{"id":45485,"date":"2025-08-14T14:02:09","date_gmt":"2025-08-14T05:02:09","guid":{"rendered":"https:\/\/techgym.jp\/?p=45485"},"modified":"2025-08-14T14:02:11","modified_gmt":"2025-08-14T05:02:11","slug":"numpy-insert","status":"publish","type":"post","link":"https:\/\/techgym.jp\/column\/numpy-insert\/","title":{"rendered":"NumPy insert\u95a2\u6570\u5b8c\u5168\u30ac\u30a4\u30c9\uff5c\u914d\u5217ndarray\u306b\u8981\u7d20\u30fb\u884c\u30fb\u5217\u3092\u633f\u5165\u3059\u308b\u4f7f\u3044\u65b9\u3068\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9"},"content":{"rendered":"\n<p>\u00a0<\/p>\n<p>NumPy\u306e<code>insert<\/code>\u95a2\u6570\u306f\u3001\u914d\u5217\uff08ndarray\uff09\u306b\u65b0\u3057\u3044\u8981\u7d20\u3001\u884c\u3001\u5217\u3092\u633f\u5165\u3059\u308b\u305f\u3081\u306e\u5f37\u529b\u306a\u30c4\u30fc\u30eb\u3067\u3059\u3002\u672c\u8a18\u4e8b\u3067\u306f\u3001<code>numpy.insert()<\/code>\u306e\u57fa\u672c\u7684\u306a\u4f7f\u3044\u65b9\u304b\u3089\u5fdc\u7528\u4f8b\u307e\u3067\u3001\u5b9f\u8df5\u7684\u306a\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u3068\u3068\u3082\u306b\u8a73\u3057\u304f\u89e3\u8aac\u3057\u307e\u3059\u3002<\/p>\n<h2>numpy.insert()\u3068\u306f<\/h2>\n<p><code>numpy.insert()<\/code>\u306f\u3001\u6307\u5b9a\u3057\u305f\u4f4d\u7f6e\u306bNumPy\u914d\u5217\u306e\u8981\u7d20\u3092\u633f\u5165\u3059\u308b\u95a2\u6570\u3067\u3059\u3002\u5143\u306e\u914d\u5217\u3092\u5909\u66f4\u3059\u308b\u3053\u3068\u306a\u304f\u3001\u65b0\u3057\u3044\u914d\u5217\u3092\u8fd4\u3057\u307e\u3059\u3002<\/p>\n<p><strong>\u57fa\u672c\u69cb\u6587\uff1a<\/strong><\/p>\n<pre><code class=\"language-python\">numpy.insert(arr, obj, values, axis=None)\n<\/code><\/pre>\n<p><strong>\u30d1\u30e9\u30e1\u30fc\u30bf\uff1a<\/strong><\/p>\n<ul>\n<li><code>arr<\/code>: \u633f\u5165\u5bfe\u8c61\u306e\u914d\u5217<\/li>\n<li><code>obj<\/code>: \u633f\u5165\u4f4d\u7f6e\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9<\/li>\n<li><code>values<\/code>: \u633f\u5165\u3059\u308b\u5024<\/li>\n<li><code>axis<\/code>: \u633f\u5165\u3059\u308b\u8ef8\uff08None, 0, 1\u306a\u3069\uff09<\/li>\n<\/ul>\n<h2>1\u6b21\u5143\u914d\u5217\u3078\u306e\u8981\u7d20\u633f\u5165<\/h2>\n<h3>\u57fa\u672c\u7684\u306a\u8981\u7d20\u633f\u5165<\/h3>\n<pre><code class=\"language-python\">import numpy as np\n\n# 1\u6b21\u5143\u914d\u5217\u306e\u4f5c\u6210\narr = np.array([1, 2, 3, 4, 5])\nprint(\"\u5143\u306e\u914d\u5217:\", arr)\n\n# \u30a4\u30f3\u30c7\u30c3\u30af\u30b92\u306e\u4f4d\u7f6e\u306b10\u3092\u633f\u5165\nresult = np.insert(arr, 2, 10)\nprint(\"\u633f\u5165\u5f8c:\", result)\n# \u51fa\u529b: [1 2 10 3 4 