{"id":50793,"date":"2022-04-13T00:00:00","date_gmt":"2022-04-13T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/clustering-bustabit-gambling-behavior-using-griddb\/"},"modified":"2025-11-14T07:55:19","modified_gmt":"2025-11-14T15:55:19","slug":"clustering-bustabit-gambling-behavior-using-griddb","status":"publish","type":"post","link":"https:\/\/griddb.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/clustering-bustabit-gambling-behavior-using-griddb\/","title":{"rendered":"GridDB\u3092\u7528\u3044\u305fBustabit\u306e\u30ae\u30e3\u30f3\u30d6\u30eb\u884c\u52d5\u306e\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0"},"content":{"rendered":"

\u306f\u3058\u3081\u306b<\/h2>\n

\u4eba\u9593\u306e\u884c\u52d5\u3092\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u3001\u5384\u4ecb\u3067\u6ce8\u610f\u3092\u8981\u3059\u308b\u4f5c\u696d\u3067\u3059\u3002\u3042\u308b\u72b6\u6cc1\u4e0b\u3067\u4eba\u304c\u3069\u306e\u3088\u3046\u306b\u884c\u52d5\u3059\u308b\u306e\u304b\u3001\u3069\u306e\u3088\u3046\u306a\u5224\u65ad\u3092\u4e0b\u3059\u306e\u304b\u3092\u8aac\u660e\u3059\u308b\u306e\u306f\u7c21\u5358\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3057\u3001\u5358\u7d14\u3067\u3082\u3042\u308a\u307e\u305b\u3093\u3002\u3057\u304b\u3057\u3001\u4eba\u3092\u89b3\u5bdf\u3057\u3001\u6b21\u306b\u4f55\u3092\u3059\u308b\u304b\u3092\u4e88\u6e2c\u3057\u3088\u3046\u3068\u3059\u308b\u3053\u3068\u306f\u3001\u771f\u306e\u5b66\u7fd2\u7d4c\u9a13\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u305d\u308c\u306f\u3001\u3088\u308a\u826f\u3044\u7d50\u679c\u3092\u5f97\u308b\u305f\u3081\u306b\u3001\u5341\u5206\u306a\u60c5\u5831\u3092\u5f97\u305f\u4e0a\u3067\u610f\u601d\u6c7a\u5b9a\u3092\u884c\u3046\u306e\u306b\u5f79\u7acb\u3061\u307e\u3059\u3002<\/p>\n

\u4eba\u9593\u306e\u6027\u8cea\u3092\u4e88\u6e2c\u3059\u308b\u3053\u3068\u304c\u6709\u76ca\u306a\u5834\u9762\u306e\u3072\u3068\u3064\u306b\u3001\u30ae\u30e3\u30f3\u30d6\u30eb\u304c\u3042\u308a\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u30dd\u30fc\u30ab\u30fc\u30b2\u30fc\u30e0\u3067\u306f\u3001\u69d8\u3005\u306a\u72b6\u6cc1\u4e0b\u3067\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u306a\u305c\u30ec\u30a4\u30ba\u3001\u30b3\u30fc\u30eb\u3001\u30d5\u30a9\u30fc\u30eb\u30c9\u3059\u308b\u306e\u304b\u3092\u7406\u89e3\u3059\u308b\u3053\u3068\u3067\u3001\u7af6\u4e89\u306b\u304a\u3044\u3066\u660e\u78ba\u306a\u30a2\u30c9\u30d0\u30f3\u30c6\u30fc\u30b8\u3092\u5f97\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001\u30ae\u30e3\u30f3\u30d6\u30e9\u30fc\u306e\u305f\u3081\u306e\u30aa\u30f3\u30e9\u30a4\u30f3\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067\u3042\u308bBustabit<\/strong>\u306e\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n

\u30b2\u30fc\u30e0\u306e\u30eb\u30fc\u30eb\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\u3002<\/p>\n

    \n
  1. \u30d3\u30c3\u30c8\u30b3\u30a4\u30f3\u306e100\u4e07\u5206\u306e1\u3067\u3042\u308bBits\u3067\u4efb\u610f\u306e\u91d1\u984d\u3092\u300c\u30d9\u30c3\u30c8\u300d<\/strong>\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/li>\n
