{"id":47390,"date":"2025-07-30T07:36:52","date_gmt":"2025-07-29T23:36:52","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/47390.html"},"modified":"2025-07-30T07:36:52","modified_gmt":"2025-07-29T23:36:52","slug":"%e3%80%90pandas%e3%80%91pandas-index-objects-index-memory_usage","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/47390.html","title":{"rendered":"\u3010Pandas\u3011pandas Index objects Index.memory_usage"},"content":{"rendered":"

Pandas2.2 Index objects<\/h2>\n

Properties<\/h3>\n\n\u65b9\u6cd5\u63cf\u8ff0<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Index.values<\/td>\n\u8fd4\u56de Index \u5bf9\u8c61\u7684\u503c，\u901a\u5e38\u662f\u4e00\u4e2a NumPy \u6570\u7ec4<\/td>\n<\/tr>\n
Index.is_monotonic_increasing<\/td>\n\u7528\u4e8e\u68c0\u67e5\u7d22\u5f15\u7684\u5143\u7d20\u662f\u5426 \u5355\u8c03\u9012\u589e<\/td>\n<\/tr>\n
Index.is_monotonic_decreasing<\/td>\n\u7528\u4e8e\u5224\u65ad\u7d22\u5f15\u7684\u503c\u662f\u5426 \u5355\u8c03\u9012\u51cf<\/td>\n<\/tr>\n
Index.is_unique<\/td>\n\u7528\u4e8e\u68c0\u67e5\u7d22\u5f15\u4e2d\u7684\u6807\u7b7e\u662f\u5426 \u552f\u4e00<\/td>\n<\/tr>\n
Index.has_duplicates<\/td>\n\u7528\u4e8e\u68c0\u67e5\u7d22\u5f15\u662f\u5426\u5305\u542b\u91cd\u590d\u503c<\/td>\n<\/tr>\n
Index.hasnans<\/td>\n\u7528\u4e8e\u68c0\u67e5\u7d22\u5f15\u4e2d\u662f\u5426\u5305\u542b\u7f3a\u5931\u503c（NaN）<\/td>\n<\/tr>\n
Index.dtype<\/td>\n\u7528\u4e8e\u83b7\u53d6\u7d22\u5f15\u4e2d\u5143\u7d20\u7684\u6570\u636e\u7c7b\u578b（dtype）<\/td>\n<\/tr>\n
Index.inferred_type<\/td>\n\u7528\u4e8e\u63a8\u65ad\u7d22\u5f15\u4e2d\u6570\u636e\u7684\u7c7b\u578b<\/td>\n<\/tr>\n
Index.shape<\/td>\n\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u7684\u5f62\u72b6（\u5373\u7d22\u5f15\u4e2d\u5143\u7d20\u7684\u6570\u91cf）<\/td>\n<\/tr>\n
Index.name<\/td>\n\u7528\u4e8e\u83b7\u53d6\u6216\u8bbe\u7f6e\u7d22\u5f15\u7684\u540d\u79f0<\/td>\n<\/tr>\n
Index.names<\/td>\n\u7528\u4e8e\u83b7\u53d6\u6216\u8bbe\u7f6e**\u591a\u7ea7\u7d22\u5f15（MultiIndex）**\u4e2d\u6bcf\u4e00\u5c42\u7ea7\u7684\u540d\u79f0<\/td>\n<\/tr>\n
Index.nbytes<\/td>\n\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u5bf9\u8c61\u6240\u5360\u7528\u7684\u5185\u5b58\u5927\u5c0f（\u4ee5\u5b57\u8282\u4e3a\u5355\u4f4d）<\/td>\n<\/tr>\n
Index.ndim<\/td>\n\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u7684\u7ef4\u5ea6\u6570\u91cf<\/td>\n<\/tr>\n
Index.size<\/td>\n\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u4e2d\u5143\u7d20\u7684\u603b\u6570\u91cf<\/td>\n<\/tr>\n
Index.empty<\/td>\n\u7528\u4e8e\u68c0\u67e5\u7d22\u5f15\u662f\u5426\u4e3a\u7a7a<\/td>\n<\/tr>\n
Index.T<\/td>\n\u5b83\u662f [transpose]（\u8f6c\u7f6e）\u7684\u7b80\u5199<\/td>\n<\/tr>\n
Index.memory_usage([deep])<\/td>\n\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u5bf9\u8c61\u6240\u5360\u7528\u7684\u5185\u5b58\u5927\u5c0f（\u4ee5\u5b57\u8282\u4e3a\u5355\u4f4d）<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

