Section1_PJ1_정지현_최종55.ipynb

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    {
      "cell_type": "markdown",
      "source": [
        "# **다음 분기에 어떤 게임을 설계해야 할까**"
      ],
      "metadata": {
        "id": "wRc_CDIz4q6I"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **0. Data Description** ##"
      ],
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        "id": "jBEY7DVh4vO1"
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      "cell_type": "markdown",
      "source": [
        "- `Name` : 게임의 이름\n",
        "\n",
        "- `Platform` : 게임이 지원되는 플랫폼의 이름\n",
        "\n",
        "- `Year` : 게임이 출시된 연도\n",
        "\n",
        "- `Genre` : 게임의 장르\n",
        "\n",
        "- `Publisher` : 게임을 배급한 회사\n",
        "\n",
        "- `NA_Sales` : 북미지역에서의 출고량\n",
        "\n",
        "- `EU_Sales` : 유럽지역에서의 출고량\n",
        "\n",
        "- `JP_Sales` : 일본지역에서의 출고량\n",
        "\n",
        "- `Other_Sales` : 기타지역에서의 출고량"
      ],
      "metadata": {
        "id": "lcWyrvOv4xK6"
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    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "df = pd.read_csv('https://ds-lecture-data.s3.ap-northeast-2.amazonaws.com/datasets/vgames2.csv')\n",
        "df"
      ],
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              "       Unnamed: 0                                            Name Platform  \\\n",
              "0               1                    Candace Kane's Candy Factory       DS   \n",
              "1               2                                  The Munchables      Wii   \n",
              "2               3  Otome wa Oanesama Boku ni Koi Shiteru Portable      PSP   \n",
              "3               4                Deal or No Deal: Special Edition       DS   \n",
              "4               5       Ben 10 Ultimate Alien: Cosmic Destruction      PS3   \n",
              "...           ...                                             ...      ...   \n",
              "16593       16594                         Ice Age 2: The Meltdown       GC   \n",
              "16594       16595                     Rainbow Islands: Revolution      PSP   \n",
              "16595       16596                                        NBA 2K16      PS3   \n",
              "16596       16597                     Toukiden: The Age of Demons      PSV   \n",
              "16597       16598                        The King of Fighters '95       PS   \n",
              "\n",
              "         Year      Genre                    Publisher NA_Sales EU_Sales  \\\n",
              "0      2008.0     Action                    Destineer     0.04        0   \n",
              "1      2009.0     Action           Namco Bandai Games     0.17        0   \n",
              "2      2010.0  Adventure                    Alchemist        0        0   \n",
              "3      2010.0       Misc                    Zoo Games     0.04        0   \n",
              "4      2010.0   Platform                  D3Publisher     0.12     0.09   \n",
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              "16593  2006.0   Platform                Vivendi Games     0.15     0.04   \n",
              "16594  2005.0     Action            Rising Star Games     0.01        0   \n",
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              "16597  1996.0   Fighting  Sony Computer Entertainment        0        0   \n",
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              "0            0           0  \n",
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              "4            0        0.04  \n",
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              "16593        0        0.01  \n",
              "16594        0           0  \n",
              "16595     0.03        0.13  \n",
              "16596     0.25        0.03  \n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **1.EDA 진행** ##"
      ],
      "metadata": {
        "id": "l5vyJvqI47qh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 0) 원본데이터 저장 ###"
      ],
      "metadata": {
        "id": "IEg3fpa06NQ8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_original = df.copy()"
      ],
      "metadata": {
        "id": "CqY8QTnI6E1y"
      },
      "execution_count": 311,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 1) 필요 없는 열 제거 ###"
      ],
      "metadata": {
        "id": "ttuR8SKaRR26"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# [Unnamed: 0], [Platform] 정보 X → 열 제거 \n",
        "df = df.drop(['Unnamed: 0'], axis=1)\n",
        "df = df.drop(['Platform'], axis=1)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "7f-tAhMn4-_c",
        "outputId": "aee9974f-a382-49c3-b061-c6240a980030"
      },
      "execution_count": 312,
      "outputs": [
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          "data": {
            "text/plain": [
              "                                             Name    Year      Genre  \\\n",
              "0                    Candace Kane's Candy Factory  2008.0     Action   \n",
              "1                                  The Munchables  2009.0     Action   \n",
              "2  Otome wa Oanesama Boku ni Koi Shiteru Portable  2010.0  Adventure   \n",
              "3                Deal or No Deal: Special Edition  2010.0       Misc   \n",
              "4       Ben 10 Ultimate Alien: Cosmic Destruction  2010.0   Platform   \n",
              "\n",
              "            Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0           Destineer     0.04        0        0           0  \n",
              "1  Namco Bandai Games     0.17        0        0        0.01  \n",
              "2           Alchemist        0        0     0.02           0  \n",
              "3           Zoo Games     0.04        0        0           0  \n",
              "4         D3Publisher     0.12     0.09        0        0.04  "
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              "      <td>0.04</td>\n",
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              "      <td>0.12</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8886bfa9-d333-4e1b-a18b-75f620dc5f7e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      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",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8886bfa9-d333-4e1b-a18b-75f620dc5f7e 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-8886bfa9-d333-4e1b-a18b-75f620dc5f7e');\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",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 312
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2) 중복 데이터 제거 ###"
      ],
      "metadata": {
        "id": "dWdhOKqqRdTC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 중복된 데이터 개수 확인\n",
        "df.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-oRo_Jqy5Atc",
        "outputId": "76eda65f-e8f2-4b4f-befa-258eb8c589d4"
      },
      "execution_count": 313,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "70"
            ]
          },
          "metadata": {},
          "execution_count": 313
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 중복된 데이터 제거\n",
        "df = df.drop_duplicates().reset_index(drop=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "VvcDQAgH5CEU",
        "outputId": "a06bfcdc-7c1f-46c2-868d-8ad0dc1345f4"
      },
      "execution_count": 314,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name    Year      Genre  \\\n",
              "0                        Candace Kane's Candy Factory  2008.0     Action   \n",
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              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010.0  Adventure   \n",
              "3                    Deal or No Deal: Special Edition  2010.0       Misc   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction  2010.0   Platform   \n",
              "...                                               ...     ...        ...   \n",
              "16523                         Ice Age 2: The Meltdown  2006.0   Platform   \n",
              "16524                     Rainbow Islands: Revolution  2005.0     Action   \n",
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              "16526                     Toukiden: The Age of Demons  2013.0     Action   \n",
              "16527                        The King of Fighters '95  1996.0   Fighting   \n",
              "\n",
              "                         Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0                        Destineer     0.04        0        0           0  \n",
              "1               Namco Bandai Games     0.17        0        0        0.01  \n",
              "2                        Alchemist        0        0     0.02           0  \n",
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              "4                      D3Publisher     0.12     0.09        0        0.04  \n",
              "...                            ...      ...      ...      ...         ...  \n",
              "16523                Vivendi Games     0.15     0.04        0        0.01  \n",
              "16524            Rising Star Games     0.01        0        0           0  \n",
              "16525         Take-Two Interactive     0.44     0.19     0.03        0.13  \n",
              "16526                   Tecmo Koei     0.05     0.05     0.25        0.03  \n",
              "16527  Sony Computer Entertainment        0        0     0.16        0.01  \n",
              "\n",
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              "      <td>Rainbow Islands: Revolution</td>\n",
              "      <td>2005.0</td>\n",
              "      <td>Action</td>\n",
              "      <td>Rising Star Games</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0.44</td>\n",
              "      <td>0.19</td>\n",
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              "      <th>16526</th>\n",
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              "      <td>Fighting</td>\n",
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              "<p>16528 rows × 8 columns</p>\n",
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              "          document.querySelector('#df-8ac5b127-3bee-4e2e-849b-2e6cfe662b6e button.colab-df-convert');\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8ac5b127-3bee-4e2e-849b-2e6cfe662b6e');\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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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 314
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3) 결측치 제거 ###"
      ],
      "metadata": {
        "id": "2_cvAn45Rj3L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 결측치 확인\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mp0DxWW96yaA",
        "outputId": "c87c86aa-5847-4681-f68e-4de819b2f03f"
      },
      "execution_count": 315,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name             0\n",
              "Year           268\n",
              "Genre           50\n",
              "Publisher       58\n",
              "NA_Sales         0\n",
              "EU_Sales         0\n",
              "JP_Sales         0\n",
              "Other_Sales      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 315
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 결측치 제거\n",
        "df = df.dropna().reset_index(drop=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "AhQeJzT07PP5",
        "outputId": "ceebb296-4aad-472f-f995-f5f039026af2"
      },
      "execution_count": 316,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                                                 Name    Year      Genre  \\\n",
              "0                        Candace Kane's Candy Factory  2008.0     Action   \n",
              "1                                      The Munchables  2009.0     Action   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010.0  Adventure   \n",
              "3                    Deal or No Deal: Special Edition  2010.0       Misc   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction  2010.0   Platform   \n",
              "...                                               ...     ...        ...   \n",
              "16169                         Ice Age 2: The Meltdown  2006.0   Platform   \n",
              "16170                     Rainbow Islands: Revolution  2005.0     Action   \n",
              "16171                                        NBA 2K16  2015.0     Sports   \n",
              "16172                     Toukiden: The Age of Demons  2013.0     Action   \n",
              "16173                        The King of Fighters '95  1996.0   Fighting   \n",
              "\n",
              "                         Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0                        Destineer     0.04        0        0           0  \n",
              "1               Namco Bandai Games     0.17        0        0        0.01  \n",
              "2                        Alchemist        0        0     0.02           0  \n",
              "3                        Zoo Games     0.04        0        0           0  \n",
              "4                      D3Publisher     0.12     0.09        0        0.04  \n",
              "...                            ...      ...      ...      ...         ...  \n",
              "16169                Vivendi Games     0.15     0.04        0        0.01  \n",
              "16170            Rising Star Games     0.01        0        0           0  \n",
              "16171         Take-Two Interactive     0.44     0.19     0.03        0.13  \n",
              "16172                   Tecmo Koei     0.05     0.05     0.25        0.03  \n",
              "16173  Sony Computer Entertainment        0        0     0.16        0.01  \n",
              "\n",
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              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Year</th>\n",
              "      <th>Genre</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>NA_Sales</th>\n",
              "      <th>EU_Sales</th>\n",
              "      <th>JP_Sales</th>\n",
              "      <th>Other_Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Candace Kane's Candy Factory</td>\n",
              "      <td>2008.0</td>\n",
              "      <td>Action</td>\n",
              "      <td>Destineer</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The Munchables</td>\n",
              "      <td>2009.0</td>\n",
              "      <td>Action</td>\n",
              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Otome wa Oanesama Boku ni Koi Shiteru Portable</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Alchemist</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Deal or No Deal: Special Edition</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Zoo Games</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Ben 10 Ultimate Alien: Cosmic Destruction</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>Platform</td>\n",
              "      <td>D3Publisher</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0</td>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16169</th>\n",
              "      <td>Ice Age 2: The Meltdown</td>\n",
              "      <td>2006.0</td>\n",
              "      <td>Platform</td>\n",
              "      <td>Vivendi Games</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16170</th>\n",
              "      <td>Rainbow Islands: Revolution</td>\n",
              "      <td>2005.0</td>\n",
              "      <td>Action</td>\n",
              "      <td>Rising Star Games</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16171</th>\n",
              "      <td>NBA 2K16</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Take-Two Interactive</td>\n",
              "      <td>0.44</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16172</th>\n",
              "      <td>Toukiden: The Age of Demons</td>\n",
              "      <td>2013.0</td>\n",
              "      <td>Action</td>\n",
              "      <td>Tecmo Koei</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16173</th>\n",
              "      <td>The King of Fighters '95</td>\n",
              "      <td>1996.0</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>Sony Computer Entertainment</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16174 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3f841461-e90a-41cb-9487-5fc3bb302c56')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      fill: #1967D2;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-3f841461-e90a-41cb-9487-5fc3bb302c56 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-3f841461-e90a-41cb-9487-5fc3bb302c56');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 316
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 4) 출시연도 column ###"
      ],
      "metadata": {
        "id": "AFAxKJsnSwER"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 출시연도에 이상치가 있는지 확인\n",
        "df['Year'].sort_values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vA3EUiLs6UCo",
        "outputId": "6b00a7b5-04bf-4eb6-dec0-d59e49faee20"
      },
      "execution_count": 317,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "15976       0.0\n",
              "9068        0.0\n",
              "14294       0.0\n",
              "2204        1.0\n",
              "8485        1.0\n",
              "          ...  \n",
              "9326     2016.0\n",
              "14844    2017.0\n",
              "9881     2017.0\n",
              "5191     2017.0\n",
              "6755     2020.0\n",
              "Name: Year, Length: 16174, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 317
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "error_year = df[df['Year'] < 1000]\n",
        "error_year"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "DzQrYmFTdEvr",
        "outputId": "ecd1206d-afc6-438e-f1bb-7aab681225a8"
      },
      "execution_count": 318,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                               Name  Year     Genre  \\\n",
              "72          Age of Empires III: Complete Collection   9.0  Strategy   \n",
              "79                            Treasures of the Deep  97.0    Action   \n",
              "210                                NASCAR Unleashed  11.0    Racing   \n",
              "299    Kung Fu Panda: Showdown of Legendary Legends  15.0    Action   \n",
              "757                             NASCAR Thunder 2004   3.0    Racing   \n",
