\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RestBP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 20,\n        \"min\": 120,\n        \"max\": 160,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          160\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25,\n        \"min\": 236,\n        \"max\": 286,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          286\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Fbs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RestECG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 2,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"MaxHR\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 43,\n        \"min\": 108,\n        \"max\": 187,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          108\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ExAng\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4011899704655801,\n        \"min\": 0.8,\n        \"max\": 3.5,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Slope\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.7320508075688772,\n        \"min\": 0.0,\n        \"max\": 3.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Thal\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"normal\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AHD\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"No\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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       "        document.querySelector('#df-0149331a-c59e-4b9f-8d18-b8125a1a8815 button.colab-df-convert');\n",
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       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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       "          + ' to learn more about interactive tables.';\n",
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       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
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       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
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       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
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       "    border-radius: 50%;\n",
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       "    width: 32px;\n",
       "  }\n",
       "\n",
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       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
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       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
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       "    30% {\n",
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       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-b85a579e-9d60-4f1d-b64e-b07c990e858e button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "   Age  Sex     ChestPain  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  Oldpeak  \\\n",
       "1   67    1  asymptomatic     160   286    0        2    108      1      1.5   \n",
       "3   37    1    nonanginal     130   250    0        0    187      0      3.5   \n",
       "5   56    1    nontypical     120   236    0        0    178      0      0.8   \n",
       "\n",
       "   Slope   Ca    Thal  AHD  \n",
       "1      2  3.0  normal  Yes  \n",
       "3      3  0.0  normal   No  \n",
       "5      1  0.0  normal   No  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 여러행 동시에 선택\n",
    "df.loc[[1,3,5]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0K2-wWf8pKx8"
   },
   "source": [
    "## 모든열 살펴보기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "FvzgMiwQpMqr"
   },
   "outputs": [],
   "source": [
    "columns = df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "k9YT12-Opqu5",
    "outputId": "f9088ad2-fbdc-451e-cae3-bbebf459bc5e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      63\n",
       "1      67\n",
       "2      67\n",
       "3      37\n",
       "4      41\n",
       "       ..\n",
       "298    45\n",
       "299    68\n",
       "300    57\n",
       "301    57\n",
       "302    38\n",
       "Name: Age, Length: 303, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[columns[0]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6Wg7QJ1-sGY9"
   },
   "source": [
    "## 통계량 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 320
    },
    "id": "RdxxtJekre-h",
    "outputId": "a044ed44-d1f5-4c78-d453-43f9b176e0bb"
   },
   "outputs": [
    {
     "data": {
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       "      <th>Age</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>303.000000</td>\n",
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       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
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       "      <td>303.000000</td>\n",
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       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>299.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>54.438944</td>\n",
       "      <td>0.679868</td>\n",
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       "      <td>0.326733</td>\n",
       "      <td>1.039604</td>\n",
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       "      <td>0.672241</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.038662</td>\n",
       "      <td>0.467299</td>\n",
       "      <td>17.599748</td>\n",
       "      <td>51.776918</td>\n",
       "      <td>0.356198</td>\n",
       "      <td>0.994971</td>\n",
       "      <td>22.875003</td>\n",
       "      <td>0.469794</td>\n",
       "      <td>1.161075</td>\n",
       "      <td>0.616226</td>\n",
       "      <td>0.937438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>48.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>133.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>56.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>241.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>275.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
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       "      <td>1.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>564.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
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       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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       "          + ' to learn more about interactive tables.';\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
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       "    20% {\n",
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       "      border-left-color: var(--fill-color);\n",
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       "      border-right-color: var(--fill-color);\n",
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       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
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       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
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       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
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       "        console.error('Error during call to suggestCharts:', error);\n",