  2. \u30b2\u30fc\u30e0\u304c\u7d42\u4e86\u3059\u308b\u524d\u306b\u30ad\u30e3\u30c3\u30b7\u30e5\u30a2\u30a6\u30c8\u3059\u308c\u3070\u52dd\u3061\u3068\u306a\u308a\u307e\u3059\u3002<\/li>\n
  3. \u30ad\u30e3\u30c3\u30b7\u30e5\u30a2\u30a6\u30c8\u6642\u306b\u3001\u305d\u306e\u6642\u70b9\u306e\u30de\u30eb\u30c1\u30d7\u30e9\u30a4\u30e4\u30fc\u306e\u5024\u306b\u5fdc\u3058\u3066\u52dd\u6557\u304c\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/li>\n
  4. \u30b2\u30fc\u30e0\u3054\u3068\u306e\u300c\u30dc\u30fc\u30ca\u30b9\u300d<\/strong>\u306e\u5272\u5408\u304c\u304a\u5ba2\u69d8\u306e\u30d9\u30c3\u30c8\u306b\u9069\u7528\u3055\u308c\u3001\u6700\u7d42\u7684\u306a\u52dd\u3061\u984d\u307e\u305f\u306f\u52dd\u3061\u30b2\u30fc\u30e0\u3067\u306e\u300c\u5229\u76ca\u300d<\/strong>\u306b\u5408\u8a08\u3055\u308c\u307e\u3059\u3002<\/li>\n<\/ol>\n

    \u5927\u91cf\u306e\u30c7\u30fc\u30bf\u3092\u4fdd\u5b58\u3059\u308b\u305f\u3081\u306bGridDB\u3092\u4f7f\u7528\u3057\u3001\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306b\u30c7\u30fc\u30bf\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3001\u9ad8\u901f\u306a\u51e6\u7406\u3092\u884c\u3046\u4e88\u5b9a\u3067\u3059\u3002<\/p>\n

    GridDB\u3092\u4f7f\u3063\u305f\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3068\u30a4\u30f3\u30dd\u30fc\u30c8<\/h2>\n

    GridDB\u306f\u3001\u9ad8\u3044\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3068\u6700\u9069\u5316\u3092\u5b9f\u73fe\u3057\u305f\u30a4\u30f3\u30e1\u30e2\u30eaNoSQL\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3067\u3001\u7279\u306b\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306b\u304a\u3044\u3066\u4e26\u5217\u51e6\u7406\u306b\u3088\u308b\u9ad8\u3044\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3068\u52b9\u7387\u6027\u3092\u5b9f\u73fe\u3057\u307e\u3059\u3002\u4eca\u56de\u306fGridDB\u306epython\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002\u305d\u3046\u3059\u308b\u3053\u3068\u3067GridDB\u3068python\u3092\u63a5\u7d9a\u3057\u3001\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306b\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u3084\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3092\u884c\u3046\u3053\u3068\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n

    \u30e9\u30a4\u30d6\u30e9\u30ea<\/h3>\n

    \u3044\u304f\u3064\u304b\u306epython\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3057\u3066\u3001\u30c7\u30fc\u30bf\u306e\u524d\u51e6\u7406\u3068\u8996\u899a\u7684\u306a\u5206\u6790\u3092\u884c\u3046\u4e88\u5b9a\u3067\u3059\u3002<\/p>\n

      \n
    1. Pandas\uff1a\u7279\u306b\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u6271\u3046\u969b\u306b\u591a\u7528\u3055\u308c\u308bPython\u30e9\u30a4\u30d6\u30e9\u30ea<\/li>\n
    2. Matplotlib\uff1a\u57fa\u672c\u7684\u306a\u30d7\u30ed\u30c3\u30c8\u3092\u7528\u3044\u3066\u30c7\u30fc\u30bf\u3092\u8996\u899a\u7684\u306b\u8868\u73fe\u3059\u308b\u305f\u3081\u306e\u4e3b\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea<\/li>\n