              "...                                             ...   ...       ...   \n",
              "15578                                Sugoi Hebereke  94.0  Fighting   \n",
              "15692                                  Fab 5 Soccer   8.0    Sports   \n",
              "15736                    Dragon Ball Z: Burst Limit   8.0  Fighting   \n",
              "15976                                 Point Blank 3   0.0   Shooter   \n",
              "16061              Super Robot Taisen F Kanketsuhen  98.0  Strategy   \n",
              "\n",
              "                    Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "72     Microsoft Game Studios     0.01     0.12        0        0.03  \n",
              "79         Namco Bandai Games      0.1     0.07        0        0.01  \n",
              "210                Activision     0.09        0        0        0.01  \n",
              "299              Little Orbit        0     0.02        0           0  \n",
              "757           Electronic Arts     0.53     0.41        0        0.14  \n",
              "...                       ...      ...      ...      ...         ...  \n",
              "15578                 Sunsoft        0        0     0.02           0  \n",
              "15692               Destineer     0.01        0        0           0  \n",
              "15736                   Atari     0.24     0.18     0.03        0.05  \n",
              "15976      Namco Bandai Games     0.01     0.01        0           0  \n",
              "16061               Banpresto       0M        0     0.55           0  \n",
              "\n",
              "[100 rows x 8 columns]"
            ],
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              "      <th>72</th>\n",
              "      <td>Age of Empires III: Complete Collection</td>\n",
              "      <td>9.0</td>\n",
              "      <td>Strategy</td>\n",
              "      <td>Microsoft Game Studios</td>\n",
              "      <td>0.01</td>\n",
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              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>Treasures of the Deep</td>\n",
              "      <td>97.0</td>\n",
              "      <td>Action</td>\n",
              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.1</td>\n",
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              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>NASCAR Unleashed</td>\n",
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              "      <th>299</th>\n",
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              "      <th>757</th>\n",
              "      <td>NASCAR Thunder 2004</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Racing</td>\n",
              "      <td>Electronic Arts</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>15578</th>\n",
              "      <td>Sugoi Hebereke</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>15692</th>\n",
              "      <td>Fab 5 Soccer</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Destineer</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15736</th>\n",
              "      <td>Dragon Ball Z: Burst Limit</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>Atari</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.05</td>\n",
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              "    <tr>\n",
              "      <th>15976</th>\n",
              "      <td>Point Blank 3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Shooter</td>\n",
              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>16061</th>\n",
              "      <td>Super Robot Taisen F Kanketsuhen</td>\n",
              "      <td>98.0</td>\n",
              "      <td>Strategy</td>\n",
              "      <td>Banpresto</td>\n",
              "      <td>0M</td>\n",
              "      <td>0</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>100 rows × 8 columns</p>\n",
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              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0c21f701-1c64-4013-9656-131e0c50e31c');\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",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 318
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 비정상적인 연도 삭제\n",
        "df = df.drop(error_year.index).reset_index(drop=True)\n",
        "df['Year'].sort_values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6EJD1frQdSn0",
        "outputId": "d4c95c14-42eb-4125-c29c-9ab1687fff6d"
      },
      "execution_count": 319,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8960     1980.0\n",
              "5563     1980.0\n",
              "5776     1980.0\n",
              "13819    1980.0\n",
              "12732    1980.0\n",
              "          ...  \n",
              "14031    2016.0\n",
              "9818     2017.0\n",
              "5158     2017.0\n",
              "14758    2017.0\n",
              "6715     2020.0\n",
              "Name: Year, Length: 16074, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 319
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터셋의 정보 확인\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OYZpNZqT49TB",
        "outputId": "6bef2b04-c77f-403b-b2d8-29ce5e95bc80"
      },
      "execution_count": 320,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 16074 entries, 0 to 16073\n",
            "Data columns (total 8 columns):\n",
            " #   Column       Non-Null Count  Dtype  \n",
            "---  ------       --------------  -----  \n",
            " 0   Name         16074 non-null  object \n",
            " 1   Year         16074 non-null  float64\n",
            " 2   Genre        16074 non-null  object \n",
            " 3   Publisher    16074 non-null  object \n",
            " 4   NA_Sales     16074 non-null  object \n",
            " 5   EU_Sales     16074 non-null  object \n",
            " 6   JP_Sales     16074 non-null  object \n",
            " 7   Other_Sales  16074 non-null  object \n",
            "dtypes: float64(1), object(7)\n",
            "memory usage: 1004.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 출시연도의 데이터타입을 int로 변환\n",
        "df = df.astype({'Year': 'int'})\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "35gezeTH55Dk",
        "outputId": "0508ea5a-7daa-458a-f50c-48814c916dbc"
      },
      "execution_count": 321,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 16074 entries, 0 to 16073\n",
            "Data columns (total 8 columns):\n",
            " #   Column       Non-Null Count  Dtype \n",
            "---  ------       --------------  ----- \n",
            " 0   Name         16074 non-null  object\n",
            " 1   Year         16074 non-null  int64 \n",
            " 2   Genre        16074 non-null  object\n",
            " 3   Publisher    16074 non-null  object\n",
            " 4   NA_Sales     16074 non-null  object\n",
            " 5   EU_Sales     16074 non-null  object\n",
            " 6   JP_Sales     16074 non-null  object\n",
            " 7   Other_Sales  16074 non-null  object\n",
            "dtypes: int64(1), object(7)\n",
            "memory usage: 1004.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 5) 각 나라별 출고량 column ###"
      ],
      "metadata": {
        "id": "Rt-igL0qLR64"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### NA (북미지역) ####"
      ],
      "metadata": {
        "id": "t8VeJby6FIsX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 북미지역에서의 출고량 컬럼을 기준으로 오름차순 정렬\n",
        "df['NA_Sales'].sort_values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hNoJ9QMSFvVe",
        "outputId": "69bc31c7-7bb6-4f6f-acca-867988bf67a1"
      },
      "execution_count": 322,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16073       0\n",
              "3740        0\n",
              "3739        0\n",
              "10032       0\n",
              "10033       0\n",
              "         ... \n",
              "6073     9.67\n",
              "10338    9.81\n",
              "13900     90K\n",
              "13372     90K\n",
              "12657     90K\n",
              "Name: NA_Sales, Length: 16074, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 322
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 북미지역에서의 출고량 데이터 중 문자를 포함하는 열\n",
        "df[df['NA_Sales'].str.contains('[a-zA-Z]')].shape[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DtfMme5AOxfr",
        "outputId": "1eb77b9e-609e-4b09-8a06-3a4f0ec661f6"
      },
      "execution_count": 323,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "188"
            ]
          },
          "metadata": {},
          "execution_count": 323
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 북미지역에서의 출고량 데이터 중 K와 M을 포함하는 열\n",
        "df[df['NA_Sales'].str.contains('K')].shape[0] + df[df['NA_Sales'].str.contains('M')].shape[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S6xt66uSvUIk",
        "outputId": "049a345b-08e3-4306-c2ca-1e50a40ed0fa"
      },
      "execution_count": 324,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "188"
            ]
          },
          "metadata": {},
          "execution_count": 324
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# K를 포함하는 데이터를 빼서 0.001을 곱해준다.\n",
        "error_na_k = df[df['NA_Sales'].str.contains('K')]\n",
        "error_na_k['NA_Sales'] = error_na_k['NA_Sales'].str.replace('K', '').astype('float')*0.001\n",
        "error_na_k"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "OtXh_Dquv_Bi",
        "outputId": "d5e4bb17-2eec-4f43-9bbe-6222c01348e3"
      },
      "execution_count": 325,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-325-1dccefebdd17>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_na_k['NA_Sales'] = error_na_k['NA_Sales'].str.replace('K', '').astype('float')*0.001\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name  Year     Genre  \\\n",
              "10                                        Ford Racing  2001    Racing   \n",
              "44                       Resident Evil: Revelations 2  2015    Action   \n",
              "140                                TOCA Race Driver 3  2006    Racing   \n",
              "860    Tears to Tiara Anecdotes: The Secret of Avalon  2009  Strategy   \n",
              "1062                        Pro Evolution Soccer 2014  2013    Action   \n",
              "...                                               ...   ...       ...   \n",
              "15154                       Championship Manager 2010  2009    Sports   \n",
              "15683                            Vin Diesel: Wheelman  2009    Racing   \n",
              "15815                         Midway Arcade Treasures  2003      Misc   \n",
              "15971                                   Mortal Kombat  2012  Fighting   \n",
              "16055                            Gex: Enter the Gecko  1998  Platform   \n",
              "\n",
              "                                    Publisher  NA_Sales EU_Sales JP_Sales  \\\n",
              "10                         Empire Interactive      0.48    0.33M       0K   \n",
              "44                                     Capcom      0.06     0.08     0.16   \n",
              "140                               Codemasters      0.00     0.02        0   \n",
              "860                                 Aqua Plus      0.00        0     0.04   \n",
              "1062             Konami Digital Entertainment      0.00        0     0.19   \n",
              "...                                       ...       ...      ...      ...   \n",
              "15154                       Eidos Interactive      0.00     0.01        0   \n",
              "15683                                 Ubisoft      0.12     0.15        0   \n",
              "15815                            Midway Games      0.72     0.56        0   \n",
              "15971  Warner Bros. Interactive Entertainment      0.47     0.18        0   \n",
              "16055           BMG Interactive Entertainment      0.32     0.22        0   \n",
              "\n",
              "      Other_Sales  \n",
              "10           0.06  \n",
              "44           0.03  \n",
              "140             0  \n",
              "860             0  \n",
              "1062            0  \n",
              "...           ...  \n",
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              "15683        0.06  \n",
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          },
          "metadata": {},
          "execution_count": 325
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# M를 포함하는 데이터를 빼서 단위만 없애준다.\n",
        "error_na_m = df[df['NA_Sales'].str.contains('M')]\n",
        "error_na_m['NA_Sales'] = error_na_m['NA_Sales'].str.replace('M', '').astype('float')\n",
        "error_na_m"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "1V32sjGGwe61",
        "outputId": "56e677bc-0189-47f0-e38f-9f94c86f79a9"
      },
      "execution_count": 326,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-326-ed6d4abb0906>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_na_m['NA_Sales'] = error_na_m['NA_Sales'].str.replace('M', '').astype('float')\n"
          ]
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              "                                             Name  Year     Genre  \\\n",
              "435                    Medal of Honor: Warfighter  2012    Action   \n",
              "446                                       F1 2010  2010    Racing   \n",
              "563                                 Mario Kart 64  1996    Racing   \n",
              "611                                    The Hobbit  2003  Platform   \n",
              "658    Star Wars The Clone Wars: Lightsaber Duels  2008    Action   \n",
              "...                                           ...   ...       ...   \n",
              "15212                                      Driven  2001    Racing   \n",
              "15483                 Juiced 2: Hot Import Nights  2007    Racing   \n",
              "15641                       Taiko no Tatsujin Wii  2008      Misc   \n",
              "15658                    Medal of Honor: Airborne  2007   Shooter   \n",
              "15891               NASCAR 06: Total Team Control  2005    Racing   \n",
              "\n",
              "                Publisher  NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "435       Electronic Arts      0.58     0.47     0.01         0.1  \n",
              "446           Codemasters      0.25     0.76     0.08        0.27  \n",
              "563              Nintendo      5.55     1.94     2.23        0.15  \n",
              "611         Vivendi Games      0.14     0.05        0           0  \n",
              "658             LucasArts      1.23      0.3        0        0.14  \n",
              "...                   ...       ...      ...      ...         ...  \n",
              "15212  BAM! Entertainment      0.02     0.01        0           0  \n",
              "15483                 THQ      0.00     0.01        0           0  \n",
              "15641  Namco Bandai Games      0.00        0     0.67           0  \n",
              "15658     Electronic Arts      0.45     0.53     0.01        0.12  \n",
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              "      <td>Juiced 2: Hot Import Nights</td>\n",
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              "      <td>Racing</td>\n",
              "      <td>THQ</td>\n",
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              "      <th>15641</th>\n",
              "      <td>Taiko no Tatsujin Wii</td>\n",
              "      <td>2008</td>\n",
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              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <th>15658</th>\n",
              "      <td>Medal of Honor: Airborne</td>\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "# 북미지역에서의 출고량 데이터 중 문자를 포함하는 열 제거\n",
        "error_NA_Sales = df[df['NA_Sales'].str.contains('[a-zA-Z]')]\n",
        "df = df.drop(error_NA_Sales.index).reset_index(drop=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "IzjpMQngVo9h",
        "outputId": "48c87865-70e7-4773-cb67-95dfc61a7612"
      },
      "execution_count": 327,
      "outputs": [
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            "text/plain": [
              "                                                 Name  Year      Genre  \\\n",
              "0                        Candace Kane's Candy Factory  2008     Action   \n",
              "1                                      The Munchables  2009     Action   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010  Adventure   \n",
              "3                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction  2010   Platform   \n",
              "...                                               ...   ...        ...   \n",
              "15881                         Ice Age 2: The Meltdown  2006   Platform   \n",
              "15882                     Rainbow Islands: Revolution  2005     Action   \n",
              "15883                                        NBA 2K16  2015     Sports   \n",
              "15884                     Toukiden: The Age of Demons  2013     Action   \n",
              "15885                        The King of Fighters '95  1996   Fighting   \n",
              "\n",
              "                         Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0                        Destineer     0.04        0        0           0  \n",
              "1               Namco Bandai Games     0.17        0        0        0.01  \n",
              "2                        Alchemist        0        0     0.02           0  \n",
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              "4                      D3Publisher     0.12     0.09        0        0.04  \n",
              "...                            ...      ...      ...      ...         ...  \n",
              "15881                Vivendi Games     0.15     0.04        0        0.01  \n",
              "15882            Rising Star Games     0.01        0        0           0  \n",
              "15883         Take-Two Interactive     0.44     0.19     0.03        0.13  \n",
              "15884                   Tecmo Koei     0.05     0.05     0.25        0.03  \n",