pandas.Index.memory_usage()<\/h4>\n

pandas.Index.memory_usage([deep]) \u662f pandas.Index \u5bf9\u8c61\u7684\u4e00\u4e2a\u65b9\u6cd5，\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u5bf9\u8c61\u6240\u5360\u7528\u7684\u5185\u5b58\u5927\u5c0f（\u4ee5\u5b57\u8282\u4e3a\u5355\u4f4d）\u3002\u8fd9\u4e2a\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u5f00\u53d1\u8005\u4e86\u89e3\u7d22\u5f15\u5728\u5185\u5b58\u4e2d\u7684\u5360\u7528\u60c5\u51b5，\u5bf9\u4e8e\u6027\u80fd\u5206\u6790\u548c\u5185\u5b58\u4f18\u5316\u975e\u5e38\u6709\u7528\u3002<\/p>\n

\u8be6\u7ec6\u8bf4\u660e<\/h5>\n
    \n
  • \u7528\u9014：\u8ba1\u7b97\u5e76\u8fd4\u56de\u7d22\u5f15\u5bf9\u8c61\u6240\u5360\u7528\u7684\u5185\u5b58\u5927\u5c0f<\/li>\n
  • \u53c2\u6570：\n
      \n
    • deep（\u53ef\u9009，\u5e03\u5c14\u503c，\u9ed8\u8ba4\u4e3a False）：\n
        \n
      • \u5f53 deep=False \u65f6，\u53ea\u8ba1\u7b97\u7d22\u5f15\u5bf9\u8c61\u672c\u8eab\u7684\u5185\u5b58\u5360\u7528<\/li>\n
      • \u5f53 deep=True \u65f6，\u8fd8\u4f1a\u9012\u5f52\u8ba1\u7b97\u5bf9\u8c61\u5185\u90e8\u5143\u7d20\u7684\u5185\u5b58\u5360\u7528（\u5bf9\u4e8e\u5305\u542b\u5bf9\u8c61\u7684\u7d22\u5f15\u7279\u522b\u6709\u7528）<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n
      • \u8fd4\u56de\u503c：\u6574\u6570，\u8868\u793a\u7d22\u5f15\u5bf9\u8c61\u6240\u5360\u7528\u7684\u5b57\u8282\u6570<\/li>\n
      • \u9002\u7528\u573a\u666f：\n
          \n
        • \u5185\u5b58\u4f7f\u7528\u5206\u6790<\/li>\n
        • \u6027\u80fd\u4f18\u5316<\/li>\n
        • \u5927\u6570\u636e\u96c6\u5904\u7406\u65f6\u7684\u8d44\u6e90\u7ba1\u7406<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
          \u793a\u4f8b\u4ee3\u7801\u53ca\u7ed3\u679c<\/h5>\n
          \u793a\u4f8b 1: \u57fa\u672c\u7528\u6cd5 – \u6570\u503c\u7d22\u5f15<\/h6>\n

          import<\/span> pandas as<\/span> pd
          \nimport<\/span> numpy as<\/span> np<\/p>\n

          # \u521b\u5efa\u4e0d\u540c\u7c7b\u578b\u7684\u6570\u503c\u7d22\u5f15<\/span>
          \nint_index =<\/span> pd.<\/span>Index(<\/span>[<\/span>1<\/span>,<\/span> 2<\/span>,<\/span> 3<\/span>,<\/span> 4<\/span>,<\/span> 5<\/span>]<\/span>)<\/span>
          \nfloat_index =<\/span> pd.<\/span>Index(<\/span>[<\/span>1.1<\/span>,<\/span> 2.2<\/span>,<\/span> 3.3<\/span>,<\/span> 4.4<\/span>,<\/span> 5.5<\/span>]<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u6574\u6570\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> int_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u6574\u6570\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> int_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> float_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> float_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          \u8f93\u51fa\u7ed3\u679c：<\/p>\n

          \u6574\u6570\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 40
          \n\u6574\u6570\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 40
          \n\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 40
          \n\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 40<\/p>\n