    3. Numpy\uff1a\u9ad8\u5ea6\u306a\u6570\u5b66\u7684\u8a08\u7b97\u3092\u884c\u3046\u305f\u3081\u306e\u30e9\u30a4\u30d6\u30e9\u30ea<\/li>\n
    4. Sklearn\uff1a\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u4f7f\u7528\u3059\u308b\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u304c\u542b\u307e\u308c\u308b\u30e9\u30a4\u30d6\u30e9\u30ea<\/li>\n<\/ol>\n

      \u524d\u51e6\u7406<\/h3>\n
      \n
      data = pd.read_csv(\"bustabit.csv\")<\/code><\/pre>\n<\/div>\n
      \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304c\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306e\u5f62\u3067\u5909\u6570 “data” \u306b\u4fdd\u5b58\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n
      \u4eca\u56de\u306e\u5206\u6790\u3092\u3088\u308a\u5206\u304b\u308a\u3084\u3059\u304f\u3059\u308b\u305f\u3081\u306b\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u3044\u304f\u3064\u304b\u306e\u30ab\u30e9\u30e0\u3092\u8abf\u6574\u3057\u307e\u3059\u3002’ID’ \u30ab\u30e9\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u4e3b\u30ad\u30fc\u3068\u3057\u3066\u6a5f\u80fd\u3059\u308b\u65b0\u3057\u3044\u30ab\u30e9\u30e0\u306b\u7f6e\u304d\u63db\u3048\u308b\u4e88\u5b9a\u3067\u3059\u3002\u307e\u305f\u3001’PlayDate’ \u3092 ‘Year’ \u306b\u7f6e\u304d\u63db\u3048\u307e\u3059\u3002\u3053\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001\u6642\u9593\u306b\u95a2\u3059\u308b\u66f4\u306a\u308b\u60c5\u5831\u3092\u5fc5\u8981\u3068\u3057\u306a\u3044\u70ba\u3067\u3059\u3002<\/p>\n
      \n
      data = data.drop([\"Id\"], axis = 1)\ndata.reset_index(drop=True, inplace=True)\ndata.index.name = 'ID'\n    \ndata['Year'] = pd.DatetimeIndex(data['PlayDate']).year\ndata = data.drop('PlayDate', axis = 1)<\/code><\/pre>\n<\/div>\n
      \u3053\u308c\u3089\u306f\u3001\u5206\u6790\u306b\u4f7f\u7528\u3059\u308b\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u6b8b\u3063\u3066\u3044\u308b\u5217\u3067\u3059\u3002<\/p>\n
        \n
      1. ID\uff1a\u5f53\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u4e3b\u30ad\u30fc<\/li>\n
      2. GameID\uff1a\u30d0\u30b9\u30bf\u30d3\u30c3\u30c8\u306e\u30b2\u30fc\u30e0\u306b\u95a2\u9023\u3059\u308b\u4e00\u610f\u306eID<\/li>\n
      3. Username\uff1a\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u30d0\u30b9\u30bf\u30d3\u30c3\u30c8\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067\u4f7f\u7528\u3059\u308b\u56fa\u6709\u306e\u540d\u524d<\/li>\n
      4. Bet\uff1a\u3053\u306e\u30b2\u30fc\u30e0\u3067\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u30d9\u30c3\u30c8\u3057\u305f\u30d3\u30c3\u30c8\u6570<\/li>\n
      5. CashedOut – \u3053\u306e\u30d7\u30ec\u30fc\u30e4\u30fc\u304c\u30ad\u30e3\u30c3\u30b7\u30e5\u30a2\u30a6\u30c8\u3057\u305f\u3068\u304d\u306e\u500d\u7387<\/li>\n
      6. Bonus – \u3053\u306e\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u30b2\u30fc\u30e0\u4e2d\u306b\u7372\u5f97\u3057\u305f\u30dc\u30fc\u30ca\u30b9\u5831\u916c\uff08\u5358\u4f4d\uff1a\uff05\uff09<\/li>\n
      7. Profit – \u3053\u306e\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u30b2\u30fc\u30e0\u3067\u7372\u5f97\u3057\u305f\u91d1\u984d\uff08\u30dc\u30fc\u30ca\u30b9\u3092\u542b\u3080\uff09<\/li>\n