              "15885  Sony Computer Entertainment        0        0     0.16        0.01  \n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-82f43ec6-4cb5-4c31-94a0-10772af3fd11')\"\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-82f43ec6-4cb5-4c31-94a0-10772af3fd11');\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",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 327
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# df에 변경한 데이터들을 합쳐주고 인덱스 초기화\n",
        "df = df.append(error_na_k)\n",
        "df = df.append(error_na_m)\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 554
        },
        "id": "ugRcxBPakKJI",
        "outputId": "9d72d895-21b8-440a-f1c9-6665d7f282d2"
      },
      "execution_count": 328,
      "outputs": [
        {
          "output_type": "execute_result",
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              "                                                 Name  Year      Genre  \\\n",
              "0                        Candace Kane's Candy Factory  2008     Action   \n",
              "1                                      The Munchables  2009     Action   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010  Adventure   \n",
              "3                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction  2010   Platform   \n",
              "...                                               ...   ...        ...   \n",
              "16069                                          Driven  2001     Racing   \n",
              "16070                     Juiced 2: Hot Import Nights  2007     Racing   \n",
              "16071                           Taiko no Tatsujin Wii  2008       Misc   \n",
              "16072                        Medal of Honor: Airborne  2007    Shooter   \n",
              "16073                   NASCAR 06: Total Team Control  2005     Racing   \n",
              "\n",
              "                Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0               Destineer     0.04        0        0           0  \n",
              "1      Namco Bandai Games     0.17        0        0        0.01  \n",
              "2               Alchemist        0        0     0.02           0  \n",
              "3               Zoo Games     0.04        0        0           0  \n",
              "4             D3Publisher     0.12     0.09        0        0.04  \n",
              "...                   ...      ...      ...      ...         ...  \n",
              "16069  BAM! Entertainment     0.02     0.01        0           0  \n",
              "16070                 THQ      0.0     0.01        0           0  \n",
              "16071  Namco Bandai Games      0.0        0     0.67           0  \n",
              "16072     Electronic Arts     0.45     0.53     0.01        0.12  \n",
              "16073     Electronic Arts     0.53     0.02        0        0.09  \n",
              "\n",
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              "      <td>2010</td>\n",
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              "      <td>D3Publisher</td>\n",
              "      <td>0.12</td>\n",
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              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.0</td>\n",
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              "      <th>16072</th>\n",
              "      <td>Medal of Honor: Airborne</td>\n",
              "      <td>2007</td>\n",
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              "      <td>Racing</td>\n",
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              "      <td>0.53</td>\n",
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              "<p>16074 rows × 8 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3dc2fc29-e67d-4df8-9d81-7d83ebcc1d9a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
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              "      \n",
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              "\n",
              "    .colab-df-convert {\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      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",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-3dc2fc29-e67d-4df8-9d81-7d83ebcc1d9a 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-3dc2fc29-e67d-4df8-9d81-7d83ebcc1d9a');\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",
              "          const docLink = document.createElement('div');\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 328
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### EU (유럽지역) ####"
      ],
      "metadata": {
        "id": "JbKssvyVIGTh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['EU_Sales'].str.contains('[a-zA-Z]')].shape[0] == df[df['EU_Sales'].str.contains('K')].shape[0] + df[df['EU_Sales'].str.contains('M')].shape[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JiadEfoVpcff",
        "outputId": "08f3ae7a-6680-498a-962f-914c41eecba9"
      },
      "execution_count": 329,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 329
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 유럽지역에서의 출고량 데이터 수정\n",
        "error_eu_k = df[df['EU_Sales'].str.contains('K')]\n",
        "error_eu_k['EU_Sales'] = error_eu_k['EU_Sales'].str.replace('K', '').astype('float')*0.001\n",
        "\n",
        "error_eu_m = df[df['EU_Sales'].str.contains('M')]\n",
        "error_eu_m['EU_Sales'] = error_eu_m['EU_Sales'].str.replace('M', '').astype('float')\n",
        "\n",
        "error_EU_Sales = df[df['EU_Sales'].str.contains('[a-zA-Z]')]\n",
        "df = df.drop(error_EU_Sales.index).reset_index(drop=True)\n",
        "\n",
        "df = df.append(error_eu_k)\n",
        "df = df.append(error_eu_m)\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 761
        },
        "id": "mduX1iyZQWF2",
        "outputId": "51d8a4ab-2341-4027-ff13-19ee3db7b02e"
      },
      "execution_count": 330,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-330-aad9c90d00c4>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_eu_k['EU_Sales'] = error_eu_k['EU_Sales'].str.replace('K', '').astype('float')*0.001\n",
            "<ipython-input-330-aad9c90d00c4>:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_eu_m['EU_Sales'] = error_eu_m['EU_Sales'].str.replace('M', '').astype('float')\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name  Year      Genre  \\\n",
              "0                        Candace Kane's Candy Factory  2008     Action   \n",
              "1                                      The Munchables  2009     Action   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010  Adventure   \n",
              "3                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction  2010   Platform   \n",
              "...                                               ...   ...        ...   \n",
              "16069                             Aladdin Magic Racer  2011     Racing   \n",
              "16070                         Tomb Raider: Underworld  2009     Action   \n",
              "16071                                    Koihime Enbu  2016   Fighting   \n",
              "16072                                     Ford Racing  2001     Racing   \n",
              "16073                                     Bulletstorm  2011    Shooter   \n",
              "\n",
              "                 Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0                Destineer     0.04        0        0           0  \n",
              "1       Namco Bandai Games     0.17        0        0        0.01  \n",
              "2                Alchemist        0        0     0.02           0  \n",
              "3                Zoo Games     0.04        0        0           0  \n",
              "4              D3Publisher     0.12     0.09        0        0.04  \n",
              "...                    ...      ...      ...      ...         ...  \n",
              "16069  Big Ben Interactive     0.01      0.0        0           0  \n",
              "16070    Eidos Interactive     0.09     0.04        0        0.05  \n",
              "16071                 Yeti        0      0.0     0.02           0  \n",
              "16072   Empire Interactive     0.48     0.33       0K        0.06  \n",
              "16073      Electronic Arts     0.61     0.32     0.01        0.08  \n",
              "\n",
              "[16074 rows x 8 columns]"
            ],
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              "      <th>0</th>\n",
              "      <td>Candace Kane's Candy Factory</td>\n",
              "      <td>2008</td>\n",
              "      <td>Action</td>\n",
              "      <td>Destineer</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>1</th>\n",
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              "      <td>0</td>\n",
              "      <td>0.01</td>\n",
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              "      <th>2</th>\n",
              "      <td>Otome wa Oanesama Boku ni Koi Shiteru Portable</td>\n",
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              "      <td>Adventure</td>\n",
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              "      <td>0.04</td>\n",
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              "      <th>4</th>\n",
              "      <td>Ben 10 Ultimate Alien: Cosmic Destruction</td>\n",
              "      <td>2010</td>\n",
              "      <td>Platform</td>\n",
              "      <td>D3Publisher</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0</td>\n",
              "      <td>0.04</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>16069</th>\n",
              "      <td>Aladdin Magic Racer</td>\n",
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              "      <td>0.01</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>16070</th>\n",
              "      <td>Tomb Raider: Underworld</td>\n",
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              "      <td>Eidos Interactive</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0</td>\n",
              "      <td>0.05</td>\n",
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              "    <tr>\n",
              "      <th>16071</th>\n",
              "      <td>Koihime Enbu</td>\n",
              "      <td>2016</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>Yeti</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>16072</th>\n",
              "      <td>Ford Racing</td>\n",
              "      <td>2001</td>\n",
              "      <td>Racing</td>\n",
              "      <td>Empire Interactive</td>\n",
              "      <td>0.48</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0K</td>\n",
              "      <td>0.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16073</th>\n",
              "      <td>Bulletstorm</td>\n",
              "      <td>2011</td>\n",
              "      <td>Shooter</td>\n",
              "      <td>Electronic Arts</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16074 rows × 8 columns</p>\n",
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              "                                                     [key], {});\n",
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            ]
          },
          "metadata": {},
          "execution_count": 330
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### JP (일본지역) ####"
      ],
      "metadata": {
        "id": "MHNT270eINCT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['JP_Sales'].str.contains('[a-zA-Z]')].shape[0] == df[df['JP_Sales'].str.contains('K')].shape[0] + df[df['JP_Sales'].str.contains('M')].shape[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wMqAdUNFIlvu",
        "outputId": "bfcae600-489d-488c-b4da-1ead27459c36"
      },
      "execution_count": 331,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 331
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 일본지역에서의 출고량 데이터 수정\n",
        "error_jp_k = df[df['JP_Sales'].str.contains('K')]\n",
        "error_jp_k['JP_Sales'] = error_jp_k['JP_Sales'].str.replace('K', '').astype('float')*0.001\n",
        "\n",
        "error_jp_m = df[df['JP_Sales'].str.contains('M')]\n",
        "error_jp_m['JP_Sales'] = error_jp_m['JP_Sales'].str.replace('M', '').astype('float')\n",
        "\n",
        "error_JP_Sales = df[df['JP_Sales'].str.contains('[a-zA-Z]')]\n",
        "df = df.drop(error_JP_Sales.index).reset_index(drop=True)\n",
        "\n",
        "df = df.append(error_jp_k)\n",
        "df = df.append(error_jp_m)\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 830
        },
        "id": "1mcvjedzDNl5",
        "outputId": "192aaec6-52a9-4dc7-f29c-0714d5dcdcb2"
      },
      "execution_count": 332,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-332-4ad49f935091>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_jp_k['JP_Sales'] = error_jp_k['JP_Sales'].str.replace('K', '').astype('float')*0.001\n",
            "<ipython-input-332-4ad49f935091>:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_jp_m['JP_Sales'] = error_jp_m['JP_Sales'].str.replace('M', '').astype('float')\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name  Year      Genre  \\\n",
              "0                        Candace Kane's Candy Factory  2008     Action   \n",
              "1                                      The Munchables  2009     Action   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010  Adventure   \n",
              "3                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction  2010   Platform   \n",
              "...                                               ...   ...        ...   \n",
              "16069                                    NFL Xtreme 2  1999     Sports   \n",
              "16070                     Wonder World Amusement Park  2009       Misc   \n",
              "16071       Shin Chan: Las Nuevas Aventuras Para Wii!  2006     Action   \n",
              "16072           Captain Morgane and the Golden Turtle  2012  Adventure   \n",
              "16073                  Smiley World: Island Challenge  2009     Puzzle   \n",
              "\n",
              "                    Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0                   Destineer     0.04        0        0           0  \n",
              "1          Namco Bandai Games     0.17        0        0        0.01  \n",
              "2                   Alchemist        0        0     0.02           0  \n",
              "3                   Zoo Games     0.04        0        0           0  \n",
              "4                 D3Publisher     0.12     0.09        0        0.04  \n",
              "...                       ...      ...      ...      ...         ...  \n",
              "16069             989 Studios     0.27     0.18      0.0        0.03  \n",
              "16070   Majesco Entertainment     0.08        0      0.0        0.01  \n",
              "16071               505 Games        0        0     0.07           0  \n",
              "16072      Reef Entertainment        0     0.03      0.0           0  \n",
              "16073  Zoo Digital Publishing     0.01        0      0.0           0  \n",
              "\n",
              "[16074 rows x 8 columns]"
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              "      <td>The Munchables</td>\n",
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              "      <td>2010</td>\n",
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              "      <td>D3Publisher</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0</td>\n",
              "      <td>0.04</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <th>16069</th>\n",
              "      <td>NFL Xtreme 2</td>\n",
              "      <td>1999</td>\n",
              "      <td>Sports</td>\n",
              "      <td>989 Studios</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16070</th>\n",
              "      <td>Wonder World Amusement Park</td>\n",
              "      <td>2009</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Majesco Entertainment</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16071</th>\n",
              "      <td>Shin Chan: Las Nuevas Aventuras Para Wii!</td>\n",
              "      <td>2006</td>\n",
              "      <td>Action</td>\n",
              "      <td>505 Games</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>16072</th>\n",
              "      <td>Captain Morgane and the Golden Turtle</td>\n",
              "      <td>2012</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Reef Entertainment</td>\n",
              "      <td>0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>16073</th>\n",
              "      <td>Smiley World: Island Challenge</td>\n",
              "      <td>2009</td>\n",
              "      <td>Puzzle</td>\n",
              "      <td>Zoo Digital Publishing</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16074 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8c7826a4-45d4-457e-9330-0355fd976610')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8c7826a4-45d4-457e-9330-0355fd976610');\n",
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              "            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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              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 332
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Other (기타지역) ####"
      ],
      "metadata": {
        "id": "eb3bu2sEIRvE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['Other_Sales'].str.contains('[a-zA-Z]')].shape[0] == df[df['Other_Sales'].str.contains('K')].shape[0] + df[df['Other_Sales'].str.contains('M')].shape[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tTPW8MFbIoh2",
        "outputId": "5ee2e8b3-0e1b-45e1-ffb9-f6979d3e9c32"
      },
      "execution_count": 333,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 333
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 기타지역에서의 출고량 데이터 수정\n",
        "error_other_k = df[df['Other_Sales'].str.contains('K')]\n",
        "error_other_k['Other_Sales'] = error_other_k['Other_Sales'].str.replace('K', '').astype('float')*0.001\n",
        "\n",
        "error_other_m = df[df['Other_Sales'].str.contains('M')]\n",
        "error_other_m['Other_Sales'] = error_other_m['Other_Sales'].str.replace('M', '').astype('float')\n",
        "\n",
        "error_Other_Sales = df[df['Other_Sales'].str.contains('[a-zA-Z]')]\n",
        "df = df.drop(error_Other_Sales.index).reset_index(drop=True)\n",
        "\n",
        "df = df.append(error_other_k)\n",
