Game_Genre_Analysis.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kimkihyun1/Game-Genre-Analysis/blob/main/Game_Genre_Analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 다음 분기에 어떤 게임을 설계해야 할까"
      ],
      "metadata": {
        "id": "hQ-m41XG8jkg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Game Dataset**"
      ],
      "metadata": {
        "id": "b4Mj_B-EXlpA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#라이브러리 불러오기\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n"
      ],
      "metadata": {
        "id": "HUaz16lfYOfK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#데이터 불러오기\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 77
        },
        "id": "c_bpdo9tjZQm",
        "outputId": "07e55fd3-0149-4f32-9036-33914bb66f82"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-ee45545c-6433-4779-b4bd-091df1a21e4a\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-ee45545c-6433-4779-b4bd-091df1a21e4a\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving vgames2.csv to vgames2.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('vgames2.csv', index_col=0) #index_col: 칼럼을 인덱스로 사용\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "D8g5pI8lcy8j",
        "outputId": "6464a45d-1729-4055-e80b-12a9243317d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name Platform    Year  \\\n",
              "1                        Candace Kane's Candy Factory       DS  2008.0   \n",
              "2                                      The Munchables      Wii  2009.0   \n",
              "3      Otome wa Oanesama Boku ni Koi Shiteru Portable      PSP  2010.0   \n",
              "4                    Deal or No Deal: Special Edition       DS  2010.0   \n",
              "5           Ben 10 Ultimate Alien: Cosmic Destruction      PS3  2010.0   \n",
              "...                                               ...      ...     ...   \n",
              "16594                         Ice Age 2: The Meltdown       GC  2006.0   \n",
              "16595                     Rainbow Islands: Revolution      PSP  2005.0   \n",
              "16596                                        NBA 2K16      PS3  2015.0   \n",
              "16597                     Toukiden: The Age of Demons      PSV  2013.0   \n",
              "16598                        The King of Fighters '95       PS  1996.0   \n",
              "\n",
              "           Genre                    Publisher NA_Sales EU_Sales JP_Sales  \\\n",
              "1         Action                    Destineer     0.04        0        0   \n",
              "2         Action           Namco Bandai Games     0.17        0        0   \n",
              "3      Adventure                    Alchemist        0        0     0.02   \n",
              "4           Misc                    Zoo Games     0.04        0        0   \n",
              "5       Platform                  D3Publisher     0.12     0.09        0   \n",
              "...          ...                          ...      ...      ...      ...   \n",
              "16594   Platform                Vivendi Games     0.15     0.04        0   \n",
              "16595     Action            Rising Star Games     0.01        0        0   \n",
              "16596     Sports         Take-Two Interactive     0.44     0.19     0.03   \n",
              "16597     Action                   Tecmo Koei     0.05     0.05     0.25   \n",
              "16598   Fighting  Sony Computer Entertainment        0        0     0.16   \n",
              "\n",
              "      Other_Sales  \n",
              "1               0  \n",
              "2            0.01  \n",
              "3               0  \n",
              "4               0  \n",
              "5            0.04  \n",
              "...           ...  \n",
              "16594        0.01  \n",
              "16595           0  \n",
              "16596        0.13  \n",
              "16597        0.03  \n",
              "16598        0.01  \n",
              "\n",
              "[16598 rows x 9 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c9011258-36b5-4c11-a6d0-6d7dc5c237a8\">\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>Platform</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>1</th>\n",
              "      <td>Candace Kane's Candy Factory</td>\n",
              "      <td>DS</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>2</th>\n",
              "      <td>The Munchables</td>\n",
              "      <td>Wii</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>3</th>\n",
              "      <td>Otome wa Oanesama Boku ni Koi Shiteru Portable</td>\n",
              "      <td>PSP</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>4</th>\n",
              "      <td>Deal or No Deal: Special Edition</td>\n",
              "      <td>DS</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",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Ben 10 Ultimate Alien: Cosmic Destruction</td>\n",
              "      <td>PS3</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",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>16594</th>\n",
              "      <td>Ice Age 2: The Meltdown</td>\n",
              "      <td>GC</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",
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              "    <tr>\n",
              "      <th>16595</th>\n",
              "      <td>Rainbow Islands: Revolution</td>\n",
              "      <td>PSP</td>\n",
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              "      <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>16596</th>\n",
              "      <td>NBA 2K16</td>\n",
              "      <td>PS3</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>16597</th>\n",
              "      <td>Toukiden: The Age of Demons</td>\n",
              "      <td>PSV</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",
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              "    <tr>\n",
              "      <th>16598</th>\n",
              "      <td>The King of Fighters '95</td>\n",
              "      <td>PS</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",
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              "<p>16598 rows × 9 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c9011258-36b5-4c11-a6d0-6d7dc5c237a8')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-c9011258-36b5-4c11-a6d0-6d7dc5c237a8 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-c9011258-36b5-4c11-a6d0-6d7dc5c237a8');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#결측치 개수 확인\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "leWCSF0Qj56F",
        "outputId": "186ff3ce-5081-4294-81b7-d7ae4ba56179"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name             0\n",
              "Platform         0\n",
              "Year           271\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": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#결측치 제거\n",
