{"id":45601,"date":"2025-08-15T19:19:13","date_gmt":"2025-08-15T10:19:13","guid":{"rendered":"https:\/\/techgym.jp\/?p=45601"},"modified":"2025-08-15T19:19:15","modified_gmt":"2025-08-15T10:19:15","slug":"dataframeseries","status":"publish","type":"post","link":"https:\/\/techgym.jp\/column\/dataframeseries\/","title":{"rendered":"Pandas\u3068Python\u30ea\u30b9\u30c8\u3092\u76f8\u4e92\u5909\u63db\uff01DataFrame\u30fbSeries\u3092\u4f7f\u3044\u3053\u306a\u3059\u57fa\u672c \u2194\ufe0f"},"content":{"rendered":"\n

\n

\u00a0<\/p>\n

Pandas\u3067\u30c7\u30fc\u30bf\u5206\u6790\u3092\u884c\u3046\u969b\u3001DataFrame<\/code>\u3084Series<\/code>\u3068\u3044\u3063\u305fPandas\u72ec\u81ea\u306e\u30c7\u30fc\u30bf\u69cb\u9020\u3068\u3001Python\u6a19\u6e96\u306e**\u30ea\u30b9\u30c8\uff08list\uff09**\u306e\u9593\u3067\u30c7\u30fc\u30bf\u3092\u3084\u308a\u53d6\u308a\u3059\u308b\u5834\u9762\u306f\u983b\u7e41\u306b\u767a\u751f\u3057\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u5916\u90e8\u304b\u3089\u53d6\u5f97\u3057\u305f\u30ea\u30b9\u30c8\u30c7\u30fc\u30bf\u3092Pandas\u3067\u5206\u6790\u3057\u305f\u3044\u3001\u3042\u308b\u3044\u306fPandas\u3067\u51e6\u7406\u3057\u305f\u7d50\u679c\u3092\u30ea\u30b9\u30c8\u5f62\u5f0f\u3067\u5225\u306e\u30b7\u30b9\u30c6\u30e0\u306b\u6e21\u3057\u305f\u3044\u3001\u3068\u3044\u3063\u305f\u30b1\u30fc\u30b9\u3067\u3059\u3002<\/p>\n

\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001Pandas\u306eDataFrame<\/code>\u3068Series<\/code>\u3001\u305d\u3057\u3066Python\u306e\u30ea\u30b9\u30c8\u3092\u30b9\u30e0\u30fc\u30ba\u306b\u76f8\u4e92\u5909\u63db\u3059\u308b\u65b9\u6cd5\u3092\u3001\u5177\u4f53\u7684\u306a\u30b3\u30fc\u30c9\u4f8b\u3092\u4ea4\u3048\u306a\u304c\u3089\u8a73\u3057\u304f\u89e3\u8aac\u3057\u307e\u3059\u3002<\/p>\n

\n

\u00a0<\/p>\n

Pandas\u3068Python\u30ea\u30b9\u30c8\u3001\u305d\u308c\u305e\u308c\u306e\u7279\u5fb4\u3092\u304a\u3055\u3089\u3044 \ud83d\udcda<\/h2>\n

\u00a0<\/p>\n

\u76f8\u4e92\u5909\u63db\u306e\u524d\u306b\u3001\u305d\u308c\u305e\u308c\u306e\u30c7\u30fc\u30bf\u69cb\u9020\u306e\u57fa\u672c\u7684\u306a\u7279\u5fb4\u3092\u78ba\u8a8d\u3057\u3066\u304a\u304d\u307e\u3057\u3087\u3046\u3002<\/p>\n

\u00a0<\/p>\n

Python\u30ea\u30b9\u30c8\uff1a\u67d4\u8edf\u306a\u6c4e\u7528\u30b3\u30f3\u30c6\u30ca<\/h3>\n

\u00a0<\/p>\n

Python\u306e\u30ea\u30b9\u30c8<\/b>\u306f\u3001\u9806\u5e8f\u4ed8\u3051\u3089\u308c\u305f\u8981\u7d20\u306e\u96c6\u307e\u308a\u3067\u3042\u308a\u3001\u7570\u306a\u308b\u30c7\u30fc\u30bf\u578b\u306e\u8981\u7d20\u3092\u683c\u7d0d\u3067\u304d\u307e\u3059\u3002\u975e\u5e38\u306b\u67d4\u8edf\u3067\u3001\u30c7\u30fc\u30bf\u306e\u8ffd\u52a0\u30fb\u524a\u9664\u304c\u5bb9\u6613\u306a\u6c4e\u7528\u7684\u306a\u30c7\u30fc\u30bf\u69cb\u9020\u3067\u3059\u3002<\/p>\n