        "df = df.append(error_other_m)\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 796
        },
        "id": "pALX0qWtDd83",
        "outputId": "d6443ff0-6857-48d9-f4f0-fbcc6bda0d92"
      },
      "execution_count": 334,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-334-273904595343>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_other_k['Other_Sales'] = error_other_k['Other_Sales'].str.replace('K', '').astype('float')*0.001\n",
            "<ipython-input-334-273904595343>:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  error_other_m['Other_Sales'] = error_other_m['Other_Sales'].str.replace('M', '').astype('float')\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    Name  Year       Genre  \\\n",
              "0                           Candace Kane's Candy Factory  2008      Action   \n",
              "1                                         The Munchables  2009      Action   \n",
              "2         Otome wa Oanesama Boku ni Koi Shiteru Portable  2010   Adventure   \n",
              "3                       Deal or No Deal: Special Edition  2010        Misc   \n",
              "4              Ben 10 Ultimate Alien: Cosmic Destruction  2010    Platform   \n",
              "...                                                  ...   ...         ...   \n",
              "16069  World Championship Poker: Featuring Howard Led...  2006        Misc   \n",
              "16070  Yu-Gi-Oh! Ultimate Masters: World Championship...  2006        Misc   \n",
              "16071                              PBR: Out of the Chute  2008      Sports   \n",
              "16072                                          1 vs. 100  2008        Misc   \n",
              "16073                       Thoroughbred Breeder II Plus  1995  Simulation   \n",
              "\n",
              "                          Publisher NA_Sales EU_Sales JP_Sales Other_Sales  \n",
              "0                         Destineer     0.04        0        0           0  \n",
              "1                Namco Bandai Games     0.17        0        0        0.01  \n",
              "2                         Alchemist        0        0     0.02           0  \n",
              "3                         Zoo Games     0.04        0        0           0  \n",
              "4                       D3Publisher     0.12     0.09        0        0.04  \n",
              "...                             ...      ...      ...      ...         ...  \n",
              "16069            Oxygen Interactive     0.82     0.64        0        0.22  \n",
              "16070  Konami Digital Entertainment     0.14     0.05     0.07        0.01  \n",
              "16071           Crave Entertainment     0.12        0        0        0.01  \n",
              "16072                     DSI Games     0.08      0.0        0        0.01  \n",
              "16073                          Hect        0        0     0.04         0.0  \n",
              "\n",
              "[16074 rows x 8 columns]"
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              "      <td>0.82</td>\n",
              "      <td>0.64</td>\n",
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              "      <td>0.22</td>\n",
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              "      <th>16070</th>\n",
              "      <td>Yu-Gi-Oh! Ultimate Masters: World Championship...</td>\n",
              "      <td>2006</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Konami Digital Entertainment</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.01</td>\n",
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              "    <tr>\n",
              "      <th>16071</th>\n",
              "      <td>PBR: Out of the Chute</td>\n",
              "      <td>2008</td>\n",
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              "      <td>Crave Entertainment</td>\n",
              "      <td>0.12</td>\n",
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              "      <td>0.01</td>\n",
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              "    <tr>\n",
              "      <th>16072</th>\n",
              "      <td>1 vs. 100</td>\n",
              "      <td>2008</td>\n",
              "      <td>Misc</td>\n",
              "      <td>DSI Games</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>16073</th>\n",
              "      <td>Thoroughbred Breeder II Plus</td>\n",
              "      <td>1995</td>\n",
              "      <td>Simulation</td>\n",
              "      <td>Hect</td>\n",
              "      <td>0</td>\n",
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              "      <td>0.04</td>\n",
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              "<p>16074 rows × 8 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dbd44b6b-303e-4cba-8666-e19c4076b46b')\"\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-dbd44b6b-303e-4cba-8666-e19c4076b46b 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-dbd44b6b-303e-4cba-8666-e19c4076b46b');\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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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 334
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 각각의 출고량을 float 형식으로 변환\n",
        "df = df.astype({'NA_Sales': 'float', 'EU_Sales': 'float', 'JP_Sales': 'float', 'Other_Sales': 'float'})\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j27RwlzsUVDf",
        "outputId": "9bc9fb77-93fe-4d1e-a545-d8ad226fa9f9"
      },
      "execution_count": 335,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 16074 entries, 0 to 16073\n",
            "Data columns (total 8 columns):\n",
            " #   Column       Non-Null Count  Dtype  \n",
            "---  ------       --------------  -----  \n",
            " 0   Name         16074 non-null  object \n",
            " 1   Year         16074 non-null  int64  \n",
            " 2   Genre        16074 non-null  object \n",
            " 3   Publisher    16074 non-null  object \n",
            " 4   NA_Sales     16074 non-null  float64\n",
            " 5   EU_Sales     16074 non-null  float64\n",
            " 6   JP_Sales     16074 non-null  float64\n",
            " 7   Other_Sales  16074 non-null  float64\n",
            "dtypes: float64(4), int64(1), object(3)\n",
            "memory usage: 1004.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 6) 플랫폼만 다른 게임 → 같은 게임으로 보고 데이터 합치기 ###"
      ],
      "metadata": {
        "id": "rlW-o2JwLkFH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 중복되는 데이터를 dup이라는 변수에 저장\n",
        "dup = df[df.duplicated(['Name', 'Year', 'Genre', 'Publisher'], keep=False)]\n",
        "dup"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "cp0KMKNCLxFG",
        "outputId": "97faf14b-d5cd-4f73-8f4b-8b2ba57f195d"
      },
      "execution_count": 336,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    Name  Year       Genre  \\\n",
              "0                           Candace Kane's Candy Factory  2008      Action   \n",
              "4              Ben 10 Ultimate Alien: Cosmic Destruction  2010    Platform   \n",
              "6                  JASF: Jane's Advanced Strike Fighters  2011  Simulation   \n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "# 중복되는 각 행의 열 값을 합친 값을 dup_sum이라는 변수에 저장\n",
        "dup_sum = dup.groupby(['Name', 'Year', 'Genre', 'Publisher'], as_index=False)['NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales'].sum()\n",
        "dup_sum"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 559
        },
        "id": "JfAsXOzeL28C",
        "outputId": "7c436a82-5bde-4b57-e7ac-02fac49a38f5"
      },
      "execution_count": 337,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-337-742308cbe0b4>:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  dup_sum = dup.groupby(['Name', 'Year', 'Genre', 'Publisher'], as_index=False)['NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales'].sum()\n"
          ]
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              "                                  Name  Year      Genre  \\\n",
              "0               007: Quantum of Solace  2008     Action   \n",
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              "2                     187: Ride or Die  2005     Racing   \n",
              "3                  2002 FIFA World Cup  2002     Sports   \n",
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              "...                                ...   ...        ...   \n",
              "2145                            iCarly  2009  Adventure   \n",
              "2146        iCarly 2: iJoin The Click!  2010  Adventure   \n",
              "2147                            nail'd  2010     Racing   \n",
              "2148         pro evolution soccer 2011  2010     Sports   \n",
              "2149      uDraw Studio: Instant Artist  2011       Misc   \n",
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              "                         Publisher  NA_Sales  EU_Sales  JP_Sales  Other_Sales  \n",
              "0                       Activision      1.84      1.35      0.04         0.68  \n",
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              "2                          Ubisoft      0.12      0.07      0.00         0.02  \n",
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              "...                            ...       ...       ...       ...          ...  \n",
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              "2146                    Activision      0.34      0.02      0.00         0.03  \n",
              "2147                   Deep Silver      0.16      0.04      0.00         0.03  \n",
              "2148  Konami Digital Entertainment      0.55      2.28      0.91         0.78  \n",
              "2149                           THQ      0.09      0.10      0.00         0.02  \n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-76ceb25c-9003-4107-b35a-0b0f0ecc4440 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
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              "          const element = document.querySelector('#df-76ceb25c-9003-4107-b35a-0b0f0ecc4440');\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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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 337
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터 중복값 전체 삭제 후, dup_sum을 df에 병합시키고 인덱스 초기화\n",
        "df = df.drop_duplicates(['Name', 'Year', 'Genre', 'Publisher'], keep=False).reset_index(drop=True)\n",
        "df = df.append(dup_sum).reset_index(drop=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "2EPZsT0YdZ_Y",
        "outputId": "2beb56ff-a6c7-4de8-9f4d-d7ec54432416"
      },
      "execution_count": 338,
      "outputs": [
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              "                                                 Name  Year      Genre  \\\n",
              "0                                      The Munchables  2009     Action   \n",
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              "2                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "3                              Power Pro Kun Pocket 8  2005     Sports   \n",
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              "...                                               ...   ...        ...   \n",
              "12141                                          iCarly  2009  Adventure   \n",
              "12142                      iCarly 2: iJoin The Click!  2010  Adventure   \n",
              "12143                                          nail'd  2010     Racing   \n",
              "12144                       pro evolution soccer 2011  2010     Sports   \n",
              "12145                    uDraw Studio: Instant Artist  2011       Misc   \n",
              "\n",
              "                          Publisher  NA_Sales  EU_Sales  JP_Sales  Other_Sales  \n",
              "0                Namco Bandai Games      0.17      0.00      0.00         0.01  \n",
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              "2                         Zoo Games      0.04      0.00      0.00         0.00  \n",
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              "4                        Tecmo Koei      0.07      0.00      0.11         0.01  \n",
              "...                             ...       ...       ...       ...          ...  \n",
              "12141                    Activision      1.09      0.01      0.00         0.08  \n",
              "12142                    Activision      0.34      0.02      0.00         0.03  \n",
              "12143                   Deep Silver      0.16      0.04      0.00         0.03  \n",
              "12144  Konami Digital Entertainment      0.55      2.28      0.91         0.78  \n",
              "12145                           THQ      0.09      0.10      0.00         0.02  \n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "          document.querySelector('#df-8e9e9483-07a5-4279-bde2-3e2918a364d0 button.colab-df-convert');\n",
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              "\n",
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              "          const element = document.querySelector('#df-8e9e9483-07a5-4279-bde2-3e2918a364d0');\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",
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              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 338
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 7) Feature Engineering ###"
      ],
      "metadata": {
        "id": "tbeZ-BbnTAT3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 총 출고량 column 추가 ####"
      ],
      "metadata": {
        "id": "TcVJ1fb4J_4b"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 게임 별 총 판매량 구하기\n",
        "total_sales = df[{'NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales'}]\n",
        "total_sales.sum(axis=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CaWnu7sWSQEi",
        "outputId": "277f50a5-14ba-44fa-cc03-28389ac31c46"
      },
      "execution_count": 339,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        0.18\n",
              "1        0.02\n",
              "2        0.04\n",
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              "4        0.19\n",
              "         ... \n",
              "12141    1.18\n",
              "12142    0.39\n",
              "12143    0.23\n",
              "12144    4.52\n",
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              "Length: 12146, dtype: float64"
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          "metadata": {},
          "execution_count": 339
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    {
      "cell_type": "code",
      "source": [
        "df['Total_Sales'] = total_sales.sum(axis=1)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 624
        },
        "id": "90n1VYO5SNfJ",
        "outputId": "955c8037-1455-4336-dd50-8afb1b648056"
      },
      "execution_count": 340,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name  Year      Genre  \\\n",
              "0                                      The Munchables  2009     Action   \n",
              "1      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010  Adventure   \n",
              "2                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "3                              Power Pro Kun Pocket 8  2005     Sports   \n",
              "4                      Samurai Warriors: State of War  2005     Action   \n",
              "...                                               ...   ...        ...   \n",
              "12141                                          iCarly  2009  Adventure   \n",
              "12142                      iCarly 2: iJoin The Click!  2010  Adventure   \n",
              "12143                                          nail'd  2010     Racing   \n",
              "12144                       pro evolution soccer 2011  2010     Sports   \n",
              "12145                    uDraw Studio: Instant Artist  2011       Misc   \n",
              "\n",
              "                          Publisher  NA_Sales  EU_Sales  JP_Sales  \\\n",
              "0                Namco Bandai Games      0.17      0.00      0.00   \n",
              "1                         Alchemist      0.00      0.00      0.02   \n",
              "2                         Zoo Games      0.04      0.00      0.00   \n",
              "3      Konami Digital Entertainment      0.00      0.00      0.14   \n",
              "4                        Tecmo Koei      0.07      0.00      0.11   \n",
              "...                             ...       ...       ...       ...   \n",
              "12141                    Activision      1.09      0.01      0.00   \n",
              "12142                    Activision      0.34      0.02      0.00   \n",
              "12143                   Deep Silver      0.16      0.04      0.00   \n",
              "12144  Konami Digital Entertainment      0.55      2.28      0.91   \n",
              "12145                           THQ      0.09      0.10      0.00   \n",
              "\n",
              "       Other_Sales  Total_Sales  \n",
              "0             0.01         0.18  \n",
              "1             0.00         0.02  \n",
              "2             0.00         0.04  \n",
              "3             0.00         0.14  \n",
              "4             0.01         0.19  \n",
              "...            ...          ...  \n",
              "12141         0.08         1.18  \n",
              "12142         0.03         0.39  \n",
              "12143         0.03         0.23  \n",
              "12144         0.78         4.52  \n",
              "12145         0.02         0.21  \n",
              "\n",
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              "      <th>Genre</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>NA_Sales</th>\n",
              "      <th>EU_Sales</th>\n",
              "      <th>JP_Sales</th>\n",
              "      <th>Other_Sales</th>\n",
              "      <th>Total_Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Munchables</td>\n",
              "      <td>2009</td>\n",
              "      <td>Action</td>\n",
              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Otome wa Oanesama Boku ni Koi Shiteru Portable</td>\n",