        "df = df.dropna(axis=0)\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "oiImFiNg2pgW",
        "outputId": "13348ca0-4621-442e-f399-95c4ea37bb24"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name Platform    Year  \\\n",
              "0                        Candace Kane's Candy Factory       DS  2008.0   \n",
              "1                                      The Munchables      Wii  2009.0   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable      PSP  2010.0   \n",
              "3                    Deal or No Deal: Special Edition       DS  2010.0   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction      PS3  2010.0   \n",
              "...                                               ...      ...     ...   \n",
              "16236                         Ice Age 2: The Meltdown       GC  2006.0   \n",
              "16237                     Rainbow Islands: Revolution      PSP  2005.0   \n",
              "16238                                        NBA 2K16      PS3  2015.0   \n",
              "16239                     Toukiden: The Age of Demons      PSV  2013.0   \n",
              "16240                        The King of Fighters '95       PS  1996.0   \n",
              "\n",
              "           Genre                    Publisher NA_Sales EU_Sales JP_Sales  \\\n",
              "0         Action                    Destineer     0.04        0        0   \n",
              "1         Action           Namco Bandai Games     0.17        0        0   \n",
              "2      Adventure                    Alchemist        0        0     0.02   \n",
              "3           Misc                    Zoo Games     0.04        0        0   \n",
              "4       Platform                  D3Publisher     0.12     0.09        0   \n",
              "...          ...                          ...      ...      ...      ...   \n",
              "16236   Platform                Vivendi Games     0.15     0.04        0   \n",
              "16237     Action            Rising Star Games     0.01        0        0   \n",
              "16238     Sports         Take-Two Interactive     0.44     0.19     0.03   \n",
              "16239     Action                   Tecmo Koei     0.05     0.05     0.25   \n",
              "16240   Fighting  Sony Computer Entertainment        0        0     0.16   \n",
              "\n",
              "      Other_Sales  \n",
              "0               0  \n",
              "1            0.01  \n",
              "2               0  \n",
              "3               0  \n",
              "4            0.04  \n",
              "...           ...  \n",
              "16236        0.01  \n",
              "16237           0  \n",
              "16238        0.13  \n",
              "16239        0.03  \n",
              "16240        0.01  \n",
              "\n",
              "[16241 rows x 9 columns]"
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              "      <td>2006.0</td>\n",
              "      <td>Platform</td>\n",
              "      <td>Vivendi Games</td>\n",
              "      <td>0.15</td>\n",
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              "      <td>PSP</td>\n",
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              "      <td>Action</td>\n",
              "      <td>Rising Star Games</td>\n",
              "      <td>0.01</td>\n",
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              "      <td>Toukiden: The Age of Demons</td>\n",
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              "      <td>Action</td>\n",
              "      <td>Tecmo Koei</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.05</td>\n",
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              "<p>16241 rows × 9 columns</p>\n",
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              "      </button>\n",
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              "          const dataTable =\n",
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              "                                                     [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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              "          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": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 1. 지역에 따른 선호하는 게임 장르 분석"
      ],
      "metadata": {
        "id": "smHDUtqEiyRO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#장르 종류\n",
        "df['Genre'].unique()  #총 12종류"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N9NoywAdjDMT",
        "outputId": "30bb9bd6-ed9f-44ff-e491-23a48b247d64"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Action', 'Adventure', 'Misc', 'Platform', 'Sports', 'Simulation',\n",
              "       'Racing', 'Role-Playing', 'Puzzle', 'Strategy', 'Fighting',\n",
              "       'Shooter'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g5qwjA3QBnmk",
        "outputId": "2809222f-be55-45e6-c811-71dfd805d199"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name            object\n",
              "Platform        object\n",
              "Year           float64\n",
              "Genre           object\n",
              "Publisher       object\n",
              "NA_Sales        object\n",
              "EU_Sales        object\n",
              "JP_Sales        object\n",
              "Other_Sales     object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Sales columns : 백만 단위\n",
        "df = df[~(df['EU_Sales'].str.contains('K|M') | df['NA_Sales'].str.contains('K|M') | df['JP_Sales'].str.contains('K|M') | df['Other_Sales'].str.contains('K|M'))] \n",
        "\n",
        "\n",
        "#데이터 타입 변경\n",
        "df = df.astype({'Year': 'int'})\n",
        "\n",
        "#1980년 이상 데이터\n",
        "df_Year = df['Year'] >= 1980\n",
        "df = df[df_Year]\n",
        "df\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "fYP1lqKeLi4s",
        "outputId": "a069df8c-6503-4feb-c5a5-48bf5e0804cd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 Name Platform  Year  \\\n",
              "0                        Candace Kane's Candy Factory       DS  2008   \n",
              "1                                      The Munchables      Wii  2009   \n",
              "2      Otome wa Oanesama Boku ni Koi Shiteru Portable      PSP  2010   \n",
              "3                    Deal or No Deal: Special Edition       DS  2010   \n",
              "4           Ben 10 Ultimate Alien: Cosmic Destruction      PS3  2010   \n",
              "...                                               ...      ...   ...   \n",
              "16236                         Ice Age 2: The Meltdown       GC  2006   \n",
              "16237                     Rainbow Islands: Revolution      PSP  2005   \n",
              "16238                                        NBA 2K16      PS3  2015   \n",
              "16239                     Toukiden: The Age of Demons      PSV  2013   \n",