          \u793a\u4f8b 2: \u5b57\u7b26\u4e32\u7d22\u5f15<\/h6>\n

          import<\/span> pandas as<\/span> pd<\/p>\n

          # \u521b\u5efa\u5b57\u7b26\u4e32\u7d22\u5f15<\/span>
          \nstring_index =<\/span> pd.<\/span>Index(<\/span>[<\/span>'apple'<\/span>,<\/span> 'banana'<\/span>,<\/span> 'cherry'<\/span>,<\/span> 'date'<\/span>]<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> string_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> string_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          # \u521b\u5efa\u5305\u542b\u8f83\u957f\u5b57\u7b26\u4e32\u7684\u7d22\u5f15<\/span>
          \nlong_string_index =<\/span> pd.<\/span>Index(<\/span>[<\/span>'this_is_a_very_long_string_example'<\/span>]<\/span> *<\/span> 4<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u957f\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> long_string_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u957f\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> long_string_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          \u8f93\u51fa\u7ed3\u679c：<\/p>\n

          \u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 32
          \n\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 196
          \n\u957f\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 32
          \n\u957f\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 140<\/p>\n

          \u793a\u4f8b 3: \u65f6\u95f4\u7d22\u5f15<\/h6>\n

          import<\/span> pandas as<\/span> pd<\/p>\n

          # \u521b\u5efa\u65f6\u95f4\u7d22\u5f15<\/span>
          \ndate_index =<\/span> pd.<\/span>date_range(<\/span>'2023-01-01'<\/span>,<\/span> periods=<\/span>100<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u65f6\u95f4\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> date_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u65f6\u95f4\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> date_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          \u8f93\u51fa\u7ed3\u679c：<\/p>\n

          \u65f6\u95f4\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 800
          \n\u65f6\u95f4\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 800<\/p>\n

          \u793a\u4f8b 4: \u5206\u7c7b\u7d22\u5f15<\/h6>\n

          import<\/span> pandas as<\/span> pd<\/p>\n

          # \u521b\u5efa\u5206\u7c7b\u7d22\u5f15<\/span>
          \ncategories =<\/span> [<\/span>'low'<\/span>,<\/span> 'medium'<\/span>,<\/span> 'high'<\/span>]<\/span>
          \nvalues =<\/span> [<\/span>'low'<\/span>,<\/span> 'medium'<\/span>,<\/span> 'high'<\/span>]<\/span> *<\/span> 10<\/span>
          \ncategorical_index =<\/span> pd.<\/span>CategoricalIndex(<\/span>values,<\/span> categories=<\/span>categories)<\/span><\/p>\n

          print<\/span>(<\/span>"\u5206\u7c7b\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> categorical_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u5206\u7c7b\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> categorical_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          # \u5bf9\u6bd4\u666e\u901a\u5bf9\u8c61\u7d22\u5f15<\/span>
          \nobject_index =<\/span> pd.<\/span>Index(<\/span>values)<\/span>
          \nprint<\/span>(<\/span>"\u5bf9\u8c61\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> object_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u5bf9\u8c61\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> object_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          \u8f93\u51fa\u7ed3\u679c：<\/p>\n

          \u5206\u7c7b\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 164
          \n\u5206\u7c7b\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 164
          \n\u5bf9\u8c61\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 240
          \n\u5bf9\u8c61\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 804<\/p>\n

          \u793a\u4f8b 5: \u591a\u7ea7\u7d22\u5f15<\/h6>\n

          import<\/span> pandas as<\/span> pd<\/p>\n

          # \u521b\u5efa\u591a\u7ea7\u7d22\u5f15<\/span>
          \narrays =<\/span> [<\/span>
          \n [<\/span>'A'<\/span>,<\/span> 'A'<\/span>,<\/span> 'B'<\/span>,<\/span> 'B'<\/span>,<\/span> 'C'<\/span>,<\/span> 'C'<\/span>]<\/span>,<\/span>
          \n [<\/span>1<\/span>,<\/span> 2<\/span>,<\/span> 1<\/span>,<\/span> 2<\/span>,<\/span> 1<\/span>,<\/span> 2<\/span>]<\/span>
          \n]<\/span>
          \nmulti_index =<\/span> pd.<\/span>MultiIndex.<\/span>from_arrays(<\/span>arrays,<\/span> names=<\/span>[<\/span>'letter'<\/span>,<\/span> 'number'<\/span>]<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u591a\u7ea7\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> multi_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u591a\u7ea7\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> multi_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          \u8f93\u51fa\u7ed3\u679c：<\/p>\n

