{"id":1114406,"date":"2025-01-08T17:56:52","date_gmt":"2025-01-08T09:56:52","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1114406.html"},"modified":"2025-01-08T17:56:54","modified_gmt":"2025-01-08T09:56:54","slug":"python%e4%b8%ad%e6%97%b6%e5%ba%8f%e6%95%b0%e6%8d%ae%e5%a6%82%e4%bd%95%e5%81%9a%e5%b7%ae%e5%80%bc-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1114406.html","title":{"rendered":"python\u4e2d\u65f6\u5e8f\u6570\u636e\u5982\u4f55\u505a\u5dee\u503c"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25075606\/9dd4f0a8-c3d8-468f-a6ac-d58d39423b8e.webp\" alt=\"python\u4e2d\u65f6\u5e8f\u6570\u636e\u5982\u4f55\u505a\u5dee\u503c\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\u8fdb\u884c\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u503c\u8ba1\u7b97\uff0c\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528Pandas\u5e93\u4e2d\u7684diff()\u51fd\u6570\u3001shift()\u51fd\u6570\u3001\u4ee5\u53ca\u81ea\u5b9a\u4e49\u51fd\u6570\u6765\u5b9e\u73b0\u3002<\/strong>\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u4f60\u5206\u6790\u65f6\u5e8f\u6570\u636e\u7684\u53d8\u5316\u8d8b\u52bf\u3001\u8bc6\u522b\u5f02\u5e38\u70b9\u3001\u4ee5\u53ca\u8fdb\u884c\u540e\u7eed\u7684\u6570\u636e\u5904\u7406\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\u53ca\u5176\u5e94\u7528\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528Pandas\u5e93\u4e2d\u7684diff()\u51fd\u6570<\/h3>\n<\/p>\n<p><p>Pandas\u5e93\u4e2d\u7684diff()\u51fd\u6570\u662f\u8ba1\u7b97\u5e8f\u5217\u7684\u5dee\u5206\u7684\u4e00\u4e2a\u7b80\u5355\u800c\u6709\u6548\u7684\u65b9\u6cd5\u3002\u5b83\u901a\u8fc7\u8ba1\u7b97\u5f53\u524d\u503c\u4e0e\u524d\u4e00\u4e2a\u503c\u4e4b\u95f4\u7684\u5dee\u6765\u5b9e\u73b0\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u5206\u3002\u8fd9\u5bf9\u4e8e\u8fdb\u884c\u57fa\u672c\u7684\u65f6\u5e8f\u5206\u6790\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u7684\u65f6\u95f4\u5e8f\u5217\u6570\u636e<\/strong><\/h2>\n<p>data = {&#39;Date&#39;: pd.date_range(start=&#39;2023-01-01&#39;, periods=10, freq=&#39;D&#39;),<\/p>\n<p>        &#39;Value&#39;: [10, 12, 15, 14, 13, 16, 18, 17, 19, 20]}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<p>df.set_index(&#39;Date&#39;, inplace=True)<\/p>\n<h2><strong>\u8ba1\u7b97\u5dee\u5206<\/strong><\/h2>\n<p>df[&#39;Diff&#39;] = df[&#39;Value&#39;].diff()<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>Pandas\u7684diff()\u51fd\u6570\u975e\u5e38\u7b80\u5355\u6613\u7528\u3002\u5728\u4e0a\u8ff0\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u521b\u5efa\u4e86\u4e00\u4e2a\u5305\u542b\u65e5\u671f\u548c\u6570\u503c\u7684DataFrame\u3002\u7136\u540e\uff0c\u6211\u4eec\u901a\u8fc7\u8c03\u7528<code>df[&#39;Value&#39;].diff()<\/code>\u8ba1\u7b97\u6570\u503c\u5217\u7684\u5dee\u5206\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u7684\u5217&#39;Diff&#39;\u4e2d\u3002\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u80fd\u591f\u8f7b\u677e\u5730\u770b\u5230\u6bcf\u4e2a\u65f6\u95f4\u70b9\u4e0a\u7684\u6570\u503c\u53d8\u5316\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528Pandas\u5e93\u4e2d\u7684shift()\u51fd\u6570<\/h3>\n<\/p>\n<p><p>shift()\u51fd\u6570\u53ef\u4ee5\u5c06\u6570\u636e\u5411\u524d\u6216\u5411\u540e\u79fb\u52a8\u4e00\u4e2a\u6216\u591a\u4e2a\u4f4d\u7f6e\u3002\u901a\u8fc7\u7ed3\u5408shift()\u51fd\u6570\u548c\u51cf\u6cd5\u8fd0\u7b97\u7b26\uff0c\u6211\u4eec\u53ef\u4ee5\u624b\u52a8\u8ba1\u7b97\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u5206\u3002\u8fd9\u79cd\u65b9\u6cd5\u63d0\u4f9b\u4e86\u66f4\u5927\u7684\u7075\u6d3b\u6027\uff0c\u56e0\u4e3a\u5b83\u5141\u8bb8\u6211\u4eec\u8ba1\u7b97\u4efb\u610f\u9636\u7684\u5dee\u5206\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8ba1\u7b97\u5dee\u5206<\/p>\n<p>df[&#39;Shifted_Value&#39;] = df[&#39;Value&#39;].shift(1)<\/p>\n<p>df[&#39;Manual_Diff&#39;] = df[&#39;Value&#39;] - df[&#39;Shifted_Value&#39;]<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