5]\n<\/code><\/pre>\n<h3>\u8907\u6570\u306e\u8981\u7d20\u3092\u540c\u6642\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># \u8907\u6570\u306e\u5024\u3092\u633f\u5165\narr = np.array([1, 2, 3, 4, 5])\nresult = np.insert(arr, 2, [10, 20])\nprint(\"\u8907\u6570\u633f\u5165:\", result)\n# \u51fa\u529b: [1 2 10 20 3 4 5]\n<\/code><\/pre>\n<h3>\u914d\u5217\u306e\u5148\u982d\u3068\u672b\u5c3e\u3078\u306e\u633f\u5165<\/h3>\n<pre><code class=\"language-python\">arr = np.array([2, 3, 4])\n\n# \u5148\u982d\u306b\u633f\u5165\nfront = np.insert(arr, 0, 1)\nprint(\"\u5148\u982d\u633f\u5165:\", front)\n# \u51fa\u529b: [1 2 3 4]\n\n# \u672b\u5c3e\u306b\u633f\u5165\nback = np.insert(arr, len(arr), 5)\nprint(\"\u672b\u5c3e\u633f\u5165:\", back)\n# \u51fa\u529b: [2 3 4 5]\n<\/code><\/pre>\n<h2>2\u6b21\u5143\u914d\u5217\u3078\u306e\u884c\u633f\u5165\uff08axis=0\uff09<\/h2>\n<h3>\u65b0\u3057\u3044\u884c\u306e\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># 2\u6b21\u5143\u914d\u5217\u306e\u4f5c\u6210\narr_2d = np.array([[1, 2, 3],\n                   [4, 5, 6]])\nprint(\"\u5143\u306e\u914d\u5217:\")\nprint(arr_2d)\n\n# 1\u884c\u76ee\u306b\u65b0\u3057\u3044\u884c\u3092\u633f\u5165\nnew_row = np.array([7, 8, 9])\nresult = np.insert(arr_2d, 1, new_row, axis=0)\nprint(\"\u884c\u633f\u5165\u5f8c:\")\nprint(result)\n# \u51fa\u529b:\n# [[1 2 3]\n#  [7 8 9]\n#  [4 5 6]]\n<\/code><\/pre>\n<h3>\u8907\u6570\u884c\u306e\u540c\u6642\u633f\u5165<\/h3>\n<pre><code class=\"language-python\">arr_2d = np.array([[1, 2],\n                   [3, 4]])\n\n# \u8907\u6570\u884c\u3092\u633f\u5165\nnew_rows = np.array([[5, 6], [7, 8]])\nresult = np.insert(arr_2d, 1, new_rows, axis=0)\nprint(\"\u8907\u6570\u884c\u633f\u5165:\")\nprint(result)\n# \u51fa\u529b:\n# [[1 2]\n#  [5 6]\n#  [7 8]\n#  [3 4]]\n<\/code><\/pre>\n<h3>\u5148\u982d\u3068\u672b\u5c3e\u3078\u306e\u884c\u633f\u5165<\/h3>\n<pre><code class=\"language-python\">arr_2d = np.array([[2, 3],\n                   [4, 5]])\n\n# \u5148\u982d\u306b\u884c\u633f\u5165\nfirst_row = np.insert(arr_2d, 0, [1, 1], axis=0)\nprint(\"\u5148\u982d\u884c\u633f\u5165:\")\nprint(first_row)\n\n# \u672b\u5c3e\u306b\u884c\u633f\u5165\nlast_row = np.insert(arr_2d, arr_2d.shape[0], [6, 7], axis=0)\nprint(\"\u672b\u5c3e\u884c\u633f\u5165:\")\nprint(last_row)\n<\/code><\/pre>\n<h2>2\u6b21\u5143\u914d\u5217\u3078\u306e\u5217\u633f\u5165\uff08axis=1\uff09<\/h2>\n<h3>\u65b0\u3057\u3044\u5217\u306e\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># 2\u6b21\u5143\u914d\u5217\u306e\u4f5c\u6210\narr_2d = np.array([[1, 2, 4],\n                   [5, 6, 8]])\nprint(\"\u5143\u306e\u914d\u5217:\")\nprint(arr_2d)\n\n# 2\u5217\u76ee\u306b\u65b0\u3057\u3044\u5217\u3092\u633f\u5165\nnew_col = np.array([3, 7])\nresult = np.insert(arr_2d, 2, new_col, axis=1)\nprint(\"\u5217\u633f\u5165\u5f8c:\")\nprint(result)\n# \u51fa\u529b:\n# [[1 2 3 4]\n#  [5 6 7 8]]\n<\/code><\/pre>\n<h3>\u8907\u6570\u5217\u306e\u540c\u6642\u633f\u5165<\/h3>\n<pre><code class=\"language-python\">arr_2d = np.array([[1, 4],\n                   [5, 8]])\n\n# \u8907\u6570\u5217\u3092\u633f\u5165\nnew_cols = np.array([[2, 3], [6, 7]])\nresult = np.insert(arr_2d, 1, new_cols, axis=1)\nprint(\"\u8907\u6570\u5217\u633f\u5165:\")\nprint(result)\n# \u51fa\u529b:\n# [[1 2 3 4]\n#  [5 6 7 8]]\n<\/code><\/pre>\n<h3>\u5217\u306e\u5148\u982d\u3068\u672b\u5c3e\u3078\u306e\u633f\u5165<\/h3>\n<pre><code class=\"language-python\">arr_2d = np.array([[2, 3],\n                   [5, 6]])\n\n# \u5148\u982d\u306b\u5217\u633f\u5165\nfirst_col = np.insert(arr_2d, 0, [1, 4], axis=1)\nprint(\"\u5148\u982d\u5217\u633f\u5165:\")\nprint(first_col)\n\n# \u672b\u5c3e\u306b\u5217\u633f\u5165\nlast_col = np.insert(arr_2d, arr_2d.shape[1], [4, 7], axis=1)\nprint(\"\u672b\u5c3e\u5217\u633f\u5165:\")\nprint(last_col)\n<\/code><\/pre>\n<h2>axis=None\u306e\u52d5\u4f5c\uff081\u6b21\u5143\u5316\uff09<\/h2>\n<pre><code class=\"language-python\"># 2\u6b21\u5143\u914d\u5217\u3092axis=None\u30671\u6b21\u5143\u5316\u3057\u3066\u633f\u5165\narr_2d = np.array([[1, 2],\n                   [3, 4]])\n\nresult = np.insert(arr_2d, 2, 99, axis=None)\nprint(\"axis=None:\", result)\n# \u51fa\u529b: [1 2 99 3 4]\n<\/code><\/pre>\n<h2>\u9ad8\u6b21\u5143\u914d\u5217\u3067\u306e\u5fdc\u7528<\/h2>\n<h3>3\u6b21\u5143\u914d\u5217\u3078\u306e\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># 3\u6b21\u5143\u914d\u5217\u306e\u4f5c\u6210\narr_3d = np.array([[[1, 2], [3, 4]],\n                   [[5, 6], [7, 8]]])\nprint(\"3\u6b21\u5143\u914d\u5217\u306e\u5f62\u72b6:\", arr_3d.shape)\n\n# axis=0\u3067\u633f\u5165\nnew_layer = np.array([[9, 10], [11, 12]])\nresult = np.insert(arr_3d, 1, new_layer, axis=0)\nprint(\"\u633f\u5165\u5f8c\u306e\u5f62\u72b6:\", result.shape)\nprint(\"\u633f\u5165\u7d50\u679c:\")\nprint(result)\n<\/code><\/pre>\n<h2>\u30c7\u30fc\u30bf\u578b\u3092\u8003\u616e\u3057\u305f\u633f\u5165<\/h2>\n<h3>\u6574\u6570\u914d\u5217\u3078\u306e\u6d6e\u52d5\u5c0f\u6570\u70b9\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># \u6574\u6570\u914d\u5217\nint_arr = np.array([1, 2, 3], dtype=int)\nprint(\"\u5143\u306e\u578b:\", int_arr.dtype)\n\n# \u6d6e\u52d5\u5c0f\u6570\u70b9\u3092\u633f\u5165\nresult = np.insert(int_arr, 1, 2.5)\nprint(\"\u633f\u5165\u5f8c:\", result)\nprint(\"\u633f\u5165\u5f8c\u306e\u578b:\", result.dtype)\n# \u51fa\u529b: [1 2 