{"id":342,"date":"2023-02-17T06:23:12","date_gmt":"2023-05-02T05:09:50","guid":{"rendered":"https:\/\/www.silicloud.com\/zh\/blog\/index.php\/2023\/11\/30\/%e5%9c%a8python%e4%b8%ad%ef%bc%8c%e4%bd%bf%e7%94%a8numpy-append\/"},"modified":"2025-08-02T00:05:47","modified_gmt":"2025-08-01T16:05:47","slug":"%e5%9c%a8python%e4%b8%ad%ef%bc%8c%e4%bd%bf%e7%94%a8numpy-append","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/zh\/blog\/%e5%9c%a8python%e4%b8%ad%ef%bc%8c%e4%bd%bf%e7%94%a8numpy-append\/","title":{"rendered":"\u638c\u63e1Python numpy.append()\uff1a\u6570\u7ec4\u64cd\u4f5c\u6280\u5de7\u4e0e\u5b9e\u4f8b\u6559\u7a0b"},"content":{"rendered":"

\u8fd9\u662f\u6587\u7ae0\u300a\u5728Python\u4e2d\uff0c\u4f7f\u7528numpy.append()\u300b\u7684\u7b2c1\u90e8\u5206\uff08\u51711\u90e8\u5206\uff09\u3002<\/p>\n

\u5185\u5bb9\u7247\u6bb5: Python\u7684numpy\u5e93\u4e2d\u7684append()\u51fd\u6570\u7528\u4e8e\u5408\u5e76\u4e24\u4e2a\u6570\u7ec4\u3002\u8be5\u51fd\u6570\u4f1a\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684\u6570\u7ec4\uff0c\u539f\u59cb\u6570\u7ec4\u4e0d\u4f1a\u6539\u53d8\u3002<\/p>\n