      8. BustedAt – \u3053\u306e\u30b2\u30fc\u30e0\u304c\u7834\u7dbb\u3057\u305f\u3068\u304d\u306e\u30de\u30eb\u30c1\u30d7\u30e9\u30a4\u30e4\u30fc\u306e\u5024<\/li>\n
      9. Year – \u30b2\u30fc\u30e0\u304c\u884c\u308f\u308c\u305f\u5e74<\/li>\n<\/ol>\n
        GridDB \u306b\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3092\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3059\u308b\u524d\u306b\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u5b58\u5728\u3059\u308b NULL \u5024\u3092\u51e6\u7406\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30eb\u30fc\u30eb\u3067 NULL \u5024\u3092\u7f6e\u304d\u63db\u3048\u307e\u3059\u3002<\/p>\n
          \n
        1. CashedOut – ‘CashedOut’\u306e\u5024\u304cNA\u306e\u5834\u5408\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u30d0\u30b9\u30c8\u306e\u524d\u306b\u30ad\u30e3\u30c3\u30b7\u30e5\u30a2\u30a6\u30c8\u3067\u304d\u306a\u304b\u3063\u305f\u3053\u3068\u3092\u793a\u3059\u305f\u3081\u306b\u3001’BustedAt’\u306e\u5024\u3088\u308a0.01\u5927\u304d\u304f\u306a\u308b\u3088\u3046\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002<\/li>\n
        2. Profit – Profit\u306e\u5024\u304cNA\u306e\u5834\u5408\u3001\u305d\u306e\u30b2\u30fc\u30e0\u3067\u306e\u30d7\u30ec\u30a4\u30e4\u30fc\u306e\u5229\u76ca\u304c\u306a\u3044\u3053\u3068\u3092\u793a\u3059\u305f\u3081\u306b0\u306b\u8a2d\u5b9a\u3055\u308c\u307e\u3059\u3002<\/li>\n
        3. Bonus – Bonus\u306e\u5024\u304cNA\u306e\u5834\u5408\u3001\u305d\u306e\u30b2\u30fc\u30e0\u3067\u306f\u30d7\u30ec\u30a4\u30e4\u30fc\u306b\u30dc\u30fc\u30ca\u30b9\u304c\u306a\u304b\u3063\u305f\u3053\u3068\u3092\u793a\u3059\u305f\u3081\u30010\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
          \n
          data = data.assign(CashedOut = np.where((data['CashedOut'].isnull()),data['BustedAt'] + .01, data['CashedOut']))\ndata = data.assign(Profit = np.where((data['Profit'].isnull()), 0 , data['Profit']))\ndata = data.assign(Profit = np.where((data['Bonus'].isnull()), 0 , data['Bonus']))<\/code><\/pre>\n<\/div>\n
          \u30c7\u30fc\u30bf\u306e\u524d\u51e6\u7406\u304c\u5b8c\u4e86\u3057\u305f\u306e\u3067\u3001\u4eca\u5ea6\u306f\u30c7\u30fc\u30bf\u3092\u30ed\u30fc\u30ab\u30eb\u30c9\u30e9\u30a4\u30d6\u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/p>\n
          \n
          data.to_csv(\"preprocessed.csv\")<\/code><\/pre>\n<\/div>\n
          \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092GridDB\u306b\u66f8\u304d\u51fa\u3059<\/h3>\n
          GridDB\u306b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3059\u308b\u305f\u3081\u306b\u3001\u524d\u51e6\u7406\u3055\u308c\u305f\u30c7\u30fc\u30bf\u3092\u542b\u3080CSV\u30d5\u30a1\u30a4\u30eb\u3092\u8aad\u307f\u8fbc\u3080\u3053\u3068\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n
          \n
          data_processed = pd.read_csv(\"preprocessed.csv\")<\/code><\/pre>\n<\/div>\n