              "      <td>2010</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Alchemist</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Deal or No Deal: Special Edition</td>\n",
              "      <td>2010</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Zoo Games</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Power Pro Kun Pocket 8</td>\n",
              "      <td>2005</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Konami Digital Entertainment</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Samurai Warriors: State of War</td>\n",
              "      <td>2005</td>\n",
              "      <td>Action</td>\n",
              "      <td>Tecmo Koei</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12141</th>\n",
              "      <td>iCarly</td>\n",
              "      <td>2009</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Activision</td>\n",
              "      <td>1.09</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>1.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12142</th>\n",
              "      <td>iCarly 2: iJoin The Click!</td>\n",
              "      <td>2010</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Activision</td>\n",
              "      <td>0.34</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12143</th>\n",
              "      <td>nail'd</td>\n",
              "      <td>2010</td>\n",
              "      <td>Racing</td>\n",
              "      <td>Deep Silver</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12144</th>\n",
              "      <td>pro evolution soccer 2011</td>\n",
              "      <td>2010</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Konami Digital Entertainment</td>\n",
              "      <td>0.55</td>\n",
              "      <td>2.28</td>\n",
              "      <td>0.91</td>\n",
              "      <td>0.78</td>\n",
              "      <td>4.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12145</th>\n",
              "      <td>uDraw Studio: Instant Artist</td>\n",
              "      <td>2011</td>\n",
              "      <td>Misc</td>\n",
              "      <td>THQ</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12146 rows × 9 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af2291f7-7f7a-4d7d-8744-e42f9ac0026b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      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",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-af2291f7-7f7a-4d7d-8744-e42f9ac0026b 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-af2291f7-7f7a-4d7d-8744-e42f9ac0026b');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 340
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **2. Mission** ##"
      ],
      "metadata": {
        "id": "3K8j7ATUMoz9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 1) 지역에 따른 장르 선호도 ###"
      ],
      "metadata": {
        "id": "gBAZ4zmgaVjU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### NA (북미지역) ####"
      ],
      "metadata": {
        "id": "DUfBM56HhyZl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 각 지역에서 출고량 평균 구하기\n",
        "NA_ratio = df.groupby('Genre')['NA_Sales'].mean().sort_values(ascending=False)\n",
        "NA_ratio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Iq_7_MXUf8Vo",
        "outputId": "ad81fcd6-c982-482e-c6f0-657c3c0da41f"
      },
      "execution_count": 341,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Genre\n",
              "Platform        0.707888\n",
              "Shooter         0.645735\n",
              "Sports          0.454251\n",
              "Racing          0.423453\n",
              "Action          0.418182\n",
              "Fighting        0.335817\n",
              "Misc            0.288067\n",
              "Simulation      0.242329\n",
              "Puzzle          0.235848\n",
              "Role-Playing    0.233699\n",
              "Strategy        0.113222\n",
              "Adventure       0.091842\n",
              "Name: NA_Sales, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 341
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "NA_ratio.plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "aqzBBZvYq_Cc",
        "outputId": "fb8562af-3af2-4629-f096-5222334d292f"
      },
      "execution_count": 342,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Genre'>"
            ]
          },
          "metadata": {},
          "execution_count": 342
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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1KqqjZi1rbJOotpLjKrPW094mGxvNIz+YK+xiODo6wsPDA3q9HgCg1+vh4eGBhg0bmux35coV49cZGRk4deoU2rRpU+EbICLrZVYXY8GCBQgODsa6detQt25dhIeHAwACAwMRFBSEDh06YOfOnfjpp59ga2sLSZIwZswY9OrVq1IbT0SVy6yAcHNzQ1RUVJntmzZtMn49b9489VpFRFaBMymJSIgBQURCDAgiElJ1HgRRMYe69rCrVfbXq/Rl1AcPC5B9L7eqmkUyMSCoUtjVsoX3jNgK99u33AfqXPGnysAuBhEJMSCISIgBQURCDAgiEmJAEJEQA4KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREIMCCISYkAQkRADgoiEGBBEJMSAICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCREAOCiIQYEEQkxIAgIiEGBBEJMSCISIgBQURCDAgiEuLDe8nqmfOkcD4lvHIwIMjqmfOkcD4lvHKwi0FEQgwIIhJiF4OeKuWNZ5QcywA4nlESA4KeKmqNZzwtA6cMCCIFnpaBU45BEJEQA4KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREIMCCISYkAQkRADgoiEGBBEJMSAICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCRkFkrSiUlJSE4OBhZWVmoX78+wsPD0bx5c5N91q5di7i4ONjY2KBGjRqYPn06evfuXRltJqIqYlZAhIaGIiAgAD4+PoiNjUVISAi2b99usk/Hjh3x9ttvw97eHhcuXMCYMWNw/Phx2NnZVUrDiajyVdjFSE9PR2JiIry8vAAAXl5eSExMREZGhsl+vXv3hr29PQCgbdu2kCQJWVlZ6reYiKpMhQGRmpoKFxcXaLVaAIBWq4WzszNSU1OFx+zduxfNmjVDo0aN1GspEVU51Ve1Pn36NFauXInNmzfLPtbRsY6in1n6uQaWUKsW21T1tZ6kNlnLe6kwIHQ6HdLS0mAwGKDVamEwGHDr1i3odLoy+/7666+YNWsW1q1bh5YtW8puTHp6DgoLJeNrc9/Y7duPXlxczj+QWrUqqqNmrce5TWrWssb3Z06byqut5DgltWxsNI/8YK6wi+Ho6AgPDw/o9XoAgF6vh4eHBxo2bGiyX3x8PKZPn45Vq1ahXbt25rafiKyYWfMgFixYgMjISHh6eiIyMhJhYWEAgMDAQCQkJAAAwsLC8ODBA4SEhMDHxwc+Pj64ePFi5bWciCqdWWMQbm5uiIqKKrN906ZNxq+jo6PVaxURWQXOpCQiIQYEEQkxIIhIiAFBREIMCCISYkAQkRADgoiEGBBEJMSAICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCREAOCiIQYEEQkxIAgIiEGBBEJMSCISIgBQURCDAgiEmJAEJEQA4KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREIMCCISYkAQkRADgoiEGBBEJMSAICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCREAOCiIQYEEQkxIAgIiEGBBEJMSCISIgBQURCDAgiEmJAEJEQA4KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREK21d0AoqedQ1172NUy/VN0cnIwef3gYQGy7+VWZbMAMCCIqp1dLVt4z4h95D77lvsgu4raUxK7GEQkxIAgIiEGBBEJmRUQSUlJ8Pf3h6enJ/z9/ZGcnFxmn+PHj8PPzw/t27dHeHi42u0kompgVkCEhoYiICAABw4cQEBAAEJCQsrs4+rqiiVLluCdd95RvZFEVD0qDIj09HQkJibCy8sLAODl5YXExERkZGSY7Pfcc8/Bw8MDtra8MEL0pKjwrzk1NRUuLi7QarUAAK1WC2dnZ6SmpqJhw4aqNsbRsY6i40pfM7aEWrXYpqqvxTap3war+rhPT89BYaFkfG3uG7t9+9FXiOX8A6lVq6I6atZ6nNukZi1rfH9V2SZR7UcdZ2OjeeQHc4VdDJ1Oh7S0NBgMBgCAwWDArVu3oNPpZDeWiB4vFQaEo6MjPDw8oNfrAQB6vR4eHh6qdy+IyPqYdRVjwYIFiIyMhKenJyIjIxEWFgYACAwMREJCAgDgzJkz6NOnD7Zs2YIdO3agT58+OHbsWOW1nIgqnVljEG5uboiKiiqzfdOmTcavu3Xrhh9//FG9lhFRtbOqQUoiUq68u0IBy+4MZUAQPSHMuSsUkHdnKO/FICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCREAOCiIQYEEQkxIAgIiEGBBEJMSCISIgBQURCDAgiEmJAEJEQA4KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREIMCCISYkAQkRADgoiEGBBEJMSAICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCREAOCiIQYEEQkxIAgIiEGBBEJMSCISIgBQURCDAgiEmJAEJEQA4KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREIMCCISYkAQkRADgoiEGBBEJMSAICIhBgQRCTEgiEiIAUFEQgwIIhJiQBCRkFkBkZSUBH9/f3h6esLf3x/Jycll9jEYDAgLC8OAAQMwcOBAREVFqd1WIqpiZgVEaGgoAgICcODAAQQEBCAkJKTMPvv27UNKSgoOHjyInTt3YvXq1bh+/brqDSaiqlNhQKSnpyMxMRFeXl4AAC8vLyQmJiIjI8Nkv7i4OIwYMQI2NjZo2LAhBgwYgB9++KFyWk1EVcK2oh1SU1Ph4uICrVYLANBqtXB2dkZqaioaNmxosl/jxo2Nr3U6HW7evCmrMTY2mjLbnBvYKzpOSR01a5lTR81aj2ub1Kxlje/PGttUslaFNaUKJCQkSEOGDDHZNnjwYOn333832ebl5SX99ttvxtcbN26UFi1aVFF5IrJiFXYxdDod0tLSYDAYABQNRt66dQs6na7Mfn/99ZfxdWpqKho1amRWmhGRdaowIBwdHeHh4QG9Xg8A0Ov18PDwMOleAMCgQYMQFRWFwsJCZGRk4NChQ/D09KycVhNRldBIkiRVtNOVK1cQHByMe/fuoW7duggPD0fLli0RGBiIoKAgdOjQAQaDAQsXLsRPP/0EAAgMDIS/v3+lvwEiqjxmBQQRPZ04k5KIhBgQRCTEgCAiIQYEEQkxIIhIiAFBREJPTUAUFhbi6NGj1d0MonI9fPiwuptQrqcmIGxsbPDZZ5+pUmvLli3Izs4GAMyaNQuDBg3C8ePHValNT6d+/frhk08+QUpKisW1Tpw4gcjISADAnTt3kJSUpLhWhXdzPknc3d0RHx+Pjh07WlRnz549eOutt3Dy5ElkZGTg448/xuLFi9GrVy/Ztb7++usy2xwcHNCxY0c0b97c7Drp6en46quvcO3aNRQUFBi3r1y5UnabyjvTqlOnDtq0aQMHBwdZtRYvXowpU6agfv36AIDMzEysW7cO8+fPl1Xnl19+QUREBK5duwaDwQBJkqDRaHDixAlZdUrKyMgoc8uAXLm5uWW22dubd0dlSd999x127tyJcePGwc3NDaNHj0bfvn1l19m4cSOOHj2K27dvY8yYMSgoKMC8efPw7bffyq4FPCYBcfXqVaxfv77ML//u3btl1Tl37hzeeOMNPPfcc3jmmWcU1ym+9f3UqVPw9vbGCy+8AKUTUo8dO4aff/4ZL730EgDg5MmT6NSpE1asWIEpU6bg9ddfN6vO+++/Dzc3N7z00kvG9im1bt06/P7772jTpg0A4NKlS2jbti3S0tKwePFiWb+4Z86cMYYDADRo0AA///yz7DbNnz8fkyZNQufOnWFjY9mJ72+//YZp06YZu50JCQnYtWsXFi1aJLtWly5doNGY3jJta2uLjh07YtGiRWjZsqVZdRwdHTFp0iS8++67OHz4MMLCwrBo0SKMGTMGo0ePRq1atcyqo9frER0djREjRgAAGjVqhJycHHlvquR7UXxkFZo6dSp8fHzg5+dn0S//hx9+qEp77OzssHHjRuzfvx9ff/01JElCfn6+oloajQb79u0zrqWRmpqKsLAwREVF4a233jI7IO7du6foF7w8zZo1w0cffYT27dsDKArWLVu2ICIiAh988IGsgCi+C7ikkiFvLjs7O3h7e8s+rjxLly7Fpk2bMHPmTABAhw4dEBwcrKjW9OnTUatWLbz++uuQJAkxMTHIzMyEq6srQkND8dVXX5ldKzc3F7Gxsfjmm2/QrFkzjBgxAqdOnUJgYCC2b99uVg07OzvUqFHDZFvpAJPjsQgIW1tbjB8/3uI63bt3B2D5qeXSpUvxzTffYObMmXByckJKSoriX97r16+XWWjnxo0bcHJykhWGrVu3RlpaGlxcXBS1o6QLFy4YwwEA2rVrh0uXLsHNzU32mVKHDh2wePFiBAYGQpIkfPHFF+jQoYPsNvXp0wdHjx7Fyy+/LPvY0vLz89GqVSuTbaX/qMx14MAB7Nmzx/h67Nix8PPzw549e7Blyxaz6yxcuBAHDx5Ev3798OmnnxrP3ry9vTFo0CCz6zRq1AhnzpyBRqNBYWEhNmzYgNatW5v/hkp5LAKid+/eqvxyqHVqGR8fb9KHbtasmeK1LxwdHbFhwwb4+fkBAGJiYtCwYUMYDAZZyX/v3j0MHToUXbp0MTkdVTIGYW9vD71eb1xmUK/Xw87ODoD8T6N58+ZhyZIl8PX1hUajwcsvv4x58+bJbtPOnTvx+eefo3bt2qhZs6ZFYxA1a9bE33//bXwvf/zxh9mn8KXl5ubi2rVrcHV1BQBcu3YN9+/fBwBZAd+kSRPs378f9erVK/M9c88eAOCjjz7CnDlzcPnyZXTq1AndunXDp59+avbxpT0Wd3OeOHECkyZNgo2NjUW/HKNGjcLixYsxc+ZM7N27FwDw2muvYf/+/bLqDBs2DDExMRVuM0daWhqWLFmCU6dOAQB69OiBefPmoUGDBkhOTkbbtm3NqiP62cOGDZPdpitXrmDWrFm4fPkyNBoNWrVqhfDwcDRp0gS//vorevbsKbumpW7cuFHu9iZNmsiudfToUeOYVu/evXHs2DFERETgn//8p+xaBw4cQEhICNq3bw9JkpCYmIiwsDD06tULX331Fd577z2z6qgx2GkwGLB79274+/sjNzcXhYWFqF27tqwapT0WATFw4EDMmDED7dq1MxmgkvvLMXz4cERHR8PX19cYECW/rkhCQgLi4+OxadMmBAYGGrfn5ORg3759xkV1nhTFg1t16tRRXCMuLg59+vRBnTp1sHLlSsTHx2P69OkmXRhzFRQUGC/ZtWjRAra2yk+Ar127hmPHjkGSJPTq1QvPPfec4lp37txBfHw8AKBTp05wdHSUXcPd3V2Vwc7i7o1aHosuRr169WT1w0QsPbVMS0vD77//jtzcXPz+++/G7bVr18bSpUsVt+vEiRNISUkxGbwbPXq0rBoZGRlYtGiR8ayqZ8+emD9/vuKxlpSUFKSkpJgMMirp4q1fvx5DhgxBfHw8jh8/jrFjx2Lx4sXYsWOHrDoJCQkICgoynkEWFBRg9erVaNeunew2AYCrqysCAgIUHVvas88+i169ehn/rXJzc2V/+qs12NmjRw/88MMPqvy9AI/JGcSGDRtQr149DB482OQPWu7/BDVOLQsLC/Gf//wH/fv3l/WzRYKDg/H777/j+eefN+mzyg2c999/H61atcKoUaMgSRJ27dqFS5cuYc2aNbLbtHz5ckRFRcHNzc14xqbRaGT1hYsVd73Wr18PR0dHjBw5UlF3bNSoUZg6darxcvCJEyewcuVKWUEzfPjwR46hyL3cDQAHDx7E4sWLcfv2bQAwdn/Pnz8vq055n/zF27y9vbFv3z6z6rz44ovIysqCnZ0d7O3tLZ4v8licQRTPgAwLC4NGo1H8P+Hll19Gy5YtjaeWEydOlH1qaWNjgzVr1qgWEL/++iv0er3iUfRiKSkpWL16tfF1UFAQfHx8FNX64YcfcOjQIYu6FsU0Gg3i4uIQFxeHdevWAYCiS8K5ubnGcACAl156CZ988omsGnPmzJH9cysSERGBzz77zOL5GWoNdkZHRytuQ3msPiAKCwuxd+9euLu7W1yreOyg5Kll6fEEc6g1IxOAait/FxYWIj093dj/TU9PR2FhoaJaTk5OqoQDUDT35IsvvsDrr78OV1dXJCcno0ePHrLr2Nvb49SpU8ZjT58+LfsMsvgy95EjR9CrVy/UrFnT+L3Tp0/LbhNQ1P194YUXFB1b0rRp0/D666+bzD0JCwvD33//Lau7oGTQ9lEeiy6GnFOsR1Hr6sPQoUNx5coVi2dkAkWPNfzjjz8wYMAAk19YuWMQe/fuxfLly/HKK68AKOpOzZgxQ9FZxLJly3Dz5k0MGjTIpEunxhwEpeLj4zF16lTjv1F+fj5WrVqlaLCzffv26NChg7HrCii/CvX555/DwcEBQ4YMsaj7CxSF+m+//QZA+WDniy++WG436onuYjz33HO4fv06mjZtquj4n376CcePH8etW7ewbNky4/acnBxFU6TVmpEJAHl5eWjWrBkuXbpkUR1fX188//zzxk/CsWPHKp4gk5CQAAAmA2PFcxjMtW3bNowbNw7h4eHl/sLOnj1bVps6duyIgwcPmlzFUNota9WqFfz8/BAQEID169ejWbNmiqfK//vf/wZQNNHJku4vUDSXpbCwEAMGDMDff/+NrKwsk2nq5ijZxXj48CH27dtn0dWexyIg/v77bwwdOhRdu3Y1+cQ2dxJQjRo1ULt2bWg0GpPjnZ2dMWHCBNntKT5VLe4jlqwplyVXP0pr06aNcQaeJeRMDxYp/jS19Dp8Xl4eatasaZwnUNxHLygoQEFBgaJPao1GgxEjRqBRo0Z4++23ERERoXg68oULFxQdV1pMTAw+//xz5OfnY8CAAUhLS8PChQuxdetWWXVKdzGmTp2KkSNHYvLkyYra9VgExNChQzF06FDFx3fv3h3du3fHq6++qsof0LVr1zBjxgycP38eGo0Gzz//PCIiIoy/vOY4e/YsunbtKlyjwtxP61mzZiEiIkI4Qi+n21M8SPbHH3+U+/3S05MfxWAw4Ouvv0aDBg3MPqY8/v7+iImJKXNTlCWf1MVnC71798aaNWsQFBSEzMxMi9ppqW3btiE6OtrYtWzZsiXu3Lljcd1r164hPT1d8fGPRUAomQ1YHldXVyxfvhz//e9/AQC9evXCe++9J/tTKCQkBCNHjsTw4cMBFN3+HRISImvufUxMDLp27YovvviizPfknM6PGzcOgDoj9IsXL8bnn39e7lmVRqPB4cOHza61aNEitGvXzuJALh4XUOuTGiiac1DM3d0dX331FaKiomTVGDduHLZt21amz6/0smLxWW5JSm5MLNmewsJC4+3eilXysz9VkZ6eLk2bNk3q0aOH1KNHD+mDDz6Q0tPTZdeZO3euNHv2bOnMmTPSmTNnpODgYCk4OFh2naFDh5q1rSrt3bvXrG1VJTo6WhozZow0fPhwKTIyUsrKyrKo3uLFi83aZo6lS5dK165dM9n25ZdfyqqRlpYmSZIkXb9+vdz/5Bo/frx09epVydfXV5Kkov93EyZMkF2nZBtu3rwpFRQUyK5R0mMREFOmTJE+++wz6ebNm1Jqaqq0cuVKafLkybLreHl5mbwuLCwss80cvr6+0pUrV4yvr169Kg0bNkx2HUmSpJiYGJM/nszMTCk2NlZRm8zZZo6goCCztpkjJSVFWrVqlTRo0CApKChIOn/+vKI65b0XHx8fRbW6d+8uDRgwwORp9Er/rfR6vZSfn6/o2JKuXLkiDRs2TOrUqZPUt29fafDgwdKff/4pu46aQSpJkvRYdDHUnAR0//5946BieTfImGP69OkYPXo0PDw8IEkSLl68aHJ1RI7NmzfD19fX+Lp+/frYvHmz2WMuxfeHZGZmmqxOlZOTo3iNivKWPbt69aqiWq6urnjzzTfx7LPPYtWqVejVq5esOS3ff/89vv/+e9y4cQNTp041bs/JyTHeYSqXTqfD0qVLERQUhNmzZ2PgwIGKr2Lo9XqEh4dj+PDhGDVqlOLb7Vu2bImoqCgkJydDkiS0aNFCURfjzJkzZbYpWaCn2GMREGpNAvL29oa/vz9ee+01AEU3EikJmj59+mD//v0m16wtXbqspPIWWRFR8/6QXbt2YefOnUhOTjZZqCY7OxstWrSQVUuSJBw7dgx79uzB5cuXMXjwYOzatUvWQC5QdDnzlVdeQUJCgnGOB1B0A1nJmZVyaDQaeHh4YPv27Xjvvfdw/fp1xVcx1q9fj+vXr2PHjh0YPnw4XnjhBQQEBODFF1+UVWfq1KlYuXIl3NzcymwzR2UEKfCYBMQ777wDX1/fMpOA5JowYQLatm2LkydPAgBmzpyJPn36qNlU2ZycnHDw4EG8+uqrAIpuH5YzQWbAgAEYMGAAjh8/rmhNzJJ69uyJ5557DosWLTKZp1CnTh2zbzsv1qdPHzg7O8PPzw+TJ0+GRqPBw4cPjVdIzL0i4u7uDnd3d/Tr10/2nACR4rMFnU6Hr7/+GkFBQRbNQ2natClmzpyJfv364YMPPsCxY8fQtGlThIaGolu3bmbVsPSsrTKCFLDymZQluwOXL182WTPBklVyLJ2/cPDgQeOSbJIk4fz581i0aBEGDBggu9aVK1cwadIk4xmRVqvFunXrzL69t9jGjRsxcuRIk8Vho6OjVVmJS4l+/foZvy6eQFTytZwrIkDRvIfo6GicP3/eZIl4JfNISq8oZjAY8Msvv+Af//iH7Fp5eXmIi4vDt99+C4PBgDFjxhjvXp09ezaOHDnyyOOLz9quXr1qcvZQfNa2YcMGWe1RMrnqUaw6IIrvZiu+1m+plJQUzJw503jJTMn8BQAYPHgw1q1bZzztTk5OxsSJE/H9998rapfBYDCZIaik7+nj44PY2FiTbXLWuihJrUWC1TRv3jwYDAacOnUKb7zxBvR6Pbp164bQ0FDZtSyde1JSr1690KNHD4wZMwZdunQx+d78+fOxZMmSRx5/48YNXL9+HYsWLUJISIhxe/FZm9zfBTVXNwesvItR3K8+d+4crly5UmYgSc7EHaDovgdL5y8ARbMES/bJmzdvblE/T6vVokGDBnj48CHS0tIAwGSdSnOUl/NyxjJK+uCDDzBo0CCLFwlWU0JCAvbt2wdvb2+8++67CAgIwKRJkxTVKjn3JC8vD+fPn8fzzz+vKCD27NkDZ2fncr9XUTgARTMfmzRpotpiQ2qubg5YeUD861//wuzZs5GSklLmjkslp6kZGRkmg2/Dhw9XtMZB//79sX79euPiHnv27EH//v3x4MEDSJIka+LViRMnEBwcjPT0dNjY2CA/Px/169eXPdGmefPm2LJlC958801IkoQtW7agWbNmct8agKJBYXOXSqsqxVO3tVotcnNz4eDgoHiGYOmp5H/88Qe+/PJLRbWcnZ1x9epVXLhwAXl5ecbtJa9MmSM7OxubNm0q04WS+/up5urmgJUHREBAAAICAjB9+nTjTTGWsLGxwdWrV439+6SkJEUpu3btWgBFp20l+9dr1qyRPf03IiICW7duxfTp0xETE4Pdu3fj+vXrsts0f/58zJo1CytWrIBGo0GXLl3w/vvvy64DAJ07d8aFCxdUucVeLfXq1cPdu3fRu3dvBAYGokGDBqqs4A0UnYmeO3dO0bHbt2/Hzp07cfv2bXTo0AFnzpzBP/7xD9kBMW/ePLi5uSE5ORlTp05FdHS0otWy1FzdHLDygCj2/PPPl9mmZB0HteYvFI9h3L17F6dPn4arq6tFf0wtWrRAQUGB8SYiPz8/k+nA5nBxccH27dvx119/Yc+ePdi3bx/mzZuHgwcPml2j+H6OgoIC7NmzBy1atDC5hbk6xyA2btwIrVaL6dOn47vvvkNOTo7sP8JiJccgCgsLkZCQoPiOx127diEqKgpvvPEGvvzyS1y6dMn4ASLHn3/+idWrV+Pw4cPw8vLCq6++irFjx8quo+bq5sBjEhBxcXFlwqC8bRXp06cP9Hq9yQKjcuYvzJw5E+PHj4e7uzuysrLg4+ODOnXqIDMzE9OnTzc+zUiO4l9MFxcXHDlyBE2aNMHdu3dl1SgoKMDhw4cRHR2N3377DQUFBdi8eTM6deokq05lrLikluIzPRsbG8XBABSN8k+bNg3NmzdHnTp1YGtri2bNmin+A6pZsyaeeeYZFBYWQpIktGnTBsnJyYrqAEX3ZGRlZaFevXrIyMiQXcfLy8v4uAI1WHVAqL2OA1D0HIqePXsqWmA0MTHReKYQGxsLNzc3bN68GTdv3sS7776rKCDGjh2Lu3fvYurUqZgxYways7Nl3Vzz8ccfY//+/Wjbti2GDRuGVatWYciQIbLDAfh/t7FbEzXXkYyLi8PcuXNRu3ZtpKSkYM2aNRbNEQCKFobJz8+Hu7s7IiIioNPpFE3ia968ObKysoyT+RwcHBR1MdS6sbGYVQeE2us4WLrAaMlTtrNnzxrnPTRq1EjRTLzbt2+jefPmqF27Njp27IgdO3bg888/x6JFi8year1z50507twZEyZMMM7es+RRa0D5f5QODg7o3Lkzxo8fb/EaD3KoeVazfv167NixAx4eHjh58iTWrl1rcUCEhoYiPz8fwcHBWLFiBa5fv66o21r8cJu33noLHTp0QHZ2Nnr37i27TnJyMubOnYu0tDQcOXIE586dw5EjRxSPRz0WN2tdvHhRlToDBgyQzp49KxkMBkXH+/r6Sjdv3pRyc3OlHj16SJcvXzZ+b9CgQbJq7dq1S2rXrp30z3/+U/Ly8pL+53/+R+rWrZs0depUWTfp3L17V4qMjJSGDRsm9evXT1q1apX08ssvy2pLaREREdKUKVOkQ4cOSYcOHZLef/99adGiRdLcuXOlmTNnWlS7OpW+41bpzV5qKygoUHyzWGnjxo2Tjh49anyvBoNBGjJkiOJ6Vn0GUaxNmzY4fvx4mUtAU6ZMkVXH0gVGJ0yYAF9fX9SoUQNdu3Y1zsP4v//7P9nzFrZu3YqYmBi0bt0aZ8+exdixY7F8+XLZzzOoW7cuRo8ejdGjR+PChQuIjo7Gw4cPMXr0aHh7e2PUqFGy6gFFN/fs3LnT+Lpv374YNWoUdu7ciSFDhsiupwY1FsTJz883mU+Tl5dn8lrOvJqKzhLkLKmn1WrxzDPP4OHDh4ofAVgsOzsbffr0wYoVKwAUjdlYsmL6YxEQn376KRISEvDHH3+gf//+OHz4sKxTw+K7NgcOHIhvvvlG8QKjgwcPRrdu3XDnzh2TqxY6nU72tWdbW1vjdPGuXbvC1dXV4oeduLu7Y/78+Zg9ezYOHTqEPXv2KAqIzMxMk1/WvLw83L17FxqNxqIJYZYo2dV4+PAh9u/fL5ygJPLgwYMyA9vFr+XOq7FkmcHytGjRAqNHj4anp6dJbbmLF2u1WuTn5xvDNC0tzaLl+B+LgDh69ChiYmLg5+eHhQsXYvLkybIWji1erqz4k8KSBUadnJzg5ORksk3JNefSn2Y2NjaKP81Kq1GjBgYPHozBgwcrOn7w4MHw9/c3Hn/gwAF4enri77//Vn1ZdXOVHkDt1asX3njjDVk1KrovQo7is9fMzEyLl9UDima9tm7dWvFt9cUCAgIwZcoUZGZmYvXq1di7d6/sS+YlWfW9GMWKn6np4+OD3bt3o0aNGhYtha/W/AVLlLyZqTQls0TVduTIEeMK2d27d39ke6tDdnY2hg0bhkOHDlXLzz958iSmTZuGu3fvolGjRli3bh08PDwU18vJySnzLJLytpnjzJkz+M9//gNJktCvXz+z7ygtz2NxBlG7dm3k5uaiS5cuCA4OhpOTk6xT3cqYv2ApNT/NKkO/fv2sKhRKjkEUFhbi+vXreOutt6qtPcuWLcOSJUvQs2dPxMXFYfny5eWuL2quf/3rX2Wey1HetoqcOXMG3bp1sygUSnosAmLFihXQarWYM2cOtmzZguzsbFkTW86dO6f6/IUnUUREBGbNmoWgoKByBwSVTiZSQ8kxCK1WC1dXV9ljEGoyGAzGxy/6+fkpuqcHKJrklp+fj8LCQuO9PEDRjEglK54tXboU2dnZ8PX1hZ+fn8VPbnssAuLZZ581fq3kDr6SZxtqzF94UhXfINa3b1/k5+db/LxQNVnjJK6Sf9CSJJm8Nnfge8OGDcZ7eDp37gygqItZu3ZtRWdI0dHRuHjxIvbu3YsRI0agdevW8PPzUzy70qrHIESfZMXM/UQbNmyY8TFrr7zyCiIjI42DgIMHD1a8jsOTpuT6EUofRVdZzpw5gxUrViAlJQUGg8Hip1Zbyt3dvcxCOMWUPK9j4cKFCAkJUXV8LC8vD4sXL0ZUVJSi54cAVn4G0bdvX2RlZUGSJNja2sLBwUFRHTXnLzzJSj/fwZrMnz8f06ZNQ/v27S26bKcWtZ7TUTw+FhISotr42KVLlxATE4P9+/ejVatWCA8PV9w+qw6IWrVq4bPPPkPt2rWRl5eH1atXK5oaq+b8hSfZw4cPjZdaS08iAiy79GqpunXrKr5sW1VOnz4tuyuk9vjYsGHDcP/+ffj6+mLnzp3Q6XSyji/NqgNCzbnzas1feJKVnkhU8uvqvvTq5eWFb7/9FoMHD7b4KdqVZenSpbK7ZWqPj3344Yfo2rWr7ONErDogbGxsjNeWX3zxRXzyySfV3KInmzVfenV0dMRHH32EhQsXArDs2ZyVRWm3LC0tDfXq1cPp06cRFBRk3F7ytoKKlFzjorw1N5UspwdYeUCoOXeeHm8rVqzA9u3b0a5dO6sYgyiPkqnyao2PFc/ByM/PR3x8vPGZqJcuXULHjh0VB4RVX8Ww9tmGVHVGjRqFHTt2VHczypWTk4M///xT0foNQNFt/8XjYyXvoTAYDLIH0T/44AOMGzfOuB5IfHw8tm3bhuXLlytqm1UHBFGxzz77DPn5+WVutKvus8ijR48iJCQEWq0WR44cQUJCAtauXSv7eRZqKe8WBEtuS7DqLgZRse+++w4ATOasWMNZ5KpVq7B7927jgG6HDh3KfUpWVbG3t0dsbKzxkZLfffedRQO5DAh6LFjzAGrpq2PF60tWh48//hizZ8/Ghx9+CI1GgzZt2iA4OFhxPesc7SH6/xU/ayI3N7fc/6pb7dq1cefOHePYwalTpxRP6FNDq1atsGfPHhw4cAATJkyQvcZpaRyDIKtWPOW75NRmpWt5VIb4+HiEhobi+vXrcHd3R3JyMtavX4/27dtXeVvUWt28JAYEPVasYS2P0rKzs/HLL78AKFqcqG7dulXehtKrmw8cOBBDhgyxuGvGMQiyata4lkdpDg4OiucZqKUyVjcHGBBk5ax1LY8XX3yx3D/A6rrL9NixY9i3bx+WLVuGu3fvwtfXV/HDm0tiQJBVs9a1PKKjo6vtZ5enMlY3B3gVgx4DaWlpePDgQZm7JeXcq6C2Jk2aGP9zcXHB/fv3cf/+fbi4uFTbwr7Filc3//HHHzFmzBiL5orwDIKsmrWv5ZGQkICgoCDUrFkTkiShoKAAq1evVjztWk2Wrm4O8CoGPQbUvFdBbaNGjcLUqVONyxCcOHECK1eutNr7RuRiF4OsnpOTEzw8PEzGHFxcXKo9HICiCVwl1yh56aWXrGICl1oYEEQWsLe3x6lTp4yvT506ZVWL2FiKXQwiC8THx2Pq1KkmYxARERGqrupUnRgQRArdvn0baWlpaNu2LZKSknD37l3ExcVBr9fj559/ru7mqYJdDCIFoqKi0LdvX7z77rvw8/NDSkoKJk6ciMzMTKubI2EJXuYkUmDr1q2IiYlB69atcfbsWYwdOxbLly+3+Ant1oZnEEQK2NraonXr1gCArl27wtXV9YkLB4BnEESKlF5Q2cbG5olcUJmDlEQKPC0LKjMgiEiIYxBEJMSAICIhBgQRCfEqBgEA9u/fj61bt+Ly5cuwt7dH06ZN4evri4CAgGpdmIWqF88gCJs3b8aSJUvwzjvv4Pjx4/jvf/+LsLAw/PLLL8jPz1f1Z6mxDBpVHV7FeMplZ2ejd+/eCA8Ph6enZ7n75OXl4d///je+//575OXlYcCAAZg3bx7s7Oxw6tQpzJo1C2+++SY2bdoErVaL6dOnY/jw4QCA4OBg1KpVC3/99Rd+/vlnrFu3Dm5ubli8eDF+/vlnPPPMM3jzzTcxduzYqnzbZCaeQTzlfv31V+Tl5aF///7CfT799FMkJSVh7969OHjwIG7duoW1a9cav3/nzh1kZ2fjxx9/xJIlS7Bw4ULcvXvX+H29Xo/33nsPv/zyC7p06YKJEyeibdu2+PHHH7Ft2zZs27YNx44dq9T3ScowIJ5ymZmZaNCgAWxt/99w1KhRo9CtWzd07NgRp0+fxq5duzBv3jzUr18fderUwbvvvov9+/cb97e1tcXkyZNRo0YNvPzyy3jmmWeQlJRk/H7//v3RtWtX2NjY4NKlS8jIyMCUKVNQs2ZNuLq6YuTIkYiLi6vS903m4SDlU65+/frIzMxEQUGBMSSKl0vr06cP7ty5g9zcXPj5+RmPkSQJhYWFJjVKBoy9vT3u379vfK3T6Yxf37hxA7du3UK3bt2M2wwGg8lrsh4MiKdcly5dULNmTRw+fLjcMYgGDRrAzs4O+/fvh4uLi8U/T6fToWnTpjh48KDFtajysYvxlKtbty4mT56MsLAw/PDDD8jJyUFhYSHOnz+P3Nxc2NjYYMSIEfj444+Rnp4OoGjBWKVjBh07dkTt2rWxceNGPHjwAAaDAZcuXUJ8fLyab4tUwjMIQmBgIFxcXPDFF19gzpw5sLe3h6urK2bOnIkuXbqgc+fOWLt2LUaOHInMzEy4uLjgjTfeQO/evWX/LK1Wiw0bNiA8PBz9+/dHXl4eWrRogWnTpqn/xshivMxJRELsYhCREAOCiIQYEEQkxIAgIiEGBBEJMSCISIgBQURCDAgiEmJAEJHQ/weSGwRQpffDvQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# NA(북미지역)은 Platform, Shooter 장르를 선호"