          \u591a\u7ea7\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 96
          \n\u591a\u7ea7\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 240<\/p>\n

          \u793a\u4f8b 6: \u5305\u542b NaN \u503c\u7684\u7d22\u5f15<\/h6>\n

          import<\/span> pandas as<\/span> pd
          \nimport<\/span> numpy as<\/span> np<\/p>\n

          # \u521b\u5efa\u5305\u542b NaN \u7684\u6570\u503c\u7d22\u5f15<\/span>
          \nnan_float_index =<\/span> pd.<\/span>Index(<\/span>[<\/span>1.0<\/span>,<\/span> 2.0<\/span>,<\/span> np.<\/span>nan,<\/span> 4.0<\/span>,<\/span> 5.0<\/span>]<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u5305\u542b NaN \u7684\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> nan_float_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u5305\u542b NaN \u7684\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> nan_float_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          # \u521b\u5efa\u5305\u542b NaN \u7684\u5b57\u7b26\u4e32\u7d22\u5f15<\/span>
          \nnan_string_index =<\/span> pd.<\/span>Index(<\/span>[<\/span>'a'<\/span>,<\/span> 'b'<\/span>,<\/span> np.<\/span>nan,<\/span> 'd'<\/span>,<\/span> 'e'<\/span>]<\/span>)<\/span><\/p>\n

          print<\/span>(<\/span>"\u5305\u542b NaN \u7684\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）:"<\/span>,<\/span> nan_string_index.<\/span>memory_usage(<\/span>)<\/span>)<\/span>
          \nprint<\/span>(<\/span>"\u5305\u542b NaN \u7684\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）:"<\/span>,<\/span> nan_string_index.<\/span>memory_usage(<\/span>deep=<\/span>True<\/span>)<\/span>)<\/span><\/p>\n

          \u8f93\u51fa\u7ed3\u679c：<\/p>\n

          \u5305\u542b NaN \u7684\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 40
          \n\u5305\u542b NaN \u7684\u6d6e\u70b9\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 40
          \n\u5305\u542b NaN \u7684\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（\u9ed8\u8ba4）: 40
          \n\u5305\u542b NaN \u7684\u5b57\u7b26\u4e32\u7d22\u5f15\u5185\u5b58\u5360\u7528（deep=True）: 148<\/p>\n