          \u3053\u3053\u3067\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u3066\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u30b9\u30ad\u30fc\u30de\u3092GridDB\u306b\u6e21\u3057\u3001\u884c\u60c5\u5831\u3092\u633f\u5165\u3059\u308b\u524d\u306b\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u30c7\u30b6\u30a4\u30f3\u3092\u751f\u6210\u3067\u304d\u308b\u3088\u3046\u306b\u3057\u307e\u3059\u3002\u6b21\u306b\u3001GridDB\u306b\u30c7\u30fc\u30bf\u3092\u633f\u5165\u3057\u307e\u3059\u3002<\/p>\n
          \n
          #Create container \ndata_container = \"data_container\"\n\n# Create containerInfo\ndata_containerInfo = griddb.ContainerInfo(data_container,\n                [[\"ID\", griddb.Type.FLOAT],\n                [\"GameID\", griddb.Type.FLOAT],\n                [\"Username\", griddb.Type.STRING],\n                [\"Bet\", griddb.Type.FLOAT],\n                [\"CashedOut\", griddb.Type.FLOAT],\n                [\"Bonus\", griddb.Type.FLOAT],\n                [\"Profit\", griddb.Type.FLOAT],\n                [\"BustedAt\", griddb.Type.FLOAT],\n                [\"Year\", griddb.Type.INTEGER]],\n                griddb.ContainerType.COLLECTION, True)\n    \ndata_columns = gridstore.put_container(data_containerInfo)\n\nprint(\"container created and columns added\")\n    \n# Put rows\ndata_columns.put_rows(data_processed)    \nprint(\"Data Inserted using the DataFrame\")<\/code><\/pre>\n<\/div>\n
          \u3053\u308c\u3067\u3001GridDB\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3078\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u306b\u6210\u529f\u3057\u307e\u3057\u305f\u3002<\/p>\n
          GridDB\u304b\u3089\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u8aad\u307f\u8fbc\u3080<\/h3>\n
          GridDB\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u304b\u3089\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u53d6\u308a\u8fbc\u3080\u305f\u3081\u306b\u3001SQL\u306b\u4f3c\u305fGridDB\u306e\u30af\u30a8\u30ea\u8a00\u8a9e\u3067\u3042\u308bTQL\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u306b\u3057\u307e\u3059\u3002\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u3001\u305d\u306e\u4e2d\u306b\u53d6\u308a\u8fbc\u3093\u3060\u30c7\u30fc\u30bf\u3092\u683c\u7d0d\u3057\u307e\u3059\u3002<\/p>\n
          \n
          # Define the container names\ndata_container = \"data_container\"\n\n# Get the containers\nobtained_data = gridstore.get_container(data_container)\n    \n# Fetch all rows - language_tag_container\nquery = obtained_data.query(\"select *\")<\/code><\/pre>\n<\/div>\n
          \u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u306f\u3001\u5217\u60c5\u5831\u306e\u9806\u306b\u884c\u3092\u62bd\u51fa\u3057\u3066\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u4fdd\u5b58\u3057\u3001\u30c7\u30fc\u30bf\u306e\u53ef\u8996\u5316\u3068\u5206\u6790\u306b\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/p>\n
          \n
          # Convert the list to a pandas data frame\ndata = pd.DataFrame(retrieved_data, columns=['ID', 'GameID',\"Username\",\n                   \"Bet\",\"CashedOut\" ,\"Bonus\", \"Profit\",\"BustedAt\",\"Year\"])<\/code><\/pre>\n<\/div>\n