\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
# Python\u30ea\u30b9\u30c8\u306e\u4f8b<\/span>\nmy_list = [1<\/span>, 'apple'<\/span>, 3.14<\/span>, True<\/span>]\nprint(f\"Python\u30ea\u30b9\u30c8: {my_list}<\/span>\"<\/span>)\nprint(f\"\u578b: {type<\/span>(my_list)}<\/span>\"<\/span>)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
Pandas Series\uff1a1\u6b21\u5143\u306e\u30e9\u30d9\u30eb\u4ed8\u304d\u914d\u5217<\/h3>\n
\u00a0<\/p>\n
Pandas\u306e**Series<\/code>**\u306f\u30011\u6b21\u5143\u306e\u30e9\u30d9\u30eb\u4ed8\u304d\u914d\u5217\u3067\u3001\u5358\u4e00\u306e\u30c7\u30fc\u30bf\u578b\u306e\u8981\u7d20\u3092\u52b9\u7387\u7684\u306b\u6271\u3044\u307e\u3059\u3002\u5404\u8981\u7d20\u306b\u306f\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u304c\u81ea\u52d5\u7684\u306b\u4ed8\u4e0e\u3055\u308c\u307e\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\n# Series\u306e\u4f8b<\/span>\nmy_series = pd.Series([10<\/span>, 20<\/span>, 30<\/span>], name='\u58f2\u4e0a'<\/span>)\nprint(\"\\n--- Pandas Series ---\"<\/span>)\nprint(my_series)\nprint(f\"\u578b: {type<\/span>(my_series)}<\/span>\"<\/span>)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
Pandas DataFrame\uff1a2\u6b21\u5143\u306e\u8868\u5f62\u5f0f\u30c7\u30fc\u30bf\u69cb\u9020<\/h3>\n
\u00a0<\/p>\n
Pandas\u306e**DataFrame<\/code>**\u306f\u3001\u8907\u6570\u306e\u5217\u3068\u884c\u3092\u6301\u30642\u6b21\u5143\u306e\u8868\u5f62\u5f0f\u30c7\u30fc\u30bf\u69cb\u9020\u3067\u3059\u3002\u5404\u5217\u306fSeries<\/code>\u306e\u96c6\u307e\u308a\u3068\u8003\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u3001\u5217\u3054\u3068\u306b\u7570\u306a\u308b\u30c7\u30fc\u30bf\u578b\u3092\u6301\u3064\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\n# DataFrame\u306e\u4f8b<\/span>\nmy_df = pd.DataFrame({\n    '\u540d\u524d'<\/span>: ['Alice'<\/span>, 'Bob'<\/span>],\n    '\u5e74\u9f62'<\/span>: [25<\/span>, 30<\/span>]\n})\nprint(\"\\n--- Pandas DataFrame ---\"<\/span>)\nprint(my_df)\nprint(f\"\u578b: {type<\/span>(my_df)}<\/span>\"<\/span>)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\n
\u00a0<\/p>\n
Python\u30ea\u30b9\u30c8 \u27a1\ufe0f Pandas\u3078\u306e\u5909\u63db \u2b06\ufe0f<\/h2>\n
\u00a0<\/p>\n
Python\u306e\u30ea\u30b9\u30c8\u304b\u3089Series<\/code>\u3084DataFrame<\/code>\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3092\u898b\u3066\u3044\u304d\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u00a0<\/p>\n
1. \u30ea\u30b9\u30c8\u304b\u3089Series\u3078\u306e\u5909\u63db<\/h3>\n
\u00a0<\/p>\n
\u6700\u3082\u7c21\u5358\u3067\u76f4\u63a5\u7684\u306a\u5909\u63db\u3067\u3059\u3002\u30ea\u30b9\u30c8\u3092pd.Series()<\/code>\u306e\u30b3\u30f3\u30b9\u30c8\u30e9\u30af\u30bf\u306b\u6e21\u3059\u3060\u3051\u3067\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\nmy_list_data = [100<\/span>, 200<\/span>, 300<\/span>]\ns = pd.Series(my_list_data)\nprint(\"--- \u30ea\u30b9\u30c8\u304b\u3089Series\u3078 ---\"<\/span>)\nprint(s)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
2. \u30ea\u30b9\u30c8\u304b\u3089DataFrame\u3078\u306e\u5909\u63db<\/h3>\n