NumPy append() \u8bed\u6cd5<\/h2>\n

\u51fd\u6570\u8bed\u6cd5\u5982\u4e0b\uff1a<\/p>\n

numpy.append(arr, values, axis=None)\r\n<\/code><\/pre>\n
    \n
  • arr\u53ef\u4ee5\u662f\u4e00\u4e2a\u7c7b\u6570\u7ec4\u5bf9\u8c61\u6216\u4e00\u4e2aNumPy\u6570\u7ec4\u3002values\u5c06\u88ab\u9644\u52a0\u5230\u8be5\u6570\u7ec4\u7684\u4e00\u4e2a\u526f\u672c\u4e0a\u3002<\/li>\n
  • values\u662f\u7c7b\u6570\u7ec4\u5bf9\u8c61\uff0c\u5b83\u88ab\u9644\u52a0\u5230”arr”\u5143\u7d20\u7684\u672b\u5c3e\u3002<\/li>\n
  • axis\u6307\u5b9a\u4e86values\u9644\u52a0\u7684\u8f74\u5411\u3002\u5982\u679c\u672a\u63d0\u4f9baxis\u53c2\u6570\uff0c\u4e24\u4e2a\u6570\u7ec4\u90fd\u5c06\u88ab\u5c55\u5e73\u3002<\/li>\n<\/ul>\n
    Python\u7684numpy.append()\u793a\u4f8b<\/h2>\n
    \u8ba9\u6211\u4eec\u6765\u770b\u4e00\u4e9bNumPy append() \u51fd\u6570\u7684\u793a\u4f8b\u3002<\/p>\n
    1. \u5c06\u4e24\u4e2a\u6570\u7ec4\u5c55\u5f00\u5408\u5e76<\/h3>\n
    import numpy as np\r\n\r\narr1 = np.array([[1, 2], [3, 4]])\r\narr2 = np.array([[10, 20], [30, 40]])\r\n\r\n# \u672a\u63d0\u4f9baxis\u53c2\u6570\uff0c\u6570\u7ec4\u5143\u7d20\u5c06\u88ab\u5c55\u5e73\r\narr_flat = np.append(arr1, arr2)\r\n\r\nprint(arr_flat)  # [ 1  2  3  4 10 20 30 40]\r\n<\/code><\/pre>\n
    2. \u6cbf\u8f74\u5411\u5408\u5e76<\/h3>\n
    import numpy as np\r\n\r\narr_merged = np.append([[1, 2], [3, 4]], [[10, 20], [30, 40]], axis=0)\r\nprint(f'\u6cbfAxis-0\u5408\u5e762x2\u6570\u7ec4:\\n{arr_merged}')\r\n\r\narr_merged = np.append([[1, 2], [3, 4]], [[10, 20], [30, 40]], axis=1)\r\nprint(f'\u6cbfAxis-1\u5408\u5e762x2\u6570\u7ec4:\\n{arr_merged}')\r\n<\/code><\/pre>\n
    \u8f93\u51fa\uff1a<\/p>\n
    \u6cbfAxis-0\u5408\u5e762x2\u6570\u7ec4:\r\n[[ 1  2]\r\n [ 3  4]\r\n [10 20]\r\n [30 40]]\r\n\u6cbfAxis-1\u5408\u5e762x2\u6570\u7ec4:\r\n[[ 1  2 10 20]\r\n [ 3  4 30 40]]\r\n<\/code><\/pre>\n
      \n
    • \u5f532×2\u6570\u7ec4\u6cbfx\u8f74\u5408\u5e76\u65f6\uff0c\u8f93\u51fa\u6570\u7ec4\u7684\u5927\u5c0f\u4e3a4×2\u3002<\/li>\n
    • \u5f532×2\u6570\u7ec4\u6cbfy\u8f74\u5408\u5e76\u65f6\uff0c\u8f93\u51fa\u6570\u7ec4\u7684\u5927\u5c0f\u4e3a2×4\u3002<\/li>\n<\/ul>\n
      3. \u5408\u5e76\u4e0d\u540c\u5f62\u72b6\u7684\u6570\u7ec4<\/h3>\n
      \u5982\u679c\u4e24\u4e2a\u6570\u7ec4\u7684\u5f62\u72b6\u4e0d\u540c\uff08\u8f74\u9664\u5916\uff09\uff0c\u90a3\u4e48append()\u51fd\u6570\u4f1a\u629b\u51faValueError\u3002\u8ba9\u6211\u4eec\u7528\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\u6765\u7406\u89e3\u8fd9\u79cd\u60c5\u51b5\u3002<\/p>\n
      arr3 = np.append([[1, 2]], [[1, 2, 3], [1, 2, 3]])\r\nprint(arr3)\r\n\r\narr3 = np.append([[1, 2]], [[1, 2], [3, 4]], axis=0)\r\nprint(arr3)\r\n<\/code><\/pre>\n
        \n
      • \u5728\u7b2c\u4e00\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6570\u7ec4\u5143\u7d20\u88ab\u5c55\u5e73\u3002\u6240\u4ee5\u5373\u4f7f\u5b83\u4eec\u6709\u5b8c\u5168\u4e0d\u540c\u7684\u5927\u5c0f – 1×2\u548c2×3\uff0cappend()\u51fd\u6570\u4e5f\u80fd\u6b63\u5e38\u5de5\u4f5c\u3002<\/li>\n