3] (2.5\u306f2\u306b\u5909\u63db\u3055\u308c\u308b)\n<\/code><\/pre>\n<h3>\u578b\u5909\u63db\u3092\u4f34\u3046\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># \u660e\u793a\u7684\u306a\u578b\u6307\u5b9a\nfloat_arr = np.array([1.1, 2.2, 3.3])\nresult = np.insert(float_arr, 1, 10)\nprint(\"\u6d6e\u52d5\u5c0f\u6570\u70b9\u914d\u5217:\", result)\nprint(\"\u578b:\", result.dtype)\n<\/code><\/pre>\n<h2>\u5b9f\u8df5\u7684\u306a\u5fdc\u7528\u4f8b<\/h2>\n<h3>\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u98a8\u306e\u64cd\u4f5c<\/h3>\n<pre><code class=\"language-python\"># \u5b66\u751f\u306e\u6210\u7e3e\u30c7\u30fc\u30bf\nscores = np.array([[85, 92, 78],\n                   [91, 88, 85],\n                   [79, 94, 90]])\n\n# \u65b0\u3057\u3044\u5b66\u751f\u306e\u6210\u7e3e\u3092\u8ffd\u52a0\nnew_student = np.array([88, 89, 92])\nupdated_scores = np.insert(scores, 1, new_student, axis=0)\nprint(\"\u66f4\u65b0\u3055\u308c\u305f\u6210\u7e3e:\")\nprint(updated_scores)\n\n# \u65b0\u3057\u3044\u79d1\u76ee\u306e\u6210\u7e3e\u3092\u8ffd\u52a0\nnew_subject = np.array([90, 87, 89, 91])\nfinal_scores = np.insert(updated_scores, 3, new_subject, axis=1)\nprint(\"\u79d1\u76ee\u8ffd\u52a0\u5f8c:\")\nprint(final_scores)\n<\/code><\/pre>\n<h3>\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u633f\u5165<\/h3>\n<pre><code class=\"language-python\"># \u6642\u7cfb\u5217\u30c7\u30fc\u30bf\ntime_data = np.array([10, 15, 20, 30])\n\n# \u6b20\u640d\u5024\u3092\u88dc\u9593\u3059\u308b\u3088\u3046\u306b\u633f\u5165\ninterpolated = np.insert(time_data, 2, 17.5)\nprint(\"\u88dc\u9593\u5f8c:\", interpolated)\n# \u51fa\u529b: [10.  15.  17.5 20.  30. ]\n<\/code><\/pre>\n<h2>\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u306e\u8003\u616e\u4e8b\u9805<\/h2>\n<h3>\u5927\u304d\u306a\u914d\u5217\u3067\u306e\u6ce8\u610f\u70b9<\/h3>\n<pre><code class=\"language-python\">import time\n\n# \u5927\u304d\u306a\u914d\u5217\u3067\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u30c6\u30b9\u30c8\nlarge_arr = np.random.rand(10000)\n\n# \u633f\u5165\u51e6\u7406\u306e\u6642\u9593\u6e2c\u5b9a\nstart = time.time()\nresult = np.insert(large_arr, 5000, 999)\nend = time.time()\n\nprint(f\"\u633f\u5165\u51e6\u7406\u6642\u9593: {end - start:.6f}\u79d2\")\nprint(f\"\u5143\u306e\u914d\u5217\u30b5\u30a4\u30ba: {large_arr.size}\")\nprint(f\"\u633f\u5165\u5f8c\u30b5\u30a4\u30ba: {result.size}\")\n<\/code><\/pre>\n<h3>\u30e1\u30e2\u30ea\u52b9\u7387\u7684\u306a\u4ee3\u66ff\u624b\u6bb5<\/h3>\n<pre><code class=\"language-python\"># append\u3068\u306e\u6bd4\u8f03\narr = np.array([1, 2, 3])\n\n# insert\u4f7f\u7528\ninsert_result = np.insert(arr, len(arr), 