\u00a0<\/p>\n
\u30ea\u30b9\u30c8\u306e\u5f62\u5f0f\u306b\u3088\u3063\u3066\u3001DataFrame<\/code>\u306e\u4f5c\u6210\u65b9\u6cd5\u304c\u5909\u308f\u308a\u307e\u3059\u3002<\/p>\n
\u00a0<\/p>\n
a. \u8f9e\u66f8\u306e\u30ea\u30b9\u30c8\u304b\u3089DataFrame\u3078 (\u63a8\u5968)<\/h4>\n
\u00a0<\/p>\n
\u5404\u8f9e\u66f8\u304c1\u3064\u306e\u884c\u3092\u8868\u3057\u3001\u8f9e\u66f8\u306e\u30ad\u30fc\u304c\u5217\u540d\u306b\u306a\u308b\u305f\u3081\u3001\u6700\u3082\u76f4\u611f\u7684\u3067\u63a8\u5968\u3055\u308c\u308b\u65b9\u6cd5\u3067\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\nlist_of_dicts = [\n    {'\u540d\u524d'<\/span>: 'Alice'<\/span>, '\u5e74\u9f62'<\/span>: 25<\/span>},\n    {'\u540d\u524d'<\/span>: 'Bob'<\/span>, '\u5e74\u9f62'<\/span>: 30<\/span>}\n]\ndf_from_list_dicts = pd.DataFrame(list_of_dicts)\nprint(\"\\n--- \u8f9e\u66f8\u306e\u30ea\u30b9\u30c8\u304b\u3089DataFrame\u3078 ---\"<\/span>)\nprint(df_from_list_dicts)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
b. \u30ea\u30b9\u30c8\u306e\u30ea\u30b9\u30c8\u304b\u3089DataFrame\u3078<\/h4>\n
\u00a0<\/p>\n
\u5404\u5185\u5074\u306e\u30ea\u30b9\u30c8\u304c1\u3064\u306e\u884c\u3092\u8868\u3057\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001columns<\/code>\u5f15\u6570\u3067\u5217\u540d\u3092\u6307\u5b9a\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\nlist_of_lists = [\n    ['Alice'<\/span>, 25<\/span>, 'Tokyo'<\/span>],\n    ['Bob'<\/span>, 30<\/span>, 'Osaka'<\/span>]\n]\ndf_from_list_lists = pd.DataFrame(list_of_lists, columns=['\u540d\u524d'<\/span>, '\u5e74\u9f62'<\/span>, '\u90fd\u5e02'<\/span>])\nprint(\"\\n--- \u30ea\u30b9\u30c8\u306e\u30ea\u30b9\u30c8\u304b\u3089DataFrame\u3078 ---\"<\/span>)\nprint(df_from_list_lists)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\n
\u00a0<\/p>\n
Pandas \u27a1\ufe0f Python\u30ea\u30b9\u30c8\u3078\u306e\u5909\u63db \u2b07\ufe0f<\/h2>\n
\u00a0<\/p>\n
Series<\/code>\u3084DataFrame<\/code>\u304b\u3089Python\u30ea\u30b9\u30c8\u306b\u5909\u63db\u3059\u308b\u65b9\u6cd5\u3092\u898b\u3066\u3044\u304d\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u00a0<\/p>\n
1. Series\u304b\u3089\u30ea\u30b9\u30c8\u3078\u306e\u5909\u63db\uff1a.tolist()<\/code><\/h3>\n
\u00a0<\/p>\n
Series<\/code>\u306e\u30c7\u30fc\u30bf\u3092Python\u30ea\u30b9\u30c8\u306b\u5909\u63db\u3059\u308b\u306b\u306f\u3001.tolist()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u3046\u306e\u304c\u6700\u3082\u7c21\u6f54\u3067\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\ns = pd.Series([10<\/span>, 20<\/span>, 30<\/span>], name='\u58f2\u4e0a'<\/span>)\nlist_from_series = s.tolist()\nprint(\"--- Series\u304b\u3089\u30ea\u30b9\u30c8\u3078 ---\"<\/span>)\nprint(list_from_series)\nprint(f\"\u578b: {type<\/span>(list_from_series)}<\/span>\"<\/span>)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
2. DataFrame\u304b\u3089\u30ea\u30b9\u30c8\u3078\u306e\u5909\u63db<\/h3>\n
\u00a0<\/p>\n
DataFrame<\/code>\u304b\u3089\u30ea\u30b9\u30c8\u3078\u306e\u5909\u63db\u306f\u3001\u3069\u306e\u3088\u3046\u306b\u30ea\u30b9\u30c8\u5316\u3057\u305f\u3044\u304b\u306b\u3088\u3063\u3066\u65b9\u6cd5\u304c\u7570\u306a\u308a\u307e\u3059\u3002<\/p>\n