              "16240                        The King of Fighters '95       PS  1996   \n",
              "\n",
              "           Genre                    Publisher NA_Sales EU_Sales JP_Sales  \\\n",
              "0         Action                    Destineer     0.04        0        0   \n",
              "1         Action           Namco Bandai Games     0.17        0        0   \n",
              "2      Adventure                    Alchemist        0        0     0.02   \n",
              "3           Misc                    Zoo Games     0.04        0        0   \n",
              "4       Platform                  D3Publisher     0.12     0.09        0   \n",
              "...          ...                          ...      ...      ...      ...   \n",
              "16236   Platform                Vivendi Games     0.15     0.04        0   \n",
              "16237     Action            Rising Star Games     0.01        0        0   \n",
              "16238     Sports         Take-Two Interactive     0.44     0.19     0.03   \n",
              "16239     Action                   Tecmo Koei     0.05     0.05     0.25   \n",
              "16240   Fighting  Sony Computer Entertainment        0        0     0.16   \n",
              "\n",
              "      Other_Sales  \n",
              "0               0  \n",
              "1            0.01  \n",
              "2               0  \n",
              "3               0  \n",
              "4            0.04  \n",
              "...           ...  \n",
              "16236        0.01  \n",
              "16237           0  \n",
              "16238        0.13  \n",
              "16239        0.03  \n",
              "16240        0.01  \n",
              "\n",
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              "      <td>PS3</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "      <th>16236</th>\n",
              "      <td>Ice Age 2: The Meltdown</td>\n",
              "      <td>GC</td>\n",
              "      <td>2006</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",
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              "    <tr>\n",
              "      <th>16237</th>\n",
              "      <td>Rainbow Islands: Revolution</td>\n",
              "      <td>PSP</td>\n",
              "      <td>2005</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",
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              "    <tr>\n",
              "      <th>16238</th>\n",
              "      <td>NBA 2K16</td>\n",
              "      <td>PS3</td>\n",
              "      <td>2015</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",
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              "    <tr>\n",
              "      <th>16239</th>\n",
              "      <td>Toukiden: The Age of Demons</td>\n",
              "      <td>PSV</td>\n",
              "      <td>2013</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>16240</th>\n",
              "      <td>The King of Fighters '95</td>\n",
              "      <td>PS</td>\n",
              "      <td>1996</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>Sony Computer Entertainment</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "</table>\n",
              "<p>15382 rows × 9 columns</p>\n",
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    {
      "cell_type": "code",
      "source": [
        "#데이터 타입 변경\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "df[[\"NA_Sales\", \"EU_Sales\",\"JP_Sales\",\"Other_Sales\"]] = df[[\"NA_Sales\", \"EU_Sales\",\"JP_Sales\",\"Other_Sales\"]].apply(pd.to_numeric)\n",
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZA1T-UD4CuT7",
        "outputId": "c933a570-578c-4d20-9652-8eb5898f800a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name            object\n",
              "Platform        object\n",
              "Year             int64\n",
              "Genre           object\n",
              "Publisher       object\n",
              "NA_Sales       float64\n",
              "EU_Sales       float64\n",
              "JP_Sales       float64\n",
              "Other_Sales    float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#NA_Sales 데이터\n",
        "df_NA_Sales = df[['Genre', 'NA_Sales']]\n",
        "df_NA_Sales = df_NA_Sales.groupby('Genre').sum()\n",
        "df_NA_Sales"
      ],
      "metadata": {
        "colab": {
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          "height": 457
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              NA_Sales\n",
              "Genre                 \n",
              "Action          801.89\n",
              "Adventure        97.29\n",
              "Fighting        210.51\n",
              "Misc            380.36\n",
              "Platform        410.96\n",
              "Puzzle          118.40\n",
              "Racing          334.14\n",
              "Role-Playing    283.86\n",
              "Shooter         544.63\n",
              "Simulation      173.64\n",
              "Sports          633.87\n",
              "Strategy         65.67"
            ],
            "text/html": [
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              "      <td>544.63</td>\n",
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              "      <td>633.87</td>\n",
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              "      <td>65.67</td>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e5c6caae-35a2-461f-a15d-cc567decad66');\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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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#EU_Sales 데이터\n",
        "df_EU_Sales = df[['Genre', 'EU_Sales']]\n",
        "df_EU_Sales = df_EU_Sales.groupby('Genre').sum()\n",
        "df_EU_Sales"
      ],
      "metadata": {
        "id": "rcbH6y9Dxupw",
        "outputId": "2f4cfbf3-45f1-4cf6-d813-94325fcdea5d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              EU_Sales\n",
              "Genre                 \n",
              "Action          486.60\n",
              "Adventure        60.65\n",
              "Fighting         94.18\n",
              "Misc            200.14\n",
              "Platform        184.11\n",
              "Puzzle           49.95\n",
              "Racing          222.66\n",
              "Role-Playing    160.10\n",
              "Shooter         293.38\n",
              "Simulation      106.97\n",
              "Sports          349.85\n",
              "Strategy         43.11"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-536e8d37-70a4-474e-8213-9498bbfbaae6\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "      <th></th>\n",
              "      <th>EU_Sales</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Genre</th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Action</th>\n",
              "      <td>486.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Adventure</th>\n",