          \u3053\u308c\u3067\u30c7\u30fc\u30bf\u304cpandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0 “data “\u306b\u4fdd\u5b58\u3055\u308c\u3001\u5f15\u304d\u7d9a\u304d\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u4f7f\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002<\/p>\n
          \u30c7\u30fc\u30bf\u5206\u6790<\/h2>\n
          \u6211\u3005\u306f\u3001Kmeans\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u4f7f\u7528\u3057\u3066\u3001\u30d7\u30ec\u30fc\u30e4\u30fc\u30925\u3064\u306e\u7570\u306a\u308b\u30bb\u30c3\u30c8\u306b\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3059\u308b\u4e88\u5b9a\u3067\u3059\u3002\u6211\u3005\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u3088\u308a\u3088\u304f\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u30013\u3064\u306e\u65b0\u3057\u3044\u30ab\u30e9\u30e0\u3092\u5c0e\u5165\u3059\u308b\u3053\u3068\u304b\u3089\u59cb\u3081\u307e\u3059\u3002\u65b0\u3057\u3044\u30ab\u30e9\u30e0\u306f\u4ee5\u4e0b\u306e\u30eb\u30fc\u30eb\u306b\u57fa\u3065\u304f\u3082\u306e\u3067\u3059\u3002<\/p>\n
            \n
          1. Losses – \u5229\u76ca\u306e\u65b0\u3057\u3044\u5024\u304c\u30bc\u30ed\u306e\u5834\u5408\u3001\u305d\u306e\u30b2\u30fc\u30e0\u3067\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u5931\u3063\u305f\u91d1\u984d\u3092\u8a2d\u5b9a\u3057\u307e\u3059\u3002\u305d\u3046\u3067\u306a\u3044\u5834\u5408\u306f\u3001\u30bc\u30ed\u306b\u8a2d\u5b9a\u3057\u307e\u3059\u3002\u3053\u306e\u5024\u306f\u5e38\u306b\u30bc\u30ed\u304b\u30de\u30a4\u30ca\u30b9\u3067\u3042\u308b\u3079\u304d\u3067\u3059\u3002<\/li>\n
          2. GameWon – \u3053\u306e\u30b2\u30fc\u30e0\u3067\u30e6\u30fc\u30b6\u30fc\u304c\u5229\u76ca\u3092\u5f97\u305f\u5834\u5408\u3001\u5024\u306f1\u3067\u3042\u308a\u3001\u305d\u3046\u3067\u306a\u3044\u5834\u5408\u306f0\u3067\u3042\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/li>\n
          3. GameLost – \u30e6\u30fc\u30b6\u304c\u3053\u306e\u30b2\u30fc\u30e0\u3067\u8ca0\u3051\u305f\u5834\u5408\u306f 1\u3001\u305d\u3046\u3067\u306a\u3044\u5834\u5408\u306f 0 \u3068\u3059\u308b\u3002<\/li>\n<\/ol>\n
            \n
            data = data.assign(Losses = np.where((data['Profit'] == 0 ), - data['Bet'], 0))\ndata = data.assign(GameWon = np.where((data['Profit'] == 0 ), 0 , 1))\ndata = data.assign(GameLost = np.where((data['Profit'] == 0 ), 1, 0))<\/code><\/pre>\n<\/div>\n
            \u6761\u4ef6\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3057\u3001\u7279\u5b9a\u306e\u884c\u3092\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
            1.  \u6700\u3082\u9ad8\u3044\u500d\u7387: ‘BustedAt’ \u306e\u5024\u304c\u6700\u3082\u9ad8\u3044\u30b2\u30fc\u30e0\u3068\u30e6\u30fc\u30b6\u30fc\u306e\u8a73\u7d30<\/p>\n
            \n
            data.iloc[data['BustedAt'].idxmax()]<\/code><\/pre>\n<\/div>\n
            \"\"<\/a><\/p>\n
            2.  \u6700\u9ad8\u30d9\u30c3\u30c8\u984d: \u6700\u3082\u9ad8\u984d\u306a\u30d9\u30c3\u30c8\u984d\u306e\u30b2\u30fc\u30e0\u3068\u30e6\u30fc\u30b6\u30fc\u306e\u8a73\u7d30<\/p>\n