\u00a0<\/p>\n
a. \u7279\u5b9a\u306e\u5217\uff08Series\uff09\u3092\u30ea\u30b9\u30c8\u306b\u5909\u63db<\/h4>\n
\u00a0<\/p>\n
DataFrame<\/code>\u304b\u3089\u76ee\u7684\u306e\u5217\u3092Series<\/code>\u3068\u3057\u3066\u9078\u629e\u3057\u3001\u305d\u306eSeries<\/code>\u306b\u5bfe\u3057\u3066.tolist()<\/code>\u3092\u9069\u7528\u3057\u307e\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\ndf = pd.DataFrame({\n    '\u540d\u524d'<\/span>: ['Alice'<\/span>, 'Bob'<\/span>],\n    '\u5e74\u9f62'<\/span>: [25<\/span>, 30<\/span>]\n})\n\nnames_list = df['\u540d\u524d'<\/span>].tolist()\nprint(\"\\n--- DataFrame\u306e\u7279\u5b9a\u306e\u5217\u3092\u30ea\u30b9\u30c8\u3078 ---\"<\/span>)\nprint(names_list)\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
b. \u5404\u884c\u3092\u8f9e\u66f8\u306e\u30ea\u30b9\u30c8\u306b\u5909\u63db\uff1a.to_dict(orient='records')<\/code><\/h4>\n
\u00a0<\/p>\n
DataFrame<\/code>\u306e\u5404\u884c\u30921\u3064\u306e\u8f9e\u66f8\u3068\u3057\u3066\u6271\u3044\u3001\u305d\u308c\u3089\u3092\u307e\u3068\u3081\u305f\u30ea\u30b9\u30c8\u306b\u5909\u63db\u3057\u307e\u3059\u3002Web API\u3078\u306e\u30c7\u30fc\u30bf\u9001\u4fe1\u306a\u3069\u3067\u975e\u5e38\u306b\u4fbf\u5229\u3067\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\ndf = pd.DataFrame({\n    '\u540d\u524d'<\/span>: ['Alice'<\/span>, 'Bob'<\/span>],\n    '\u5e74\u9f62'<\/span>: [25<\/span>, 30<\/span>]\n})\n\nlist_of_row_dicts = df.to_dict(orient='records'<\/span>)\nprint(\"\\n--- DataFrame\u3092\u8f9e\u66f8\u306e\u30ea\u30b9\u30c8\u3078 ---\"<\/span>)\nprint(list_of_row_dicts)\n# \u51fa\u529b\u4f8b: [{'\u540d\u524d': 'Alice', '\u5e74\u9f62': 25}, {'\u540d\u524d': 'Bob', '\u5e74\u9f62': 30}]<\/span>\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u00a0<\/p>\n
c. \u5404\u884c\u3092\u30ea\u30b9\u30c8\u306e\u30ea\u30b9\u30c8\u306b\u5909\u63db\uff1a.values.tolist()<\/code><\/h4>\n
\u00a0<\/p>\n
DataFrame<\/code>\u306e\u5404\u884c\u30921\u3064\u306e\u30ea\u30b9\u30c8\u3068\u3057\u3066\u6271\u3044\u3001\u305d\u308c\u3089\u3092\u307e\u3068\u3081\u305f\u30ea\u30b9\u30c8\u306b\u5909\u63db\u3057\u307e\u3059\u3002<\/p>\n
\n
Python<\/span>\n
\u00a0<\/div>\n<\/div>\n
\n
\n
import<\/span> pandas as<\/span> pd\n\ndf = pd.DataFrame({\n    '\u540d\u524d'<\/span>: ['Alice'<\/span>, 'Bob'<\/span>],\n    '\u5e74\u9f62'<\/span>: [25<\/span>, 30<\/span>]\n})\n\nlist_of_row_lists = df.values.tolist()\nprint(\"\\n--- DataFrame\u3092\u30ea\u30b9\u30c8\u306e\u30ea\u30b9\u30c8\u3078 ---\"<\/span>)\nprint(list_of_row_lists)\n# \u51fa\u529b\u4f8b: [['Alice', 25], ['Bob', 30]]<\/span>\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\n
\u00a0<\/p>\n
\u307e\u3068\u3081<\/h2>\n
\u00a0<\/p>\n
Pandas\u306eDataFrame<\/code>\u3001Series<\/code>\u3068Python\u306e\u30ea\u30b9\u30c8\u3092\u76f8\u4e92\u306b\u5909\u63db\u3059\u308b\u80fd\u529b\u306f\u3001\u30c7\u30fc\u30bf\u5206\u6790\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306b\u304a\u3051\u308b\u67d4\u8edf\u6027\u3092\u5927\u304d\u304f\u9ad8\u3081\u307e\u3059\u3002<\/p>\n