              "      <td>60.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fighting</th>\n",
              "      <td>94.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Misc</th>\n",
              "      <td>200.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platform</th>\n",
              "      <td>184.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Puzzle</th>\n",
              "      <td>49.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Racing</th>\n",
              "      <td>222.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Role-Playing</th>\n",
              "      <td>160.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shooter</th>\n",
              "      <td>293.38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Simulation</th>\n",
              "      <td>106.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sports</th>\n",
              "      <td>349.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Strategy</th>\n",
              "      <td>43.11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-536e8d37-70a4-474e-8213-9498bbfbaae6 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-536e8d37-70a4-474e-8213-9498bbfbaae6');\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",
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              "  </div>\n",
              "  "
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#JP_Sales 데이터\n",
        "df_JP_Sales = df[['Genre', 'JP_Sales']]\n",
        "df_JP_Sales = df_JP_Sales.groupby('Genre').sum()\n",
        "df_JP_Sales"
      ],
      "metadata": {
        "id": "hg28OhE7yWc_",
        "outputId": "479e5090-f1a7-4f1e-a73a-b45f77692bb3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              JP_Sales\n",
              "Genre                 \n",
              "Action          149.85\n",
              "Adventure        49.20\n",
              "Fighting         82.58\n",
              "Misc             99.47\n",
              "Platform        121.88\n",
              "Puzzle           56.16\n",
              "Racing           50.60\n",
              "Role-Playing    314.15\n",
              "Shooter          36.53\n",
              "Simulation       61.51\n",
              "Sports          126.65\n",
              "Strategy         43.56"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>JP_Sales</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Genre</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Action</th>\n",
              "      <td>149.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Adventure</th>\n",
              "      <td>49.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fighting</th>\n",
              "      <td>82.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Misc</th>\n",
              "      <td>99.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platform</th>\n",
              "      <td>121.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Puzzle</th>\n",
              "      <td>56.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Racing</th>\n",
              "      <td>50.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Role-Playing</th>\n",
              "      <td>314.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shooter</th>\n",
              "      <td>36.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Simulation</th>\n",
              "      <td>61.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sports</th>\n",
              "      <td>126.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Strategy</th>\n",
              "      <td>43.56</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-14a8c666-0c25-474f-8014-c647d4a643fc')\"\n",
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              "              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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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </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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              "      fill: #1967D2;\n",
              "      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",
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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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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-14a8c666-0c25-474f-8014-c647d4a643fc');\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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              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Other_Sales 데이터\n",
        "df_Other_Sales = df[['Genre', 'Other_Sales']]\n",
        "df_Other_Sales = df_Other_Sales.groupby('Genre').sum()\n",
        "df_Other_Sales"
      ],
      "metadata": {
        "id": "sy4heTTDyf44",
        "outputId": "277596ff-e561-4753-890f-cf12fd7738d4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Other_Sales\n",
              "Genre                    \n",
              "Action             176.14\n",
              "Adventure           16.06\n",
              "Fighting            34.33\n",
              "Misc                69.97\n",
              "Platform            47.88\n",
              "Puzzle              12.13\n",
              "Racing              73.48\n",
              "Role-Playing        50.86\n",
              "Shooter             96.68\n",
              "Simulation          29.49\n",
              "Sports             126.13\n",
              "Strategy            10.71"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Other_Sales</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Genre</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Action</th>\n",
              "      <td>176.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Adventure</th>\n",
              "      <td>16.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fighting</th>\n",
              "      <td>34.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Misc</th>\n",
              "      <td>69.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platform</th>\n",
              "      <td>47.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Puzzle</th>\n",
              "      <td>12.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Racing</th>\n",
              "      <td>73.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Role-Playing</th>\n",
              "      <td>50.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shooter</th>\n",
              "      <td>96.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Simulation</th>\n",
              "      <td>29.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sports</th>\n",
              "      <td>126.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Strategy</th>\n",
              "      <td>10.71</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 14
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#concat을 사용하여 장르를 기준으로 df_Sales 데이터프레임\n",
        "df_Sales = pd.concat([df_NA_Sales, df_EU_Sales,df_JP_Sales,df_Other_Sales], axis=1)\n",