          \u5e94\u7528\u573a\u666f<\/h5>\n
        • \u5185\u5b58\u4f18\u5316：\u6bd4\u8f83\u4e0d\u540c\u6570\u636e\u7c7b\u578b\u7d22\u5f15\u7684\u5185\u5b58\u5360\u7528，\u9009\u62e9\u6700\u4f18\u7684\u6570\u636e\u7ed3\u6784<\/li>\n
        • \u5927\u6570\u636e\u5904\u7406：\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\u76d1\u63a7\u5185\u5b58\u4f7f\u7528\u60c5\u51b5<\/li>\n
        • \u6027\u80fd\u8c03\u4f18：\u8bc6\u522b\u5185\u5b58\u5360\u7528\u8f83\u5927\u7684\u7d22\u5f15，\u8003\u8651\u4f7f\u7528\u66f4\u9ad8\u6548\u7684\u66ff\u4ee3\u65b9\u6848（\u5982\u5206\u7c7b\u7d22\u5f15）<\/li>\n
        • \u8d44\u6e90\u7ba1\u7406：\u5728\u8d44\u6e90\u53d7\u9650\u7684\u73af\u5883\u4e2d\u5408\u7406\u5206\u914d\u5185\u5b58<\/li>\n
          \u6ce8\u610f\u4e8b\u9879<\/h5>\n
            \n
          • \u5bf9\u4e8e\u6570\u503c\u7c7b\u578b\u7d22\u5f15（\u5982 int64\u3001float64），deep \u53c2\u6570\u901a\u5e38\u6ca1\u6709\u533a\u522b，\u56e0\u4e3a\u8fd9\u4e9b\u7c7b\u578b\u7684\u5185\u5b58\u5360\u7528\u662f\u56fa\u5b9a\u7684<\/li>\n
          • \u5bf9\u4e8e\u5bf9\u8c61\u7c7b\u578b\u7d22\u5f15（\u5982\u5b57\u7b26\u4e32\u7d22\u5f15），deep=True \u4f1a\u8ba1\u7b97\u5b9e\u9645\u5b57\u7b26\u4e32\u5185\u5bb9\u7684\u5185\u5b58\u5360\u7528，\u800c deep=False \u53ea\u8ba1\u7b97\u5f15\u7528\u7684\u5185\u5b58\u5360\u7528<\/li>\n
          • \u5206\u7c7b\u7d22\u5f15\u901a\u5e38\u6bd4\u5bf9\u5e94\u7684\u5bf9\u8c61\u7d22\u5f15\u5360\u7528\u66f4\u5c11\u7684\u5185\u5b58，\u7279\u522b\u662f\u5728\u6709\u91cd\u590d\u503c\u7684\u60c5\u51b5\u4e0b<\/li>\n
          • \u5728\u5904\u7406\u5927\u578b\u7d22\u5f15\u65f6，memory_usage(deep=True) \u53ef\u80fd\u9700\u8981\u66f4\u591a\u8ba1\u7b97\u65f6\u95f4<\/li>\n<\/ul>\n
            \u4e0e\u5176\u4ed6\u5c5e\u6027\u7684\u5bf9\u6bd4<\/h5>\n\n\u5c5e\u6027\/\u65b9\u6cd5\u7528\u9014\u662f\u5426\u8003\u8651\u6df1\u5c42\u5185\u5b58\u9002\u7528\u573a\u666f<\/tr>\n\n\n\n\n
            [nbytes]<\/td>\n\u7d22\u5f15\u5bf9\u8c61\u672c\u8eab\u7684\u5b57\u8282\u5927\u5c0f<\/td>\n\u5426<\/td>\n\u5feb\u901f\u67e5\u770b\u57fa\u672c\u5185\u5b58\u5360\u7528<\/td>\n<\/tr>\n
            memory_usage()<\/td>\n\u7d22\u5f15\u5bf9\u8c61\u7684\u5185\u5b58\u5360\u7528<\/td>\n\u5426（\u9ed8\u8ba4）<\/td>\n\u4e00\u822c\u5185\u5b58\u5206\u6790<\/td>\n<\/tr>\n
            memory_usage(deep=True)<\/td>\n\u7d22\u5f15\u53ca\u5176\u5143\u7d20\u7684\u603b\u5185\u5b58\u5360\u7528<\/td>\n\u662f<\/td>\n\u7cbe\u786e\u5185\u5b58\u5206\u6790<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

            \u901a\u8fc7 memory_usage() \u65b9\u6cd5，\u5f00\u53d1\u8005\u53ef\u4ee5\u66f4\u597d\u5730\u7406\u89e3\u548c\u4f18\u5316 pandas \u7d22\u5f15\u7684\u5185\u5b58\u4f7f\u7528\u60c5\u51b5，\u8fd9\u5bf9\u4e8e\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u5c24\u4e3a\u91cd\u8981\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

            \u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb513\u6b21\uff0c\u70b9\u8d5e16\u6b21\uff0c\u6536\u85cf6\u6b21\u3002`pandas.Index.memory_usage([deep])` \u662f `pandas.Index` \u5bf9\u8c61\u7684\u4e00\u4e2a\u65b9\u6cd5\uff0c\u7528\u4e8e\u8fd4\u56de\u7d22\u5f15\u5bf9\u8c61\u6240\u5360\u7528\u7684\u5185\u5b58\u5927\u5c0f\uff08\u4ee5\u5b57\u8282\u4e3a\u5355\u4f4d\uff09\u3002\u8fd9\u4e2a\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u5f00\u53d1\u8005\u4e86\u89e3\u7d22\u5f15\u5728\u5185\u5b58\u4e2d\u7684\u5360\u7528\u60c5\u51b5\uff0c\u5bf9\u4e8e\u6027\u80fd\u5206\u6790\u548c\u5185\u5b58\u4f18\u5316\u975e\u5e38\u6709\u7528\u3002<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[4278,4535],"topic":[],"class_list":["post-47390","post","type-post","status-publish","format-standard","hentry","category-server","tag-pandas","tag-pandas-index-objects"],"yoast_head":"\n\u3010Pandas\u3011pandas Index objects Index.memory_usage - 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