    \n
  • \n
    Python\u30ea\u30b9\u30c8\u304b\u3089Pandas\u3078<\/b>:<\/p>\n
      \n
    • \n
      \u30ea\u30b9\u30c8 \u27a1\ufe0f Series<\/code>: pd.Series(my_list)<\/code><\/p>\n<\/li>\n
    • \n
      \u8f9e\u66f8\u306e\u30ea\u30b9\u30c8 \u27a1\ufe0f DataFrame<\/code>: pd.DataFrame(list_of_dicts)<\/code><\/p>\n<\/li>\n
    • \n
      \u30ea\u30b9\u30c8\u306e\u30ea\u30b9\u30c8 \u27a1\ufe0f DataFrame<\/code>: pd.DataFrame(list_of_lists, columns=...)<\/code><\/p>\n<\/li>\n<\/ul>\n<\/li>\n
    • \n
      Pandas\u304b\u3089Python\u30ea\u30b9\u30c8\u3078<\/b>:<\/p>\n
        \n
      • \n
        Series<\/code> \u27a1\ufe0f \u30ea\u30b9\u30c8: my_series.tolist()<\/code><\/p>\n<\/li>\n
      • \n
        DataFrame<\/code>\u306e\u5217 \u27a1\ufe0f \u30ea\u30b9\u30c8: df['col_name'].tolist()<\/code><\/p>\n<\/li>\n
      • \n
        DataFrame<\/code>\u5168\u4f53 \u27a1\ufe0f \u8f9e\u66f8\u306e\u30ea\u30b9\u30c8: df.to_dict(orient='records')<\/code><\/p>\n<\/li>\n
      • \n
        DataFrame<\/code>\u5168\u4f53 \u27a1\ufe0f \u30ea\u30b9\u30c8\u306e\u30ea\u30b9\u30c8: df.values.tolist()<\/code><\/p>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
        \u3053\u308c\u3089\u306e\u5909\u63db\u30c6\u30af\u30cb\u30c3\u30af\u3092\u30de\u30b9\u30bf\u30fc\u3059\u308b\u3053\u3068\u3067\u3001Pandas\u3068Python\u306e\u5f37\u529b\u306a\u6a5f\u80fd\u3092\u6700\u5927\u9650\u306b\u6d3b\u7528\u3057\u3001\u3088\u308a\u30b9\u30e0\u30fc\u30ba\u3067\u52b9\u7387\u7684\u306a\u30c7\u30fc\u30bf\u51e6\u7406\u304c\u53ef\u80fd\u306b\u306a\u308b\u3067\u3057\u3087\u3046\u3002<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
        \u00a0 Pandas\u3067\u30c7\u30fc\u30bf\u5206\u6790\u3092\u884c\u3046\u969b\u3001DataFrame\u3084Series\u3068\u3044\u3063\u305fPandas\u72ec\u81ea\u306e\u30c7\u30fc\u30bf\u69cb\u9020\u3068\u3001Python\u6a19\u6e96\u306e**\u30ea\u30b9\u30c8\uff08list\uff09**\u306e\u9593\u3067\u30c7\u30fc\u30bf\u3092\u3084\u308a\u53d6\u308a\u3059\u308b\u5834\u9762\u306f\u983b\u7e41\u306b\u767a\u751f\u3057\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u5916\u90e8\u304b\u3089 […]<\/p>\n","protected":false},"author":1,"featured_media":42501,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-45601","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-column"],"views":70,"jetpack_featured_media_url":"\/wp-content\/uploads\/2025\/07\/f3403acf5c65aedec0dba821c4c26404.png","jetpack_sharing_enabled":true,"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/posts\/45601","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/comments?post=45601"}],"version-history":[{"count":0,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/posts\/45601\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/media\/42501"}],"wp:attachment":[{"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/media?parent=45601"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/categories?post=45601"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/tags?post=45601"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}