        "df_Sales"
      ],
      "metadata": {
        "id": "2G-Fgfiv_2dg",
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          "height": 457
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              NA_Sales  EU_Sales  JP_Sales  Other_Sales\n",
              "Genre                                                  \n",
              "Action          801.89    486.60    149.85       176.14\n",
              "Adventure        97.29     60.65     49.20        16.06\n",
              "Fighting        210.51     94.18     82.58        34.33\n",
              "Misc            380.36    200.14     99.47        69.97\n",
              "Platform        410.96    184.11    121.88        47.88\n",
              "Puzzle          118.40     49.95     56.16        12.13\n",
              "Racing          334.14    222.66     50.60        73.48\n",
              "Role-Playing    283.86    160.10    314.15        50.86\n",
              "Shooter         544.63    293.38     36.53        96.68\n",
              "Simulation      173.64    106.97     61.51        29.49\n",
              "Sports          633.87    349.85    126.65       126.13\n",
              "Strategy         65.67     43.11     43.56        10.71"
            ],
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              "      <td>149.85</td>\n",
              "      <td>176.14</td>\n",
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              "      <th>Puzzle</th>\n",
              "      <td>118.40</td>\n",
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              "      <td>12.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Racing</th>\n",
              "      <td>334.14</td>\n",
              "      <td>222.66</td>\n",
              "      <td>50.60</td>\n",
              "      <td>73.48</td>\n",
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              "    <tr>\n",
              "      <th>Role-Playing</th>\n",
              "      <td>283.86</td>\n",
              "      <td>160.10</td>\n",
              "      <td>314.15</td>\n",
              "      <td>50.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shooter</th>\n",
              "      <td>544.63</td>\n",
              "      <td>293.38</td>\n",
              "      <td>36.53</td>\n",
              "      <td>96.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Simulation</th>\n",
              "      <td>173.64</td>\n",
              "      <td>106.97</td>\n",
              "      <td>61.51</td>\n",
              "      <td>29.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sports</th>\n",
              "      <td>633.87</td>\n",
              "      <td>349.85</td>\n",
              "      <td>126.65</td>\n",
              "      <td>126.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Strategy</th>\n",
              "      <td>65.67</td>\n",
              "      <td>43.11</td>\n",
              "      <td>43.56</td>\n",
              "      <td>10.71</td>\n",
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          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10, 10))\n",
        "locate_heatmap = sns.heatmap(df_Sales, annot=True, fmt='.2f', cmap='Blues') #annot : cell안에 값 표시유무, \n",
        "plt.show();"
      ],
      "metadata": {
        "id": "KDX5Bgw4Wh5_",
        "outputId": "f2b01d63-292e-4003-82fa-7c2f9ff0688c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 595
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 지역에 따라서 선호하는 게임 장르가 다른지 같은지 확인\n",
        "# 귀무가설 : 지역마다 선호하는 게임 장르가 같다\n",
        "# 대립가설 : 지역마다 선호하는 게임 장르가 다르다\n",
        "from scipy.stats import chi2_contingency # 카이제곱 검정\n",
        "\n",
        "print('p-value : ', chi2_contingency(df_Sales)[1])"
      ],
      "metadata": {
        "id": "XpbXKFa6oZEA",
        "outputId": "83f5810f-ce16-4803-8540-f1e0924887ce",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "p-value :  2.0999230443534412e-116\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "p-value가 0.05보다 작기 때문에 귀무가설을 기각하고 대립가설을 채택한다.\n",
        "\n",
        "\n",
        "\n",
        "일본 지역을 제외한 전체지역에서는 Action, Sports, Shooter순으로 장르가 가장 선호되었습니다.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "일본 지역은 Role-Playing, Action, Sports순으로 장르가 가장 선호되었습니다.\n",
        "\n"
      ],
      "metadata": {
        "id": "MsbAJUVH4AC_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2. 연도별 게임 트렌드 분석"
      ],
      "metadata": {
        "id": "36xEtKvi5afa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['Year'].unique()"
      ],
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        "id": "Wrz04Gy57FmX",
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        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2008, 2009, 2010, 2005, 2011, 2007, 2003, 2006, 2014, 2015, 2002,\n",
              "       1997, 2013, 1996, 2004, 2000, 1984, 1998, 2001, 2016, 1985, 1999,\n",
              "       1995, 1993, 2012, 1987, 1982, 1994, 1990, 1992, 1991, 1983, 1988,\n",
              "       1981, 1989, 1986, 2017, 1980])"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Year, Genre 기준으로 개수\n",
        "df_Year_Genre = df.groupby(['Year','Genre']).size().reset_index(name='Count')\n",
        "df_Year_Genre"
      ],
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              "     Year         Genre  Count\n",
              "0    1980        Action      1\n",
              "1    1980      Fighting      1\n",
              "2    1980          Misc      3\n",
              "3    1980       Shooter      2\n",
              "4    1981        Action     24\n",
              "..    ...           ...    ...\n",
              "381  2016    Simulation      8\n",
              "382  2016        Sports     34\n",
              "383  2016      Strategy      9\n",
              "384  2017        Action      1\n",
              "385  2017  Role-Playing      2\n",
              "\n",
              "[386 rows x 3 columns]"
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              "      <td>Role-Playing</td>\n",
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    {
      "cell_type": "code",
      "source": [
        "#연도별 장르 최대값\n",
        "df_Genre_Count = df_Year_Genre.groupby(['Year'])['Count'].transform(max) == df_Year_Genre['Count']\n",
        "df_Genre_Max = df_Year_Genre[df_Genre_Count].reset_index(drop=True) #drop : 인덱스 기준열 삭제\n",
        "\n",
        "#중복값 제거\n",
        "df_Genre_Max = df_Genre_Max.drop_duplicates(subset=['Year','Count']).reset_index(drop=True) #subset : 중복데이터를 처리할 열\n",
        "df_Genre_Max"
      ],
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        "id": "67lSECnoCr5Q",
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      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Year         Genre  Count\n",
              "0   1980          Misc      3\n",
              "1   1981        Action     24\n",
              "2   1982        Action     18\n",
              "3   1983        Action      7\n",