      ],
      "metadata": {
        "id": "QpFToBLnrKlw"
      },
      "execution_count": 343,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### EU (유럽지역) ####"
      ],
      "metadata": {
        "id": "7TVyzEgsiC31"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "EU_ratio = df.groupby('Genre')['EU_Sales'].mean().sort_values(ascending=False)\n",
        "EU_ratio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "buW2UEKoiOdr",
        "outputId": "e652e6a8-481a-4528-bfb9-b3e9db9f03c7"
      },
      "execution_count": 344,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Genre\n",
              "Shooter         0.347579\n",
              "Platform        0.319040\n",
              "Racing          0.280767\n",
              "Sports          0.252916\n",
              "Action          0.250406\n",
              "Fighting        0.152198\n",
              "Misc            0.152013\n",
              "Simulation      0.150843\n",
              "Role-Playing    0.134178\n",
              "Puzzle          0.098226\n",
              "Strategy        0.074624\n",
              "Adventure       0.057423\n",
              "Name: EU_Sales, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 344
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "EU_ratio.plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "jG_iIyJCsUv8",
        "outputId": "69eb2d54-cd30-4ebe-9ebe-985037466117"
      },
      "execution_count": 345,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Genre'>"
            ]
          },
          "metadata": {},
          "execution_count": 345
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# EU(유럽지역)은 Shooter, Platform 장르를 선호"
      ],
      "metadata": {
        "id": "2fQlAkohsYvy"
      },
      "execution_count": 346,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### JP (일본지역) ####"
      ],
      "metadata": {
        "id": "urNS1yOPiFPO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "JP_ratio = df.groupby('Genre')['JP_Sales'].mean().sort_values(ascending=False)\n",
        "JP_ratio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D8MHseVziO-U",
        "outputId": "0e20fe51-a010-421b-f8c7-9e1fef367e0a"
      },
      "execution_count": 347,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Genre\n",
              "Role-Playing    0.255807\n",
              "Platform        0.206752\n",
              "Fighting        0.131847\n",
              "Puzzle          0.109532\n",
              "Sports          0.091958\n",
              "Simulation      0.084953\n",
              "Strategy        0.080234\n",
              "Action          0.076095\n",
              "Misc            0.075893\n",
              "Racing          0.066451\n",
              "Adventure       0.046824\n",
              "Shooter         0.042240\n",
              "Name: JP_Sales, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 347
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "JP_ratio.plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "H9LcPovgsfc2",
        "outputId": "7bc51a61-1c20-4b11-bb43-45ac38e9ee97"
      },
      "execution_count": 348,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Genre'>"
            ]
          },
          "metadata": {},
          "execution_count": 348
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# JP(일본지역)은 Role-Playing, Platform 장르를 선호"
      ],
      "metadata": {
        "id": "rrn-yU46sh8X"
      },
      "execution_count": 349,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Other (기타지역) ####"
      ],
      "metadata": {
        "id": "tP-_XYYtiHYm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Other_ratio = df.groupby('Genre')['Other_Sales'].mean().sort_values(ascending=False)\n",
        "Other_ratio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zwolf5SoiPOz",
        "outputId": "d9bd9b3f-eb0e-41e9-ded1-bd03cd07af6b"
      },
      "execution_count": 350,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Genre\n",
              "Shooter         0.114050\n",
              "Racing          0.091379\n",
              "Sports          0.090137\n",
              "Action          0.089731\n",
              "Platform        0.081840\n",
              "Fighting        0.055115\n",
              "Misc            0.053060\n",
              "Simulation      0.041821\n",
              "Role-Playing    0.041636\n",
              "Puzzle          0.024152\n",
              "Strategy        0.018698\n",
              "Adventure       0.015082\n",
              "Name: Other_Sales, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 350
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Other_ratio.plot(kind='bar')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 633
        },
        "id": "N4aIeZUyszhA",
        "outputId": "0bdc4312-30c5-4b18-d070-cc5c61cfd11b"
      },
      "execution_count": 351,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Genre'>"
            ]
          },
          "metadata": {},
          "execution_count": 351
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Other(기타지역)은 Shooter 장르를 선호"
      ],
      "metadata": {
        "id": "gorpccL9s0qk"
      },
      "execution_count": 352,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 그래프 ####"
      ],
      "metadata": {
        "id": "B1XJlB4GK0K3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터를 한번에 나타내기 위해 같은 데이터프레임으로 만들어주기\n",
        "NA_ratio = pd.DataFrame(NA_ratio)\n",
        "EU_ratio = pd.DataFrame(EU_ratio)\n",
        "JP_ratio = pd.DataFrame(JP_ratio)\n",
        "Other_ratio = pd.DataFrame(Other_ratio)\n",
        "\n",
        "ratio = pd.concat([NA_ratio, EU_ratio, JP_ratio, Other_ratio], axis=1)\n",
        "ratio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "bmLq6Ut5nYb7",
        "outputId": "8469ff7e-d5c9-459a-8d45-c025ec97edab"
      },
      "execution_count": 353,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              NA_Sales  EU_Sales  JP_Sales  Other_Sales\n",
              "Genre                                                  \n",
              "Platform      0.707888  0.319040  0.206752     0.081840\n",
              "Shooter       0.645735  0.347579  0.042240     0.114050\n",
              "Sports        0.454251  0.252916  0.091958     0.090137\n",
              "Racing        0.423453  0.280767  0.066451     0.091379\n",
              "Action        0.418182  0.250406  0.076095     0.089731\n",
              "Fighting      0.335817  0.152198  0.131847     0.055115\n",
              "Misc          0.288067  0.152013  0.075893     0.053060\n",
              "Simulation    0.242329  0.150843  0.084953     0.041821\n",
              "Puzzle        0.235848  0.098226  0.109532     0.024152\n",
              "Role-Playing  0.233699  0.134178  0.255807     0.041636\n",
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            ]
          },
          "metadata": {},
          "execution_count": 353
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 평균으로만 선호도 그래프 구하기\n",
        "ratio.T.plot(kind='bar', figsize=(18, 6), title=\"Preference of game genre by region\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "id": "26nXshCSo9Fw",
        "outputId": "902ea138-9b6a-4aa6-a2da-f349a9368efe"
      },
      "execution_count": 354,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Preference of game genre by region'}>"
            ]
          },
          "metadata": {},
          "execution_count": 354
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# NA (북미지역) : Platform, Shooter\n",
        "# EU (유럽지역) : Shooter, Platform\n",
        "# JP (일본지역) : Role-Playing, Platform\n",
        "# Other (기타지역) : 대체적으로 비슷"
      ],
      "metadata": {
        "id": "OxdfD1nNIOhm"
      },
      "execution_count": 355,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2) 나라에 따른 장르 선호도 ###"
      ],
      "metadata": {
        "id": "yp539drULNtL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### NA (북미지역) #####"
      ],
      "metadata": {
        "id": "i8ZXCIcEXFUv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "((ratio['NA_Sales']/ratio.sum(axis=0)[0])).plot(kind='pie',autopct='%.1f%%', title=\"Preference Ratio of NA_Sales\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "x8ZbPoIlWWrc",
        "outputId": "15526ba0-7f52-4bcc-99b8-3a70a2685335"
      },
      "execution_count": 356,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Preference Ratio of NA_Sales'}, ylabel='NA_Sales'>"
            ]
          },
          "metadata": {},
          "execution_count": 356
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Platform, Shooter, Sports, Racing : 비율의 절반 차지"
      ],
      "metadata": {
        "id": "RpuYbsZoXQ_u"
      },
      "execution_count": 357,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### EU (유럽지역) #####"
      ],
      "metadata": {
        "id": "ok4Ip1pgXG2l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "((ratio['EU_Sales']/ratio.sum(axis=0)[1])).plot(kind='pie',autopct='%.1f%%', title=\"Preference Ratio of EU_Sales\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "b9ez5pthT0-H",
        "outputId": "3f89f779-244f-4cd0-ed00-d3d23d319f7b"
      },
      "execution_count": 358,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Preference Ratio of EU_Sales'}, ylabel='EU_Sales'>"
            ]
          },
          "metadata": {},
          "execution_count": 358
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Shooter, Platform, Racing, Sports : 비율의 절반 차지"
      ],
      "metadata": {
        "id": "2_ol96E7XUTM"
      },
      "execution_count": 359,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### JP (일본지역) #####"
      ],
      "metadata": {
        "id": "nku_2-gnXKbD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "((ratio['JP_Sales']/ratio.sum(axis=0)[2])).plot(kind='pie',autopct='%.1f%%', title=\"Preference Ratio of JP_Sales\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "XXvoyf_xWg-o",
        "outputId": "4b2d7b74-8bc7-439d-e5fd-446fe8cd775a"
      },
      "execution_count": 360,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Preference Ratio of JP_Sales'}, ylabel='JP_Sales'>"
            ]
          },
          "metadata": {},
          "execution_count": 360
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Role-Playing, Platform, Fighting, Puzzle : 비율의 절반 차지"
      ],
      "metadata": {
        "id": "SxZBlSWDXYpU"
      },
      "execution_count": 361,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Other (기타지역) #####"
      ],
      "metadata": {
        "id": "_sG2pab2XMhD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "((ratio['Other_Sales']/ratio.sum(axis=0)[3])).plot(kind='pie',autopct='%.1f%%', title=\"Preference Ratio of Other_Sales\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "wK5ejPM1Wkmj",
        "outputId": "608a81b9-b6ff-4e03-f519-d0226d6a717e"
      },
      "execution_count": 362,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Preference Ratio of Other_Sales'}, ylabel='Other_Sales'>"
            ]
          },
          "metadata": {},
          "execution_count": 362
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Shooter, Racing, Sports, Action : 비율의 절반 차지"
      ],
      "metadata": {
        "id": "pGeAzrXEXhG1"
      },
      "execution_count": 363,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 결과 ####"
      ],
      "metadata": {
        "id": "RVXeAW8kpmE5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# NA(북미지역) : Platform, Shooter, Sports, Racing\n",
        "# EU(유럽지역) : Shooter, Platform, Racing, Sports\n",
        "# JP(일본지역) : Role-Playing, Platform, Fighting, Puzzle\n",
        "# Other(기타지역) : Shooter, Racing, Sports, Action\n",
        "\n",
        "# >> 지역별로 선호하는 게임의 장르가 Platform, Shooter, Racing, Sports로 비슷하다고 생각"
      ],
      "metadata": {
        "id": "Ipp_XnrbNEqj"
      },
      "execution_count": 364,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Q1) 지역은 어떻게 구분했나요?\n",
        "# A1) NA, EU, JP, Other로 구분\n",
        "\n",
        "# Q2) 지역별로 선호하는 게임의 장르를 파악했나요?\n",
        "# A2) NA(북미지역) : Platform, Shooter, Sports, Racing\n",
        "#     EU(유럽지역) : Shooter, Platform, Racing, Sports\n",
        "#     JP(일본지역) : Role-Playing, Platform, Fighting, Puzzle\n",
        "#     Other(기타지역) : Shooter, Racing, Sports, Action\n",
        "# >>> 지역에 관계없이 대체적으로 Platform, Shooter, Racing, Sports 장르를 선호하는 것 같다. (단, 일본은 Role-Playing, Platform, Fighting, Puzzle 장르 선호)\n",
        "\n",
        "# Q3) 지역별로 선호하는 게임의 장르가 왜 같다고 생각했나요?\n",
        "# A3) 거의 모든 지역에서 절반에 해당하는 비율에 Platform, Shooter, Racing, Sports 장르가 있기 때문"
      ],
      "metadata": {
        "id": "8XbW1_Nknpwq"
      },
      "execution_count": 365,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3) 연도별 게임의 트렌드 ###"
      ],
      "metadata": {
        "id": "LH-sZJKAJdGb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 연간 장르별 게임 출시량 ####"
      ],
      "metadata": {
        "id": "rkqE_6mLy3AS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df1 = df.copy()\n",
        "df1['number_of_game'] = 1\n",
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 852
        },
        "id": "fiU63PFwy2dP",
        "outputId": "33e65f95-8f35-410a-86f5-d098e7b091c1"
      },
      "execution_count": 366,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name  Year      Genre  \\\n",
              "0                                      The Munchables  2009     Action   \n",
              "1      Otome wa Oanesama Boku ni Koi Shiteru Portable  2010  Adventure   \n",
              "2                    Deal or No Deal: Special Edition  2010       Misc   \n",
              "3                              Power Pro Kun Pocket 8  2005     Sports   \n",
              "4                      Samurai Warriors: State of War  2005     Action   \n",
              "...                                               ...   ...        ...   \n",
              "12141                                          iCarly  2009  Adventure   \n",
              "12142                      iCarly 2: iJoin The Click!  2010  Adventure   \n",
              "12143                                          nail'd  2010     Racing   \n",
              "12144                       pro evolution soccer 2011  2010     Sports   \n",
              "12145                    uDraw Studio: Instant Artist  2011       Misc   \n",
              "\n",
              "                          Publisher  NA_Sales  EU_Sales  JP_Sales  \\\n",
              "0                Namco Bandai Games      0.17      0.00      0.00   \n",
              "1                         Alchemist      0.00      0.00      0.02   \n",
              "2                         Zoo Games      0.04      0.00      0.00   \n",
              "3      Konami Digital Entertainment      0.00      0.00      0.14   \n",
              "4                        Tecmo Koei      0.07      0.00      0.11   \n",
              "...                             ...       ...       ...       ...   \n",
              "12141                    Activision      1.09      0.01      0.00   \n",
              "12142                    Activision      0.34      0.02      0.00   \n",
              "12143                   Deep Silver      0.16      0.04      0.00   \n",
              "12144  Konami Digital Entertainment      0.55      2.28      0.91   \n",
              "12145                           THQ      0.09      0.10      0.00   \n",
              "\n",
              "       Other_Sales  Total_Sales  number_of_game  \n",
              "0             0.01         0.18               1  \n",
              "1             0.00         0.02               1  \n",
              "2             0.00         0.04               1  \n",
              "3             0.00         0.14               1  \n",
              "4             0.01         0.19               1  \n",
              "...            ...          ...             ...  \n",
              "12141         0.08         1.18               1  \n",
              "12142         0.03         0.39               1  \n",
              "12143         0.03         0.23               1  \n",
              "12144         0.78         4.52               1  \n",
              "12145         0.02         0.21               1  \n",
              "\n",
              "[12146 rows x 10 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-3ceaaded-f144-4e48-b24e-8bbee08db3f9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Name</th>\n",
              "      <th>Year</th>\n",
              "      <th>Genre</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>NA_Sales</th>\n",
              "      <th>EU_Sales</th>\n",
              "      <th>JP_Sales</th>\n",
              "      <th>Other_Sales</th>\n",
              "      <th>Total_Sales</th>\n",
              "      <th>number_of_game</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Munchables</td>\n",
              "      <td>2009</td>\n",
              "      <td>Action</td>\n",
              "      <td>Namco Bandai Games</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.18</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Otome wa Oanesama Boku ni Koi Shiteru Portable</td>\n",
              "      <td>2010</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Alchemist</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Deal or No Deal: Special Edition</td>\n",