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       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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       "\n",
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      ],
      "text/plain": [
       "              Age         Sex      RestBP        Chol         Fbs     RestECG  \\\n",
       "count  303.000000  303.000000  303.000000  303.000000  303.000000  303.000000   \n",
       "mean    54.438944    0.679868  131.689769  246.693069    0.148515    0.990099   \n",
       "std      9.038662    0.467299   17.599748   51.776918    0.356198    0.994971   \n",
       "min     29.000000    0.000000   94.000000  126.000000    0.000000    0.000000   \n",
       "25%     48.000000    0.000000  120.000000  211.000000    0.000000    0.000000   \n",
       "50%     56.000000    1.000000  130.000000  241.000000    0.000000    1.000000   \n",
       "75%     61.000000    1.000000  140.000000  275.000000    0.000000    2.000000   \n",
       "max     77.000000    1.000000  200.000000  564.000000    1.000000    2.000000   \n",
       "\n",
       "            MaxHR       ExAng     Oldpeak       Slope          Ca  \n",
       "count  303.000000  303.000000  303.000000  303.000000  299.000000  \n",
       "mean   149.607261    0.326733    1.039604    1.600660    0.672241  \n",
       "std     22.875003    0.469794    1.161075    0.616226    0.937438  \n",
       "min     71.000000    0.000000    0.000000    1.000000    0.000000  \n",
       "25%    133.500000    0.000000    0.000000    1.000000    0.000000  \n",
       "50%    153.000000    0.000000    0.800000    2.000000    0.000000  \n",
       "75%    166.000000    1.000000    1.600000    2.000000    1.000000  \n",
       "max    202.000000    1.000000    6.200000    3.000000    3.000000  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gXE1vBWy6gd1"
   },
   "source": [
    "## 범주형 데이터 살펴보기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 226
    },
    "id": "X1bIE-03uk56",
    "outputId": "6453a5ee-5b07-44a3-c791-52ee312f7c94"
   },
   "outputs": [
    {
     "data": {
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       "type": "dataframe",
       "variable_name": "df"
      },
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       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>typical</td>\n",
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       "      <td>120</td>\n",
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       "      <td>2</td>\n",
       "      <td>129</td>\n",
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       "      <td>2.6</td>\n",
       "      <td>2</td>\n",
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       "      <td>reversable</td>\n",
       "      <td>Yes</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>nonanginal</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>No</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>nontypical</td>\n",
       "      <td>130</td>\n",
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       "      <td>0</td>\n",
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       "      <td>172</td>\n",
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       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
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       "\n",
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       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
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       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
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       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
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       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
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       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-4a07ff1e-f443-4c9e-801b-992ead8ac716 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "   Age  Sex     ChestPain  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  Oldpeak  \\\n",
       "0   63    1       typical     145   233    1        2    150      0      2.3   \n",
       "1   67    1  asymptomatic     160   286    0        2    108      1      1.5   \n",
       "2   67    1  asymptomatic     120   229    0        2    129      1      2.6   \n",
       "3   37    1    nonanginal     130   250    0        0    187      0      3.5   \n",
       "4   41    0    nontypical     130   204    0        2    172      0      1.4   \n",
       "\n",
       "   Slope   Ca        Thal  AHD  \n",
       "0      3  0.0       fixed   No  \n",
       "1      2  3.0      normal  Yes  \n",
       "2      2  2.0  reversable  Yes  \n",
       "3      3  0.0      normal   No  \n",
       "4      1  0.0      normal   No  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 범주형 값의 경우, 고유값 확인\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 연습문제: 모든 칼럼에 대하여 위 작업을 수행해 보고, 어떤 칼럼이 범주형 값인지 살펴보시오"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Auto Dataset을 불러와서, 위에서 수행한 작업을 연습해보시오"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "6GO6V6T5urUp",
    "outputId": "fd2ffd45-14ef-403f-d6da-815c040351ef"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['typical', 'asymptomatic', 'nonanginal', 'nontypical'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['ChestPain'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "3Zx3IB9UurC6",
    "outputId": "9983c7f4-2907-4d5b-d64f-963d49e4971d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['fixed', 'normal', 'reversable', nan], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Thal'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "bBoCiK28vl_o",
    "outputId": "9ddf5b0d-8a5e-425e-fcbb-3d00a54f4ba6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['No', 'Yes'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['AHD'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "D_sVQmrcv15C",
    "outputId": "ef1b5081-c5bb-4d44-db83-516b11465eec"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
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   ],
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    "df['Fbs'].unique()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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    "outputId": "2106ed6b-b349-4886-e932-0c2dc4a64981"
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    {
     "data": {
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       "array([2, 0, 1])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['RestECG'].unique()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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    "outputId": "fca7c76b-01f3-4992-e36b-3665a56a9442"
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   "outputs": [
    {
     "data": {
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      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
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    "df['ExAng'].unique()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
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    "id": "oqL8jKfHwHeS",
    "outputId": "406326b8-4412-49e0-9dd5-1cbf73065565"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 2, 1])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Slope'].unique()"
   ]
  }
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