              "4   1984        Puzzle      3\n",
              "5   1985        Puzzle      4\n",
              "6   1986        Action      6\n",
              "7   1987        Sports      4\n",
              "8   1988      Platform      3\n",
              "9   1989        Puzzle      4\n",
              "10  1990        Action      3\n",
              "11  1991        Sports      7\n",
              "12  1992      Fighting      7\n",
              "13  1993      Fighting     11\n",
              "14  1994        Sports     21\n",
              "15  1995        Sports     28\n",
              "16  1996        Sports     47\n",
              "17  1997        Sports     45\n",
              "18  1998        Sports     69\n",
              "19  1999        Sports     59\n",
              "20  2000        Sports     78\n",
              "21  2001        Sports     92\n",
              "22  2002        Sports    178\n",
              "23  2003        Action    135\n",
              "24  2004        Action    117\n",
              "25  2005        Action    184\n",
              "26  2006        Action    172\n",
              "27  2007        Action    202\n",
              "28  2008        Action    210\n",
              "29  2009        Action    259\n",
              "30  2010        Action    221\n",
              "31  2011        Action    225\n",
              "32  2012        Action    246\n",
              "33  2013        Action    141\n",
              "34  2014        Action    181\n",
              "35  2015        Action    236\n",
              "36  2016        Action    111\n",
              "37  2017  Role-Playing      2"
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              "      <th>9</th>\n",
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              "      <th>13</th>\n",
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              "      <th>14</th>\n",
              "      <td>1994</td>\n",
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              "      <th>15</th>\n",
              "      <td>1995</td>\n",
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              "      <td>28</td>\n",
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              "      <th>16</th>\n",
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              "      <td>47</td>\n",
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              "      <td>117</td>\n",
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              "      <th>25</th>\n",
              "      <td>2005</td>\n",
              "      <td>Action</td>\n",
              "      <td>184</td>\n",
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              "      <th>26</th>\n",
              "      <td>2006</td>\n",
              "      <td>Action</td>\n",
              "      <td>172</td>\n",
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              "      <th>27</th>\n",
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              "      <td>210</td>\n",
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              "      <td>2009</td>\n",
              "      <td>Action</td>\n",
              "      <td>259</td>\n",
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              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2010</td>\n",
              "      <td>Action</td>\n",
              "      <td>221</td>\n",
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              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2011</td>\n",
              "      <td>Action</td>\n",
              "      <td>225</td>\n",
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              "      <td>2012</td>\n",
              "      <td>Action</td>\n",
              "      <td>246</td>\n",
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              "      <th>35</th>\n",
              "      <td>2015</td>\n",
              "      <td>Action</td>\n",
              "      <td>236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2016</td>\n",
              "      <td>Action</td>\n",
              "      <td>111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2017</td>\n",
              "      <td>Role-Playing</td>\n",
              "      <td>2</td>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </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",
              "      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-4d134bbe-84cd-4dd8-a4ff-4b008c7dd429 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-4d134bbe-84cd-4dd8-a4ff-4b008c7dd429');\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": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#bar plot\n",
        "Genre_name = df_Genre_Max['Genre'].values\n",
        "plt.figure(figsize=(20, 10))\n",
        "trend_barplot = sns.barplot(data=df_Genre_Max, x='Year', y='Count', hue='Genre')\n",
        "num = 0\n",
        "for i in df_Genre_Max['Count']:\n",
        "  trend_barplot.text(x=num, y= i+8, s=str(Genre_name[num]), color='black', size=11, rotation=90, ha='center')\n",
        "  num += 1\n",
        "\n",
        "plt.legend(loc='upper left')\n",
        "plt.xticks(rotation=90, fontsize=10)\n",
        "plt.yticks(fontsize=12)\n",
        "plt.show();"
      ],
      "metadata": {
        "id": "sPvmz5wydtcY",
        "outputId": "aab17c85-2615-4903-becd-a9579c5cb06b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 644
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "1990년대 중반 이전까지는 장르별로 다양하게 선호되었고,\n",
        "\n",
        "\n",
        "1990년대 중반 이후부터는 Sports장르가 선호되었고,\n",
        "\n",
        "\n",
        "2000년대 중반 이후부터는 Action장르가 선호되었다.\n",
        "\n",
        "\n",
        "Various Genres  ->  Sprots Genre  -> Action Genre"
      ],
      "metadata": {
        "id": "r9k2bQWxmZrf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3. 출고량이 높은 게임에 대한 분석 및 시각화 프로세스\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "wazsiFGXntOa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 최근 10년간 판매량 총 합계\n",
        "df['Sales_sum'] = df['NA_Sales'] + df['EU_Sales'] + df['JP_Sales'] + df['Other_Sales']\n",
        "df_Sales_10 = df[df.Year > 2007].sort_values(by='Sales_sum', ascending=False)\n",
        "\n",
        "df_Sales_10"
      ],
      "metadata": {
        "id": "NGm3wfn7n4Gf",
        "outputId": "a4ff6666-992c-4340-dee0-6aae38f4f506",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                   Name Platform  Year  \\\n",
              "11677                                    Mario Kart Wii      Wii  2008   \n",
              "3135                                  Wii Sports Resort      Wii  2009   \n",
              "15321                         New Super Mario Bros. Wii      Wii  2009   \n",
              "10112                                      Wii Fit Plus      Wii  2009   \n",
              "4056                                 Kinect Adventures!     X360  2010   \n",
              "...                                                 ...      ...   ...   \n",