              "      <td>2010</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Zoo Games</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Power Pro Kun Pocket 8</td>\n",
              "      <td>2005</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Konami Digital Entertainment</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Samurai Warriors: State of War</td>\n",
              "      <td>2005</td>\n",
              "      <td>Action</td>\n",
              "      <td>Tecmo Koei</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.19</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12141</th>\n",
              "      <td>iCarly</td>\n",
              "      <td>2009</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Activision</td>\n",
              "      <td>1.09</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.08</td>\n",
              "      <td>1.18</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12142</th>\n",
              "      <td>iCarly 2: iJoin The Click!</td>\n",
              "      <td>2010</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>Activision</td>\n",
              "      <td>0.34</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.39</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12143</th>\n",
              "      <td>nail'd</td>\n",
              "      <td>2010</td>\n",
              "      <td>Racing</td>\n",
              "      <td>Deep Silver</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.23</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12144</th>\n",
              "      <td>pro evolution soccer 2011</td>\n",
              "      <td>2010</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Konami Digital Entertainment</td>\n",
              "      <td>0.55</td>\n",
              "      <td>2.28</td>\n",
              "      <td>0.91</td>\n",
              "      <td>0.78</td>\n",
              "      <td>4.52</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12145</th>\n",
              "      <td>uDraw Studio: Instant Artist</td>\n",
              "      <td>2011</td>\n",
              "      <td>Misc</td>\n",
              "      <td>THQ</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.21</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12146 rows × 10 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3ceaaded-f144-4e48-b24e-8bbee08db3f9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3ceaaded-f144-4e48-b24e-8bbee08db3f9');\n",
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              "                                                     [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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 366
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 게임출시량을 기준으로 연간 출시된게임의 최다장르 구하기\n",
        "year_max_genre = df1.groupby(['Year', 'Genre'])['number_of_game'].sum().reset_index()\n",
        "year_max_genre"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "JyMqslb4z6KK",
        "outputId": "d48d6ea6-c2a4-414f-bc01-db74089c95d8"
      },
      "execution_count": 367,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Year         Genre  number_of_game\n",
              "0    1980        Action               1\n",
              "1    1980      Fighting               1\n",
              "2    1980          Misc               4\n",
              "3    1980       Shooter               2\n",
              "4    1981        Action              25\n",
              "..    ...           ...             ...\n",
              "383  2016        Sports              15\n",
              "384  2016      Strategy               8\n",
              "385  2017        Action               1\n",
              "386  2017  Role-Playing               1\n",
              "387  2020    Simulation               1\n",
              "\n",
              "[388 rows x 3 columns]"
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              "      <th></th>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1980</td>\n",
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              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1980</td>\n",
              "      <td>Shooter</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1981</td>\n",
              "      <td>Action</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>383</th>\n",
              "      <td>2016</td>\n",
              "      <td>Sports</td>\n",
              "      <td>15</td>\n",
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              "    <tr>\n",
              "      <th>384</th>\n",
              "      <td>2016</td>\n",
              "      <td>Strategy</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>385</th>\n",
              "      <td>2017</td>\n",
              "      <td>Action</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>386</th>\n",
              "      <td>2017</td>\n",
              "      <td>Role-Playing</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>387</th>\n",
              "      <td>2020</td>\n",
              "      <td>Simulation</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>388 rows × 3 columns</p>\n",
              "</div>\n",
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              "\n",
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              "\n",
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              "      background-color: #434B5C;\n",
              "      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",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fbdfb566-482b-403d-97ee-08a2219c22d2');\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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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "condition = year_max_genre['number_of_game'] == year_max_genre.groupby(['Year'])['number_of_game'].transform(max)\n",
        "year_max_genre = year_max_genre[condition]\n",
        "year_max_genre.columns = ['Year', 'Genre', 'number_of_game']\n",
        "year_max_genre.reset_index(drop=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "C7nXyg-Z1Cd6",
        "outputId": "3e647706-0ad0-4b78-bf9b-fbcc319cd4d9"
      },
      "execution_count": 368,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Year         Genre  number_of_game\n",
              "0   1980          Misc               4\n",
              "1   1981        Action              25\n",
              "2   1982        Action              18\n",
              "3   1983        Action               7\n",
              "4   1984        Puzzle               3\n",
              "5   1984        Racing               3\n",
              "6   1984       Shooter               3\n",
              "7   1985      Platform               4\n",
              "8   1985        Puzzle               4\n",
              "9   1986        Action               6\n",
              "10  1987        Sports               4\n",
              "11  1988      Platform               4\n",
              "12  1989        Puzzle               5\n",
              "13  1990        Action               3\n",
              "14  1990      Platform               3\n",
              "15  1990        Sports               3\n",
              "16  1991        Sports               7\n",
              "17  1992      Fighting               6\n",
              "18  1992      Platform               6\n",
              "19  1993      Fighting              11\n",
              "20  1993      Platform              11\n",
              "21  1994        Sports              22\n",
              "22  1995      Fighting              28\n",
              "23  1995        Sports              28\n",
              "24  1996        Sports              51\n",
              "25  1997        Sports              46\n",
              "26  1998        Sports              68\n",
              "27  1999        Sports              60\n",
              "28  2000        Sports              71\n",
              "29  2001        Sports              69\n",
              "30  2002        Sports             122\n",
              "31  2003        Action              94\n",
              "32  2004        Action              82\n",
              "33  2005        Action             113\n",
              "34  2006        Action             132\n",
              "35  2007          Misc             131\n",
              "36  2008          Misc             158\n",
              "37  2009          Misc             149\n",
              "38  2010          Misc             155\n",
              "39  2011          Misc             142\n",
              "40  2012        Action             184\n",
              "41  2013        Action              79\n",
              "42  2014        Action              87\n",
              "43  2015        Action             147\n",
              "44  2016        Action              71\n",
              "45  2017        Action               1\n",
              "46  2017  Role-Playing               1\n",
              "47  2020    Simulation               1"
            ],
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1984</td>\n",
              "      <td>Racing</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1984</td>\n",
              "      <td>Shooter</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1985</td>\n",
              "      <td>Platform</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1985</td>\n",
              "      <td>Puzzle</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1986</td>\n",
              "      <td>Action</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1987</td>\n",
              "      <td>Sports</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1988</td>\n",
              "      <td>Platform</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1989</td>\n",
              "      <td>Puzzle</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1990</td>\n",
              "      <td>Action</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1990</td>\n",
              "      <td>Platform</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1990</td>\n",
              "      <td>Sports</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1991</td>\n",
              "      <td>Sports</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1992</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1992</td>\n",
              "      <td>Platform</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1993</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>1993</td>\n",
              "      <td>Platform</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>1994</td>\n",
              "      <td>Sports</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>1995</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>1995</td>\n",
              "      <td>Sports</td>\n",
              "      <td>28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1996</td>\n",
              "      <td>Sports</td>\n",
              "      <td>51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>1997</td>\n",
              "      <td>Sports</td>\n",
              "      <td>46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>1998</td>\n",
              "      <td>Sports</td>\n",
              "      <td>68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>1999</td>\n",
              "      <td>Sports</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2000</td>\n",
              "      <td>Sports</td>\n",
              "      <td>71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2001</td>\n",
              "      <td>Sports</td>\n",
              "      <td>69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2002</td>\n",
              "      <td>Sports</td>\n",
              "      <td>122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2003</td>\n",
              "      <td>Action</td>\n",
              "      <td>94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2004</td>\n",
              "      <td>Action</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2005</td>\n",
              "      <td>Action</td>\n",
              "      <td>113</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2006</td>\n",
              "      <td>Action</td>\n",
              "      <td>132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2007</td>\n",
              "      <td>Misc</td>\n",
              "      <td>131</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2008</td>\n",
              "      <td>Misc</td>\n",
              "      <td>158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2009</td>\n",
              "      <td>Misc</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2010</td>\n",
              "      <td>Misc</td>\n",
              "      <td>155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2011</td>\n",
              "      <td>Misc</td>\n",
              "      <td>142</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2012</td>\n",
              "      <td>Action</td>\n",
              "      <td>184</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2013</td>\n",
              "      <td>Action</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2014</td>\n",
              "      <td>Action</td>\n",
              "      <td>87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2015</td>\n",
              "      <td>Action</td>\n",
              "      <td>147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2016</td>\n",
              "      <td>Action</td>\n",
              "      <td>71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2017</td>\n",
              "      <td>Action</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2017</td>\n",
              "      <td>Role-Playing</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2020</td>\n",
              "      <td>Simulation</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ad83e302-4811-417e-93a1-c8cc2dcbea6d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "    .colab-df-convert:hover {\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const element = document.querySelector('#df-ad83e302-4811-417e-93a1-c8cc2dcbea6d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 368
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(x='Year', y='number_of_game', data=year_max_genre, hue='Genre')\n",
        "plt.title('Number of Released Genre by Year')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "id": "KTdsrLAO1duM",
        "outputId": "2de463b0-b920-4f10-a2ff-db47242e86c2"
      },
      "execution_count": 369,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Number of Released Genre by Year')"
            ]
          },
          "metadata": {},
          "execution_count": 369
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 1990년대엔 Sports 장르가 많이 출시되었지만, 2000년대 초반부턴 Action 장르가 많이 출시됨"
      ],
      "metadata": {
        "id": "aZlhr3kr1vyy"
      },
      "execution_count": 370,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 연간 최대출고량 ####"
      ],
      "metadata": {
        "id": "TxzNanIVyt-D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 총 출고량을 기준으로 연간 최대출고량 구하기\n",
        "year_max_sales = df.groupby(['Year', 'Genre'])['Total_Sales'].sum().reset_index()\n",
        "year_max_sales"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "_NTfWBptmQbp",
        "outputId": "e2ba18c6-1f85-4275-f872-70732a2edb73"
      },
      "execution_count": 371,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Year         Genre  Total_Sales\n",
              "0    1980        Action         0.34\n",
              "1    1980      Fighting         0.77\n",
              "2    1980          Misc         2.70\n",
              "3    1980       Shooter         7.07\n",
              "4    1981        Action        14.79\n",
              "..    ...           ...          ...\n",
              "383  2016        Sports        14.46\n",
              "384  2016      Strategy         0.52\n",
              "385  2017        Action         0.01\n",
              "386  2017  Role-Playing         0.04\n",
              "387  2020    Simulation         0.29\n",
              "\n",
              "[388 rows x 3 columns]"
            ],
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              "      <td>Role-Playing</td>\n",
              "      <td>0.04</td>\n",
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              "    <tr>\n",
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              "      <td>2020</td>\n",
              "      <td>Simulation</td>\n",
              "      <td>0.29</td>\n",
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              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 371
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "condition = year_max_sales['Total_Sales'] == year_max_sales.groupby(['Year'])['Total_Sales'].transform(max)\n",
        "year_max_sales = year_max_sales[condition]\n",
        "year_max_sales.columns = ['Year', 'Genre', 'Total_Sales']\n",
        "year_max_sales.reset_index(drop=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Y3iw_b1boQ-x",
        "outputId": "beb7c70c-f782-43bc-c1c6-1e59a9ca21f6"
      },
      "execution_count": 372,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Year         Genre  Total_Sales\n",
              "0   1980       Shooter         7.07\n",
              "1   1981        Action        14.79\n",
              "2   1982        Puzzle        10.04\n",
              "3   1983      Platform         6.93\n",
              "4   1984       Shooter        31.10\n",
              "5   1985      Platform        43.17\n",
              "6   1986        Action        13.74\n",
              "7   1987      Fighting         5.42\n",
              "8   1988      Platform        27.73\n",
              "9   1989        Puzzle        37.75\n",
              "10  1990      Platform        22.98\n",
              "11  1991      Platform         7.63\n",
              "12  1992      Fighting        15.23\n",
              "13  1993      Platform        18.68\n",
              "14  1994      Platform        28.76\n",
              "15  1995      Platform        16.69\n",
              "16  1996  Role-Playing        43.99\n",
              "17  1997        Racing        31.92\n",
              "18  1998        Sports        41.75\n",
              "19  1999  Role-Playing        47.24\n",
              "20  2000        Sports        41.24\n",
              "21  2001        Action        56.68\n",
              "22  2002        Action        86.65\n",
              "23  2003        Action        67.98\n",