      • \u5728\u7b2c\u4e8c\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6570\u7ec4\u7684\u5f62\u72b6\u662f1×2\u548c2×2\u3002\u7531\u4e8e\u6211\u4eec\u662f\u6cbf0\u8f74\u9644\u52a0\uff0c0\u8f74\u7684\u5f62\u72b6\u53ef\u4ee5\u4e0d\u540c\u3002\u5176\u4ed6\u5f62\u72b6\u5e94\u8be5\u76f8\u540c\uff0c\u6240\u4ee5\u8fd9\u4e2aappend()\u4e5f\u80fd\u6b63\u5e38\u5de5\u4f5c\u3002<\/li>\n<\/ul>\n
        \u8f93\u51fa\uff1a<\/p>\n
        [1 2 1 2 3 1 2 3]\r\n\r\n[[1 2]\r\n [1 2]\r\n [3 4]]\r\n<\/code><\/pre>\n
        \u8ba9\u6211\u4eec\u770b\u770b\u53e6\u4e00\u4e2a\u53ef\u80fd\u5f15\u53d1 ValueError \u7684\u4f8b\u5b50\u3002<\/p>\n
        >>> import numpy as np\r\n>>> \r\n>>> arr3 = np.append([[1, 2]], [[1, 2, 3]], axis=0)\r\nTraceback (most recent call last):\r\n  File \"\", line 1, in \r\n  File \"\/Library\/Frameworks\/Python.framework\/Versions\/3.7\/lib\/python3.7\/site-packages\/numpy\/lib\/function_base.py\", line 4528, in append\r\n    return concatenate((arr, values), axis=axis)\r\nValueError: all the input array dimensions except for the concatenation axis must match exactly\r\n>>> \r\n<\/code><\/pre>\n
        \"Numpy<\/div>\n
        \u6570\u7ec4\u7684\u5f62\u72b6\u4e3a1×2\u548c2×3\u3002\u7531\u4e8e\u8f741\u7684\u5f62\u72b6\u4e0d\u540c\uff0c\u5f15\u53d1\u4e86ValueError\u9519\u8bef\u3002\u53c2\u8003\uff1aAPI\u6587\u6863\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
        \u8fd9\u662f\u6587\u7ae0\u300a\u5728Python\u4e2d\uff0c\u4f7f\u7528numpy.append()\u300b\u7684\u7b2c1\u90e8\u5206\uff08\u51711\u90e8\u5206\uff09\u3002 \u5185\u5bb9\u7247\u6bb5: Pytho […]<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[272,32,567,251,1146],"class_list":["post-342","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-numpy","tag-python","tag-567","tag-251","tag-1146"],"yoast_head":"\n\u638c\u63e1Python numpy.append()\uff1a\u6570\u7ec4\u64cd\u4f5c\u6280\u5de7\u4e0e\u5b9e\u4f8b\u6559\u7a0b - Blog - Silicon Cloud<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u8be6\u7ec6\u8bb2\u89e3Python\u4e2dnumpy.append()\u51fd\u6570\u7684\u4f7f\u7528\u65b9\u6cd5\uff0c\u5305\u62ec\u6570\u7ec4\u64cd\u4f5c\u6280\u5de7\u3001\u5b9e\u4f8b\u4ee3\u7801\u548c\u5e38\u89c1\u95ee\u9898\u89e3\u7b54\u3002\u638c\u63e1numpy.append()\u51fd\u6570\uff0c\u63d0\u5347\u6570\u636e\u5206\u6790\u6548\u7387\uff0c\u662fPython\u79d1\u5b66\u8ba1\u7b97\u7684\u5fc5\u5907\u6280\u80fd\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/zh\/blog\/\u5728python\u4e2d\uff0c\u4f7f\u7528numpy-append\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u638c\u63e1Python numpy.append()\uff1a\u6570\u7ec4\u64cd\u4f5c\u6280\u5de7\u4e0e\u5b9e\u4f8b\u6559\u7a0b\" \/>\n<meta property=\"og:description\" content=\"\u672c\u6559\u7a0b\u8be6\u7ec6\u8bb2\u89e3Python\u4e2dnumpy.append()\u51fd\u6570\u7684\u4f7f\u7528\u65b9\u6cd5\uff0c\u5305\u62ec\u6570\u7ec4\u64cd\u4f5c\u6280\u5de7\u3001\u5b9e\u4f8b\u4ee3\u7801\u548c\u5e38\u89c1\u95ee\u9898\u89e3\u7b54\u3002\u638c\u63e1numpy.append()\u51fd\u6570\uff0c\u63d0\u5347\u6570\u636e\u5206\u6790\u6548\u7387\uff0c\u662fPython\u79d1\u5b66\u8ba1\u7b97\u7684\u5fc5\u5907\u6280\u80fd\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/zh\/blog\/\u5728python\u4e2d\uff0c\u4f7f\u7528numpy-append\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - 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