              "9674            WSC REAL 09: World Snooker Championship      PS3  2009   \n",
              "6407                      Monkey Madness: Island Escape       DS  2010   \n",
              "6420                                         Juggler DS       DS  2008   \n",
              "4233                                    Princess Arthur      PSP  2013   \n",
              "5220   SCORE International Baja 1000: The Official Game      PS2  2008   \n",
              "\n",
              "          Genre               Publisher  NA_Sales  EU_Sales  JP_Sales  \\\n",
              "11677    Racing                Nintendo     15.85     12.88      3.79   \n",
              "3135     Sports                Nintendo     15.75     11.01      3.28   \n",
              "15321  Platform                Nintendo     14.59      7.06      4.70   \n",
              "10112    Sports                Nintendo      9.09      8.59      2.53   \n",
              "4056       Misc  Microsoft Game Studios     14.97      4.94      0.24   \n",
              "...         ...                     ...       ...       ...       ...   \n",
              "9674     Sports             Deep Silver      0.00      0.01      0.00   \n",
              "6407     Action        Storm City Games      0.01      0.00      0.00   \n",
              "6420       Misc                Commseed      0.00      0.00      0.01   \n",
              "4233       Misc            Idea Factory      0.00      0.00      0.01   \n",
              "5220     Racing              Activision      0.00      0.00      0.00   \n",
              "\n",
              "       Other_Sales  Sales_sum  \n",
              "11677         3.31      35.83  \n",
              "3135          2.96      33.00  \n",
              "15321         2.26      28.61  \n",
              "10112         1.79      22.00  \n",
              "4056          1.67      21.82  \n",
              "...            ...        ...  \n",
              "9674          0.00       0.01  \n",
              "6407          0.00       0.01  \n",
              "6420          0.00       0.01  \n",
              "4233          0.00       0.01  \n",
              "5220          0.00       0.00  \n",
              "\n",
              "[7554 rows x 10 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8458c059-52c7-444f-9857-bc3e6c2c81bd\">\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>Platform</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>Sales_sum</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>11677</th>\n",
              "      <td>Mario Kart Wii</td>\n",
              "      <td>Wii</td>\n",
              "      <td>2008</td>\n",
              "      <td>Racing</td>\n",
              "      <td>Nintendo</td>\n",
              "      <td>15.85</td>\n",
              "      <td>12.88</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.31</td>\n",
              "      <td>35.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3135</th>\n",
              "      <td>Wii Sports Resort</td>\n",
              "      <td>Wii</td>\n",
              "      <td>2009</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Nintendo</td>\n",
              "      <td>15.75</td>\n",
              "      <td>11.01</td>\n",
              "      <td>3.28</td>\n",
              "      <td>2.96</td>\n",
              "      <td>33.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15321</th>\n",
              "      <td>New Super Mario Bros. Wii</td>\n",
              "      <td>Wii</td>\n",
              "      <td>2009</td>\n",
              "      <td>Platform</td>\n",
              "      <td>Nintendo</td>\n",
              "      <td>14.59</td>\n",
              "      <td>7.06</td>\n",
              "      <td>4.70</td>\n",
              "      <td>2.26</td>\n",
              "      <td>28.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10112</th>\n",
              "      <td>Wii Fit Plus</td>\n",
              "      <td>Wii</td>\n",
              "      <td>2009</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Nintendo</td>\n",
              "      <td>9.09</td>\n",
              "      <td>8.59</td>\n",
              "      <td>2.53</td>\n",
              "      <td>1.79</td>\n",
              "      <td>22.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4056</th>\n",
              "      <td>Kinect Adventures!</td>\n",
              "      <td>X360</td>\n",
              "      <td>2010</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Microsoft Game Studios</td>\n",
              "      <td>14.97</td>\n",
              "      <td>4.94</td>\n",
              "      <td>0.24</td>\n",
              "      <td>1.67</td>\n",
              "      <td>21.82</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>9674</th>\n",
              "      <td>WSC REAL 09: World Snooker Championship</td>\n",
              "      <td>PS3</td>\n",
              "      <td>2009</td>\n",
              "      <td>Sports</td>\n",
              "      <td>Deep Silver</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6407</th>\n",
              "      <td>Monkey Madness: Island Escape</td>\n",
              "      <td>DS</td>\n",
              "      <td>2010</td>\n",
              "      <td>Action</td>\n",
              "      <td>Storm City Games</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6420</th>\n",
              "      <td>Juggler DS</td>\n",
              "      <td>DS</td>\n",
              "      <td>2008</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Commseed</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4233</th>\n",
              "      <td>Princess Arthur</td>\n",
              "      <td>PSP</td>\n",
              "      <td>2013</td>\n",
              "      <td>Misc</td>\n",
              "      <td>Idea Factory</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5220</th>\n",
              "      <td>SCORE International Baja 1000: The Official Game</td>\n",
              "      <td>PS2</td>\n",
              "      <td>2008</td>\n",
              "      <td>Racing</td>\n",
              "      <td>Activision</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>7554 rows × 10 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8458c059-52c7-444f-9857-bc3e6c2c81bd')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      fill: #1967D2;\n",
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              "    .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",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          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",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 최근  \n",
        "df_Genre_10 = df_Sales_10[['Genre', 'Sales_sum']]\n",
        "df_Genre_10 = df_Genre_10.groupby('Genre').sum()\n",
        "df_Genre_10 = df_Genre_10.sort_values(by='Sales_sum', ascending=False)\n",
        "df_Genre_10 = df_Genre_10.head(10)\n",
        "df_Genre_10"
      ],
      "metadata": {
        "id": "UoLRFgo2w-Ns",