              "24  2004        Action        75.94\n",
              "25  2005        Action        85.07\n",
              "26  2006        Sports       136.11\n",
              "27  2007        Action       105.99\n",
              "28  2008        Action       134.88\n",
              "29  2009        Sports       138.56\n",
              "30  2010        Action       117.42\n",
              "31  2011        Action       118.77\n",
              "32  2012        Action       120.76\n",
              "33  2013        Action       125.21\n",
              "34  2014        Action        99.01\n",
              "35  2015        Action        67.98\n",
              "36  2016        Action        19.83\n",
              "37  2017  Role-Playing         0.04\n",
              "38  2020    Simulation         0.29"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6746877a-1d68-4c5c-b4c4-237f34a26664\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Genre</th>\n",
              "      <th>Total_Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1980</td>\n",
              "      <td>Shooter</td>\n",
              "      <td>7.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1981</td>\n",
              "      <td>Action</td>\n",
              "      <td>14.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1982</td>\n",
              "      <td>Puzzle</td>\n",
              "      <td>10.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1983</td>\n",
              "      <td>Platform</td>\n",
              "      <td>6.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1984</td>\n",
              "      <td>Shooter</td>\n",
              "      <td>31.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1985</td>\n",
              "      <td>Platform</td>\n",
              "      <td>43.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1986</td>\n",
              "      <td>Action</td>\n",
              "      <td>13.74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1987</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>5.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1988</td>\n",
              "      <td>Platform</td>\n",
              "      <td>27.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1989</td>\n",
              "      <td>Puzzle</td>\n",
              "      <td>37.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1990</td>\n",
              "      <td>Platform</td>\n",
              "      <td>22.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1991</td>\n",
              "      <td>Platform</td>\n",
              "      <td>7.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1992</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>15.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1993</td>\n",
              "      <td>Platform</td>\n",
              "      <td>18.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1994</td>\n",
              "      <td>Platform</td>\n",
              "      <td>28.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1995</td>\n",
              "      <td>Platform</td>\n",
              "      <td>16.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1996</td>\n",
              "      <td>Role-Playing</td>\n",
              "      <td>43.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1997</td>\n",
              "      <td>Racing</td>\n",
              "      <td>31.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1998</td>\n",
              "      <td>Sports</td>\n",
              "      <td>41.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1999</td>\n",
              "      <td>Role-Playing</td>\n",
              "      <td>47.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2000</td>\n",
              "      <td>Sports</td>\n",
              "      <td>41.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2001</td>\n",
              "      <td>Action</td>\n",
              "      <td>56.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2002</td>\n",
              "      <td>Action</td>\n",
              "      <td>86.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2003</td>\n",
              "      <td>Action</td>\n",
              "      <td>67.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2004</td>\n",
              "      <td>Action</td>\n",
              "      <td>75.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2005</td>\n",
              "      <td>Action</td>\n",
              "      <td>85.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2006</td>\n",
              "      <td>Sports</td>\n",
              "      <td>136.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2007</td>\n",
              "      <td>Action</td>\n",
              "      <td>105.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2008</td>\n",
              "      <td>Action</td>\n",
              "      <td>134.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2009</td>\n",
              "      <td>Sports</td>\n",
              "      <td>138.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2010</td>\n",
              "      <td>Action</td>\n",
              "      <td>117.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2011</td>\n",
              "      <td>Action</td>\n",
              "      <td>118.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2012</td>\n",
              "      <td>Action</td>\n",
              "      <td>120.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2013</td>\n",
              "      <td>Action</td>\n",
              "      <td>125.21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2014</td>\n",
              "      <td>Action</td>\n",
              "      <td>99.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2015</td>\n",
              "      <td>Action</td>\n",
              "      <td>67.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2016</td>\n",
              "      <td>Action</td>\n",
              "      <td>19.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2017</td>\n",
              "      <td>Role-Playing</td>\n",
              "      <td>0.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2020</td>\n",
              "      <td>Simulation</td>\n",
              "      <td>0.29</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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          "metadata": {},
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    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(x='Year', y='Total_Sales', data=year_max_sales, hue='Genre')\n",
        "plt.title('Max Sales by Year')"
      ],
      "metadata": {
        "colab": {
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          "height": 591
        },
        "id": "kFmYlPaoxgdA",
        "outputId": "6fddeb75-852b-4ac7-a6f7-dd32e42ba710"
      },
      "execution_count": 373,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Max Sales by Year')"
            ]
          },
          "metadata": {},
          "execution_count": 373
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 1990년대 초중반엔 Platform 장르가 유행했지만, 2000년대 초반부턴 Action 장르가 유행하는 것으로 판단됨"
      ],
      "metadata": {
        "id": "2j25FXDzyZpz"
      },
      "execution_count": 374,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 결과 ####"
      ],
      "metadata": {
        "id": "Wlz3jDM8p0Eh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 1990년대엔 Sports 장르가 많이 출시되었지만, 2000년대 초반부턴 Action 장르가 많이 출시됨\n",
        "\n",
        "# 1990년대 초중반엔 Platform 장르가 유행했지만, 2000년대 초반부턴 Action 장르가 유행하는 것으로 판단됨"
      ],
      "metadata": {
        "id": "grh26hS6mjwA"
      },
      "execution_count": 375,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Q1) 트렌드는 어떤 것을 기준으로 파악했나요?\n",
        "# A1) 당해에 출고량이 높은 기준으로 파악\n",
        "\n",
        "# Q2) 연도별로 트렌드가 존재하나요?\n",
        "# A2) 1990년대 : Platform 장르 유행, 2000년대~ : Action 장르 유행"
      ],
      "metadata": {
        "id": "CbIyzhJxfbU5"
      },
      "execution_count": 376,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 4) 인기가 많은 게임에 대한 분석 및 시각화 프로세스 ###"
      ],
      "metadata": {
        "id": "Yd_tqwCttHYN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 인기가 많은 게임 ####"
      ],
      "metadata": {
        "id": "R0kGiur85PR1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['Total_Sales'].describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IxzbwjwI45lS",
        "outputId": "a70990e8-c0f8-44c7-ef3e-d3c066109af0"
      },
      "execution_count": 377,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    12146.000000\n",
              "mean         0.715487\n",
              "std          2.052205\n",
              "min          0.010000\n",
              "25%          0.060000\n",
              "50%          0.180000\n",
              "75%          0.570000\n",
              "max         82.740000\n",
              "Name: Total_Sales, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 377
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 총 출고량이 백만개 >> 인기있는 게임이라고 생각 (약 16.57프로)\n",
        "df.query('Total_Sales > 1').shape[0] / df.shape[0] * 100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_CG3V3ZBzjGT",
        "outputId": "4da9730f-8cce-45ba-f6a4-a31313b6d0c2"
      },
      "execution_count": 378,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16.556891157582744"
            ]
          },
          "metadata": {},
          "execution_count": 378
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 인기있는 게임을 새로운 변수에 저장\n",
        "popular = df.query('Total_Sales > 1')"
      ],
      "metadata": {
        "id": "sPxxoT1KtVUW"
      },
      "execution_count": 379,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 인기가 많은 게임 분석 및 시각화 ####"
      ],
      "metadata": {
        "id": "dpr4X6L0Pshv"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### by 장르 #####"
      ],
      "metadata": {
        "id": "5Riw26pgSxh_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 장르에 따른 인기가 많은 게임의 백분율 계산\n",
        "popular['Genre'].value_counts().plot(kind='pie', autopct='%.1f%%', title='Popular Games by Genre')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "iTRTe-kkujBS",
        "outputId": "4ad66490-371d-4b72-88be-131e1f658fbb"
      },
      "execution_count": 380,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Popular Games by Genre'}, ylabel='Genre'>"
            ]
          },
          "metadata": {},
          "execution_count": 380
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Action >> Sports >> Shooter >> Platform >> Role-Playing >> Racing 순으로 약 75%를 차지"
      ],
      "metadata": {
        "id": "endXMwue3yn7"
      },
      "execution_count": 381,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### by 최근 연도 #####"
      ],
      "metadata": {
        "id": "-WB0QGUXZmQn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터가 부족한 2017년을 제외한 2012~2016년도 : 최근 5년 간 인기있는 게임으로 정의\n",
        "latest_5_pop = popular.query('2012 <= Year <= 2016')"
      ],
      "metadata": {
        "id": "_sDjfvqBatFN"
      },
      "execution_count": 382,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 최근 5년간의 인기있는 게임 장르 파악\n",
        "latest_5_pop['Genre'].value_counts().plot(kind='pie', autopct='%.1f%%', title='Last-5-years Popular Games by Genre')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "wHRv-Z1ZrLzO",
        "outputId": "408268f6-6cb9-44b5-c90d-642c81d3647d"
      },
      "execution_count": 383,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:title={'center':'Last-5-years Popular Games by Genre'}, ylabel='Genre'>"
            ]
          },
          "metadata": {},
          "execution_count": 383
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Action, Shooter, Role-Playing, Sports가 74%를 차지"
      ],
      "metadata": {
        "id": "PDKDpQLcbcE_"
      },
      "execution_count": 384,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### 결과 ####"
      ],
      "metadata": {
        "id": "cHBhOHO7qnug"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Q1) 인기가 많다는 것을 어떻게 정의했나요?\n",
        "# A1) 게임 별 총 출고량을 구하고, 총 출고량이 백만(1) 이상인 값으로 정의\n",
        "\n",
        "# Q2) 해당 게임이 왜 인기가 많다고 생각했나요?\n",
        "# A2) 출고량이 많기 때문\n",
        "\n",
        "# Q3) 시각화를 통해 무엇을 나타내고자 하는지를 고려했나요?\n",
        "# A3) 인기가 많은 게임 중 장르(Genre)에 따른 게임의 백분율과, 최근(5년)동안 출고량이 높은 게임에 따른 백분율을 나타내는 원형그래프를 그렸다.\n",
        "\n",
        "# Q4) 해당 분석을 통해 어떤 인사이트를 도출할 수 있나요?\n",
        "# A4) 장르(Genre)에 따른 인기가 많은 게임 : Action, Sports, Shooter, Platform, Role-Playing, Racing 순으로 총 75%를 차지\n",
        "#     최근(5년)동안 출고량이 높은 게임 : Action, Shooter, Role-Playing, Sports가 74%를 차지\n",
        "\n",
        "# >> Action, Sports, Shooter, Role-Playing 중 하나를 만들면 될 것 같다."
      ],
      "metadata": {
        "id": "iNGiFpzGQLKW"
      },
      "execution_count": 385,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **3. 결과** ##"
      ],
      "metadata": {
        "id": "mZmIV9GSQD66"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 2-1,2에서의 결과 : 지역별로 선호하는 게임의 장르가 Platform, Shooter, Racing, Sports로 비슷\n",
        "#                   (단, 일본은 Role-Playing 선호 ↑)\n",
        "\n",
        "# 2-3에서의 결과 : 장르별 연간 출시된 게임 개수 : 1990년대 : Sports 장르 출시 多, 2000년대~ : Action 장르 출시 多\n",
        "#                  장르별 연간 최대 출고량 : 1990년대 초중반 : Platform, 2000년대~ : Action\n",
        "\n",
        "# 2-4에서의 결과 : 장르(Genre)에 따른 인기가 많은 게임 : Action, Sports, Shooter, Platform, Role-Playing, Racing가 75%를 차지\n",
        "#                  최근(5년)동안 출고량이 높은 게임 : Action, Shooter, Role-Playing, Sports가 74%를 차지\n",
        "#                  >> Action, Sports, Shooter, Role-Playing"
      ],
      "metadata": {
        "id": "-NKwyODkTinJ"
      },
      "execution_count": 386,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 결론 ##"
      ],
      "metadata": {
        "id": "ze0L9--OP7CF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 최근 5년간의 출고량을 반영하여 Action, Sports, Shooter, Role-Playing의 장르 중 하나를 만들면 좋을 것 같다.\n",
        "\n",
        "# Action :\n",
        "# 출고량이 높은 게임장르 중 20%, 최근 5년간 인기있는 게임의 32.2을 차지 → 높은 비율임\n",
        "# 2-2에서의 결과에서도 알 수 있듯이 현재 트렌드임\n",
        "\n",
        "\n",
        "# Sports :\n",
        "# 출고량이 높은 게임장르 중 15.3%, 최근 5년간 인기있는 게임의 13%를 차지\n",
        "# 2-4 결과 모두에 존재\n",
        "\n",
        "\n",
        "# Shooter :\n",
        "# 출고량이 높은 게임장르 중 10.6%, 최근 5년간 인기있는 게임의 15.4%를 차지\n",
        "# 2-4 결과 모두에 존재\n",
        "\n",
        "\n",
        "# Role-Playing :\n",
        "# 출고량이 높은 게임장르 중 9.7%, 최근 5년간 인기있는 게임의 13.4%를 차지\n",
        "# 2-3 결과 모두에 존재\n",
        "# 하지만 2-1에서 알 수 있듯이, 일본지역에서의 출고율이 높은 편 >> 일본을 대상으로 게임을 만들면 괜찮은 결과를 얻을 것으로 판단"
      ],
      "metadata": {
        "id": "LB2OPVHDUP_z"
      },
      "execution_count": 387,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **4. 각 장르의 성공 확률** ##"
      ],
      "metadata": {
        "id": "zAOmsPQd0WLk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 데이터 설정 ###"
      ],
      "metadata": {
        "id": "Di_qOdaa2Xx9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 최근 5년간의 데이터로 설정\n",
        "latest_5 = df.query('2012 <= Year <= 2016')"
      ],
      "metadata": {
        "id": "tHURicJs2bPp"
      },
      "execution_count": 388,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Action ###"
      ],
      "metadata": {
        "id": "h7xvTTo_3f5_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Action 장르 게임의 성공 확률\n",
        "latest_5_pop.query('Genre == \"Action\"').shape[0] / latest_5.query('Genre == \"Action\"').shape[0] * 100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pN8o1cp_2r78",
        "outputId": "5d3944a8-f686-468c-aa99-497aa6ee6d6e"
      },
      "execution_count": 389,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16.549295774647888"
            ]
          },
          "metadata": {},
          "execution_count": 389
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Sports ###"
      ],
      "metadata": {
        "id": "dM8WY-6R3mPO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Action 장르 게임의 성공 확률\n",
        "latest_5_pop.query('Genre == \"Sports\"').shape[0] / latest_5.query('Genre == \"Sports\"').shape[0] * 100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TKnL8fYm3vgY",
        "outputId": "5d3a9277-029a-4453-9241-c362da53e81c"
      },
      "execution_count": 390,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "37.37373737373738"
            ]
          },
          "metadata": {},
          "execution_count": 390
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Shooter ###"
      ],
      "metadata": {
        "id": "ExG4vX7P3pde"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Shooter 장르 게임의 성공 확률\n",
        "latest_5_pop.query('Genre == \"Shooter\"').shape[0] / latest_5.query('Genre == \"Shooter\"').shape[0] * 100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ATcb2Ygs32Ik",
        "outputId": "2e64cf57-d7e6-4b44-fe73-228618064bde"
      },
      "execution_count": 391,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "49.45054945054945"
            ]
          },
          "metadata": {},
          "execution_count": 391
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Role-Playing ###"
      ],
      "metadata": {
        "id": "IzwAkjsX3q5w"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Role-Playing 장르 게임의 성공 확률\n",
        "latest_5_pop.query('Genre == \"Role-Playing\"').shape[0] / latest_5.query('Genre == \"Role-Playing\"').shape[0] * 100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AJM42P2J33VS",
        "outputId": "a6ffdc8f-50df-4d61-be4d-d9e6858daf58"
      },
      "execution_count": 392,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14.130434782608695"
            ]
          },
          "metadata": {},
          "execution_count": 392
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **5. 최종 결론** ##"
      ],
      "metadata": {
        "id": "2AvLPL9_4C1c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Shooter 장르 게임의 성공 확률이 49.45%로 가장 높은것으로 확인됨"
      ],
      "metadata": {
        "id": "h9DqovlH4F3Z"
      },
      "execution_count": 393,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 만약 회사 규모가 작다면 안전하게 성공할 확률이 높은 게임으로 결정\n",
        "# (레드오션인 Action 장르보다 블루오션인 Shooter 장르로 선택)\n",
        "\n",
        "# >> Shooter 장르 제작"
      ],
      "metadata": {
        "id": "QPEn87vAJMhO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 만약 회사 규모가 크다면 유행성도 높고 판매량도 높은 게임으로 결정\n",
        "\n",
        "# >> Action 장르 제작"
      ],
      "metadata": {
        "id": "Y0vYBjfHJaVG"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}