4)\n\n# append\u4f7f\u7528\uff08\u672b\u5c3e\u8ffd\u52a0\u306e\u5834\u5408\uff09\nappend_result = np.append(arr, 4)\n\nprint(\"insert\u7d50\u679c:\", insert_result)\nprint(\"append\u7d50\u679c:\", append_result)\n# \u4e21\u65b9\u3068\u3082\u540c\u3058\u7d50\u679c: [1 2 3 4]\n<\/code><\/pre>\n<h2>\u30a8\u30e9\u30fc\u30cf\u30f3\u30c9\u30ea\u30f3\u30b0<\/h2>\n<h3>\u3088\u304f\u3042\u308b\u30a8\u30e9\u30fc\u3068\u5bfe\u51e6\u6cd5<\/h3>\n<pre><code class=\"language-python\"># \u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u30a8\u30e9\u30fc\ntry:\n    arr = np.array([1, 2, 3])\n    # \u7bc4\u56f2\u5916\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\uff08\u30a8\u30e9\u30fc\u306b\u306a\u3089\u306a\u3044\uff09\n    result = np.insert(arr, 10, 999)\n    print(\"\u7bc4\u56f2\u5916\u633f\u5165:\", result)\nexcept Exception as e:\n    print(\"\u30a8\u30e9\u30fc:\", e)\n\n# \u6b21\u5143\u4e0d\u4e00\u81f4\u30a8\u30e9\u30fc\ntry:\n    arr_2d = np.array([[1, 2], [3, 4]])\n    # \u4e0d\u9069\u5207\u306a\u5f62\u72b6\u3067\u306e\u633f\u5165\n    wrong_shape = np.insert(arr_2d, 1, [1, 2, 3], axis=0)\nexcept ValueError as e:\n    print(\"\u5f62\u72b6\u30a8\u30e9\u30fc:\", e)\n<\/code><\/pre>\n<h3>\u5b89\u5168\u306a\u633f\u5165\u51e6\u7406<\/h3>\n<pre><code class=\"language-python\">def safe_insert(arr, index, values, axis=None):\n    \"\"\"\u5b89\u5168\u306a\u633f\u5165\u51e6\u7406\"\"\"\n    try:\n        # \u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u306e\u7bc4\u56f2\u30c1\u30a7\u30c3\u30af\n        if axis is None:\n            max_index = arr.size\n        else:\n            max_index = arr.shape[axis]\n        \n        if index &lt; 0 or index &gt; max_index:\n            print(f\"\u8b66\u544a: \u30a4\u30f3\u30c7\u30c3\u30af\u30b9 {index} \u306f\u7bc4\u56f2\u5916\u3067\u3059\")\n            index = max(0, min(index, max_index))\n        \n        return np.insert(arr, index, values, axis=axis)\n    \n    except Exception as e:\n        print(f\"\u633f\u5165\u30a8\u30e9\u30fc: {e}\")\n        return arr\n\n# \u4f7f\u7528\u4f8b\narr = np.array([1, 2, 3])\nresult = safe_insert(arr, 10, 999)\nprint(\"\u5b89\u5168\u306a\u633f\u5165:\", result)\n<\/code><\/pre>\n<h2>\u307e\u3068\u3081<\/h2>\n<p><code>numpy.insert()<\/code>\u306f\u914d\u5217\u64cd\u4f5c\u306b\u304a\u3044\u3066\u975e\u5e38\u306b\u6709\u7528\u306a\u95a2\u6570\u3067\u3059\u3002\u91cd\u8981\u306a\u30dd\u30a4\u30f3\u30c8\u3092\u6574\u7406\u3059\u308b\u3068\uff1a<\/p>\n<p><strong>\u57fa\u672c\u7684\u306a\u4f7f\u3044\u65b9\uff1a<\/strong><\/p>\n<ul>\n<li>1\u6b21\u5143\u914d\u5217\uff1a<code>np.insert(arr, index, value)<\/code><\/li>\n<li>\u884c\u633f\u5165\uff1a<code>np.insert(