            \n
            data.iloc[data['Bet'].idxmax()]<\/code><\/pre>\n<\/div>\n
            \"\"<\/a><\/p>\n
            3.  \u6700\u3082\u9ad8\u3044\u5229\u76ca: \u6700\u3082\u9ad8\u3044\u5229\u76ca\u3092\u5f97\u305f\u30b2\u30fc\u30e0\u3068\u30e6\u30fc\u30b6\u30fc\u306e\u8a73\u7d30<\/p>\n
            \n
            data.iloc[data['Profit'].idxmax()]<\/code><\/pre>\n<\/div>\n
            \"\"<\/a><\/p>\n
            \u6b21\u306b\u3001\u300c\u30e6\u30fc\u30b6\u30fc\u540d\u300d\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3001Bustabit\u3067\u306e\u30ae\u30e3\u30f3\u30d6\u30eb\u5c65\u6b74\u3092\u901a\u3058\u3066\u3001\u5404\u30e6\u30fc\u30b6\u30fc\u306e\u53ce\u76ca\u3001\u52dd\u3061\u3001\u8ca0\u3051\u3092\u7279\u5b9a\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u5404\u30e6\u30fc\u30b6\u30fc\u306e\u30ae\u30e3\u30f3\u30d6\u30eb\u7fd2\u6163\u3092\u7279\u5b9a\u3057\u3001\u30d7\u30ec\u30a4\u30e4\u30fc\u30b0\u30eb\u30fc\u30d7\u9593\u306e\u95a2\u4fc2\u3084\u985e\u4f3c\u6027\u3092\u3088\u308a\u7406\u89e3\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
            \n
            data_groupby = data.groupby('Username').agg({'CashedOut': 'mean',\n                                             'Bet': 'mean',\n                                             'Profit': 'sum',\n                                             'Losses': 'sum',\n                                             'GameWon': 'sum',\n                                             'GameLost': 'sum'})<\/code><\/pre>\n<\/div>\n
            \u4eca\u3001\u30c7\u30fc\u30bf\u306f\u3053\u306e\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n
            \"\"<\/a><\/p>\n
            \u30af\u30e9\u30b9\u30bf\u5f62\u6210\u306b\u79fb\u308b\u524d\u306b\u3001\u307e\u305a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5168\u4f53\u306e\u30c7\u30fc\u30bf\u3092\u6a19\u6e96\u5316\u3057\u3088\u3046\u3068\u601d\u3044\u307e\u3059\u3002\u3053\u308c\u306f\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u6a19\u6e96\u7684\u306a\u6e2c\u5b9a\u5358\u4f4d\u306b\u5909\u63db\u3057\u3001\u6211\u3005\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u3088\u308a\u52b9\u7387\u7684\u306b\u3059\u308b\u3082\u306e\u3067\u3059\u3002\u6a19\u6e96\u5316\u95a2\u6570\u3092\u4f5c\u6210\u3057\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5404\u6570\u5024\u5217\u306b\u9069\u7528\u3057\u307e\u3059\u3002<\/p>\n
            \n
            def standardization_function(x):\n    return (x-np.mean(x)\/np.std(x))\n\n\nbustabit_standardized = data_groupby.apply(lambda x: standardization_function(x) \n                                           if ((x.dtype == float) or (type(x) == int)) \n<\/code><\/pre>\n<\/div>\n
            \u6700\u5f8c\u306e\u30b9\u30c6\u30c3\u30d7\u306f\u3001sklearn\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3063\u3066\u3001\u9078\u624b\u306e\u30af\u30e9\u30b9\u30bf\u30fc\u30925\u3064\u306e\u30bb\u30c3\u30c8\u306b\u5206\u3051\u308b\u3053\u3068\u3067\u3059\u3002<\/p>\n
            \n