        "outputId": "1b5e9d0c-b454-428b-cd70-6889d8d538a1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Sales_sum\n",
              "Genre                  \n",
              "Action           886.88\n",
              "Shooter          548.04\n",
              "Sports           520.18\n",
              "Misc             376.37\n",
              "Role-Playing     346.75\n",
              "Racing           220.84\n",
              "Platform         184.90\n",
              "Simulation       147.81\n",
              "Fighting         142.84\n",
              "Adventure        104.21"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6b6d7975-0403-43de-90f8-32adf2572b61\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sales_sum</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Genre</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Action</th>\n",
              "      <td>886.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shooter</th>\n",
              "      <td>548.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sports</th>\n",
              "      <td>520.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Misc</th>\n",
              "      <td>376.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Role-Playing</th>\n",
              "      <td>346.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Racing</th>\n",
              "      <td>220.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platform</th>\n",
              "      <td>184.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Simulation</th>\n",
              "      <td>147.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fighting</th>\n",
              "      <td>142.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Adventure</th>\n",
              "      <td>104.21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6b6d7975-0403-43de-90f8-32adf2572b61')\"\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "  </style>\n",
              "\n",
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              "        const buttonEl =\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6b6d7975-0403-43de-90f8-32adf2572b61');\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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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#pie chart \n",
        "explode = [0.1 for _ in range(10)]\n",
        "plt.pie(df_Genre_10, labels=df_Genre_10.index, autopct='%1.1f%%',explode=explode)\n",
        "plt.title('Game_TOP10', size=15)\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.show();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "id": "wT7aW4c7VheV",
        "outputId": "8d20d6f4-c2a5-4960-83f7-b55b66ef993a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: MatplotlibDeprecationWarning: Non-1D inputs to pie() are currently squeeze()d, but this behavior is deprecated since 3.1 and will be removed in 3.3; pass a 1D array instead.\n",
            "  after removing the cwd from sys.path.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "최근 10년간은 Action, Shooter, Sports장르가 선호되었다."
      ],
      "metadata": {
        "id": "v5do_uuByV9u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#최근 10년간 선호된 Platform\n",
        "df_Platform_10 = df_Sales_10[['Platform', 'Sales_sum']]\n",
        "df_Platform_10 = df_Platform_10.groupby('Platform').sum()\n",
        "df_Platform_10 = df_Platform_10.sort_values(by='Sales_sum', ascending=False)\n",
        "df_Platform_10 = df_Platform_10.head(10)\n",
        "df_Platform_10"
      ],
      "metadata": {
        "id": "nxdSJ1GayrH6",
        "outputId": "cd556e7c-b94b-40cf-bfd2-b32c4223081d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          Sales_sum\n",
              "Platform           \n",
              "PS3          809.16\n",
              "X360         735.90\n",
              "Wii          579.66\n",
              "DS           369.83\n",
              "PS4          250.54\n",
              "3DS          224.29\n",
              "PC           141.64\n",
              "XOne         132.51\n",
              "PSP          129.49\n",
              "PS2           82.07"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-32e76c18-4936-4293-830b-f9b4aa436715\">\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",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sales_sum</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Platform</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>PS3</th>\n",
              "      <td>809.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>X360</th>\n",
              "      <td>735.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Wii</th>\n",
              "      <td>579.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DS</th>\n",
              "      <td>369.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PS4</th>\n",
              "      <td>250.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3DS</th>\n",
              "      <td>224.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PC</th>\n",
              "      <td>141.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XOne</th>\n",
              "      <td>132.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PSP</th>\n",
              "      <td>129.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PS2</th>\n",
              "      <td>82.07</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-32e76c18-4936-4293-830b-f9b4aa436715')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "      \n",
              "  <style>\n",
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              "      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",
              "      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-32e76c18-4936-4293-830b-f9b4aa436715 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-32e76c18-4936-4293-830b-f9b4aa436715');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "explode = [0.1 for _ in range(10)]\n",
        "plt.pie(df_Platform_10, labels=df_Platform_10.index, autopct='%1.1f%%',explode=explode)\n",
        "plt.title('Game_Platform_10', size=15)\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.show();"
      ],
      "metadata": {
        "id": "8VjL1YrGzOB7",
        "outputId": "e4891725-8dbf-4bc2-a7b9-44f10c3b2625",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 341
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: MatplotlibDeprecationWarning: Non-1D inputs to pie() are currently squeeze()d, but this behavior is deprecated since 3.1 and will be removed in 3.3; pass a 1D array instead.\n",
            "  \n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "최근 10년간 PS3, Wii, X360 Platform이 선호되었다."
      ],
      "metadata": {
        "id": "MyM1ypNEz2jY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 다음 분기에 어떤 게임을 설계해야 할까\n",
        "\n",
        "\n",
        "\n",
        "결론 : 다음 분기에는 Action, Shooter, Sports장르의 게임을 설계하고 Platform은 PS3, Wii, X360로 설정한다. "
      ],
      "metadata": {
        "id": "yQCZAOzG0Sgv"
      }
    }
  ]
}