arr, index, values, axis=0)<\/code><\/li>\n<li>\u5217\u633f\u5165\uff1a<code>np.insert(arr, index, values, axis=1)<\/code><\/li>\n<\/ul>\n<p><strong>\u6ce8\u610f\u70b9\uff1a<\/strong><\/p>\n<ul>\n<li>\u5143\u306e\u914d\u5217\u306f\u5909\u66f4\u3055\u308c\u305a\u3001\u65b0\u3057\u3044\u914d\u5217\u304c\u8fd4\u3055\u308c\u308b<\/li>\n<li>\u30c7\u30fc\u30bf\u578b\u306e\u5909\u63db\u304c\u81ea\u52d5\u3067\u884c\u308f\u308c\u308b\u5834\u5408\u304c\u3042\u308b<\/li>\n<li>\u5927\u304d\u306a\u914d\u5217\u3067\u306f\u51e6\u7406\u6642\u9593\u306b\u6ce8\u610f\u304c\u5fc5\u8981<\/li>\n<\/ul>\n<p><strong>\u5fdc\u7528\u306e\u30b3\u30c4\uff1a<\/strong><\/p>\n<ul>\n<li>\u8907\u6570\u306e\u5024\u3084\u884c\u30fb\u5217\u3092\u540c\u6642\u633f\u5165\u53ef\u80fd<\/li>\n<li>3\u6b21\u5143\u4ee5\u4e0a\u306e\u914d\u5217\u3067\u3082\u540c\u69d8\u306b\u4f7f\u7528\u53ef\u80fd<\/li>\n<li>\u30a8\u30e9\u30fc\u30cf\u30f3\u30c9\u30ea\u30f3\u30b0\u3092\u9069\u5207\u306b\u884c\u3046<\/li>\n<\/ul>\n<p>NumPy\u306e<code>insert<\/code>\u95a2\u6570\u3092\u52b9\u679c\u7684\u306b\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u914d\u5217\u64cd\u4f5c\u304c\u3088\u308a\u67d4\u8edf\u304b\u3064\u52b9\u7387\u7684\u306b\u306a\u308a\u307e\u3059\u3002\u30c7\u30fc\u30bf\u5206\u6790\u3084\u79d1\u5b66\u8a08\u7b97\u306b\u304a\u3044\u3066\u3001\u914d\u5217\u306e\u52d5\u7684\u306a\u5909\u66f4\u304c\u5fc5\u8981\u306a\u5834\u9762\u3067\u7a4d\u6975\u7684\u306b\u6d3b\u7528\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u00a0 NumPy\u306einsert\u95a2\u6570\u306f\u3001\u914d\u5217\uff08ndarray\uff09\u306b\u65b0\u3057\u3044\u8981\u7d20\u3001\u884c\u3001\u5217\u3092\u633f\u5165\u3059\u308b\u305f\u3081\u306e\u5f37\u529b\u306a\u30c4\u30fc\u30eb\u3067\u3059\u3002\u672c\u8a18\u4e8b\u3067\u306f\u3001numpy.insert()\u306e\u57fa\u672c\u7684\u306a\u4f7f\u3044\u65b9\u304b\u3089\u5fdc\u7528\u4f8b\u307e\u3067\u3001\u5b9f\u8df5\u7684\u306a\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u3068\u3068\u3082\u306b\u8a73\u3057\u304f [&hellip;]<\/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-45485","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-column"],"views":33,"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\/45485","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=45485"}],"version-history":[{"count":0,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/posts\/45485\/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=45485"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/categories?post=45485"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techgym.jp\/wp-json\/wp\/v2\/tags?post=45485"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}