            kmeans = KMeans(n_clusters=5, random_state=0).fit(bustabit_standardized)\nclustering_data = pd.DataFrame()  \nclustering_data['cluster'] = kmeans.predict(bustabit_standardized)<\/code><\/pre>\n<\/div>\n
            \u3053\u3053\u3067\u3001\u79c1\u305f\u3061\u306e\u30c7\u30fc\u30bf\u30925\u3064\u306e\u30af\u30e9\u30b9\u30bf\u30fc\u306b\u5206\u3051\u305f\u3082\u306e\u3092\u57a3\u9593\u898b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
            \n
            summary = clustering_data.groupby(\"cluster\").mean()\nsummary['count'] = clustering_data['cluster'].value_counts()<\/code><\/pre>\n<\/div>\n
            \"\"<\/a><\/p>\n
            \u7d50\u8ad6<\/h2>\n
            \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u6700\u7d42\u7d50\u679c\u3092\u898b\u308b\u3068\u3001\u307b\u3068\u3093\u3069\u306e\u30d7\u30ec\u30a4\u30e4\u30fc\u304c\u540c\u3058\u3088\u3046\u306a\u5c5e\u6027\u3092\u6301\u3061\u3001\u540c\u3058\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u30b0\u30eb\u30fc\u30d7\u306b\u5c5e\u3059\u308b\u4e00\u65b9\u3067\u3001\u6a19\u6e96\u7684\u306a\u884c\u52d5\u3068\u306f\u7570\u306a\u308b\u30d7\u30ec\u30a4\u30e4\u30fc\u306e\u4f8b\u5916\u306f\u3054\u304f\u308f\u305a\u304b\u3067\u3042\u308b\u3068\u7d50\u8ad6\u4ed8\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3059\u3079\u3066\u306e\u5206\u6790\u306f\u3001\u30d0\u30c3\u30af\u30a8\u30f3\u30c9\u3067GridDB\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3092\u4f7f\u7528\u3057\u3066\u884c\u308f\u308c\u305f\u305f\u3081\u3001\u7d71\u5408\u306f\u30b7\u30fc\u30e0\u30ec\u30b9\u304b\u3064\u52b9\u7387\u7684\u306b\u884c\u308f\u308c\u307e\u3057\u305f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
            \u306f\u3058\u3081\u306b \u4eba\u9593\u306e\u884c\u52d5\u3092\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u3001\u5384\u4ecb\u3067\u6ce8\u610f\u3092\u8981\u3059\u308b\u4f5c\u696d\u3067\u3059\u3002\u3042\u308b\u72b6\u6cc1\u4e0b\u3067\u4eba\u304c\u3069\u306e\u3088\u3046\u306b\u884c\u52d5\u3059\u308b\u306e\u304b\u3001\u3069\u306e\u3088\u3046\u306a\u5224\u65ad\u3092\u4e0b\u3059\u306e\u304b\u3092\u8aac\u660e\u3059\u308b\u306e\u306f\u7c21\u5358\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3057\u3001\u5358\u7d14\u3067\u3082\u3042\u308a\u307e\u305b\u3093\u3002\u3057\u304b\u3057\u3001\u4eba\u3092\u89b3\u5bdf\u3057\u3001\u6b21\u306b\u4f55\u3092\u3059\u308b\u304b […]<\/p>\n","protected":false},"author":41,"featured_media":49386,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50793","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"\nGridDB\u3092\u7528\u3044\u305fBustabit\u306e\u30ae\u30e3\u30f3\u30d6\u30eb\u884c\u52d5\u306e\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0 | GridDB: Open Source Time Series Database for IoT<\/title>\n<meta name=\"description\" content=\"\u306f\u3058\u3081\u306b\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/ja\/\u672a\u5206\u985e\/clustering-bustabit-gambling-behavior-using-griddb\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" 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