u4f7f\u7528shift(1)\u51fd\u6570\u5c06\u6570\u503c\u5217\u5411\u524d\u79fb\u52a8\u4e00\u4e2a\u4f4d\u7f6e\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u7684\u5217&#39;Shifted_Value&#39;\u4e2d\u3002\u7136\u540e\uff0c\u6211\u4eec\u901a\u8fc7\u51cf\u6cd5\u8fd0\u7b97\u7b26\u8ba1\u7b97\u5f53\u524d\u503c\u4e0e\u524d\u4e00\u4e2a\u503c\u4e4b\u95f4\u7684\u5dee\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u7684\u5217&#39;Manual_Diff&#39;\u4e2d\u3002\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u5b9e\u73b0\u4e86\u4e0ediff()\u51fd\u6570\u76f8\u540c\u7684\u6548\u679c\uff0c\u4f46\u8fd9\u79cd\u65b9\u6cd5\u5141\u8bb8\u6211\u4eec\u6839\u636e\u9700\u8981\u8fdb\u884c\u66f4\u591a\u7684\u81ea\u5b9a\u4e49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570<\/h3>\n<\/p>\n<p><p>\u6709\u65f6\u5019\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u8ba1\u7b97\u66f4\u52a0\u590d\u6742\u7684\u5dee\u5206\uff0c\u4f8b\u5982\u5e26\u6709\u6761\u4ef6\u7684\u5dee\u5206\u6216\u591a\u5217\u6570\u636e\u7684\u5dee\u5206\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u4ee5\u7f16\u5199\u81ea\u5b9a\u4e49\u51fd\u6570\u6765\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u81ea\u5b9a\u4e49\u5dee\u5206\u51fd\u6570<\/p>\n<p>def custom_diff(series, periods=1):<\/p>\n<p>    return series - series.shift(periods)<\/p>\n<h2><strong>\u8ba1\u7b97\u5dee\u5206<\/strong><\/h2>\n<p>df[&#39;Custom_Diff&#39;] = custom_diff(df[&#39;Value&#39;], periods=1)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a\u540d\u4e3acustom_diff\u7684\u51fd\u6570\uff0c\u8be5\u51fd\u6570\u63a5\u53d7\u4e00\u4e2a\u65f6\u95f4\u5e8f\u5217\u548c\u4e00\u4e2a\u53c2\u6570periods\uff08\u9ed8\u8ba4\u503c\u4e3a1\uff09\uff0c\u5e76\u8fd4\u56de\u8ba1\u7b97\u51fa\u7684\u5dee\u5206\u503c\u3002\u901a\u8fc7\u8c03\u7528\u8be5\u51fd\u6570\u5e76\u4f20\u9012\u6570\u503c\u5217\u548cperiods\u53c2\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u8ba1\u7b97\u51fa\u81ea\u5b9a\u4e49\u7684\u5dee\u5206\u7ed3\u679c\u3002\u8fd9\u79cd\u65b9\u6cd5\u4f7f\u6211\u4eec\u80fd\u591f\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\u6765\u8c03\u6574\u5dee\u5206\u8ba1\u7b97\u7684\u903b\u8f91\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u5e94\u7528\u573a\u666f\u548c\u5b9e\u8df5<\/h3>\n<\/p>\n<p><h4>1\u3001\u65f6\u5e8f\u6570\u636e\u7684\u8d8b\u52bf\u5206\u6790<\/h4>\n<\/p>\n<p><p>\u901a\u8fc7\u8ba1\u7b97\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u5206\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u6e05\u6670\u5730\u770b\u5230\u6570\u636e\u7684\u53d8\u5316\u8d8b\u52bf\u3002\u4f8b\u5982\uff0c\u5728\u80a1\u7968\u4ef7\u683c\u5206\u6790\u4e2d\uff0c\u8ba1\u7b97\u6bcf\u65e5\u4ef7\u683c\u7684\u5dee\u5206\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8bc6\u522b\u4ef7\u683c\u7684\u4e0a\u5347\u6216\u4e0b\u964d\u8d8b\u52bf\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<h2><strong>\u7ed8\u5236\u539f\u59cb\u6570\u636e\u548c\u5dee\u5206\u6570\u636e<\/strong><\/h2>\n<p>plt.figure(figsize=(12, 6))<\/p>\n<p>plt.subplot(2, 1, 1)<\/p>\n<p>plt.plot(df.index, df[&#39;Value&#39;], label=&#39;Original Data&#39;)<\/p>\n<p>plt.legend()<\/p>\n<p>plt.subplot(2, 1, 2)<\/p>\n<p>plt.plot(df.index, df[&#39;Diff&#39;], label=&#39;Differenced Data&#39;, color=&#39;orange&#39;)<\/p>\n<p>plt.legend()<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u7ed8\u5236\u539f\u59cb\u6570\u636e\u548c\u5dee\u5206\u6570\u636e\u7684\u56fe\u8868\uff0c\u6211\u4eec\u53ef\u4ee5\u76f4\u89c2\u5730\u6bd4\u8f83\u4e24\u8005\u4e4b\u95f4\u7684\u5dee\u5f02\u3002\u539f\u59cb\u6570\u636e\u7684\u56fe\u8868\u5c55\u793a\u4e86\u6570\u503c\u7684\u7edd\u5bf9\u53d8\u5316\uff0c\u800c\u5dee\u5206\u6570\u636e\u7684\u56fe\u8868\u5219\u5c55\u793a\u4e86\u6570\u503c\u7684\u76f8\u5bf9\u53d8\u5316\u3002\u8fd9\u6709\u52a9\u4e8e\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u7684\u53d8\u5316\u8d8b\u52bf\u548c\u6ce2\u52a8\u60c5\u51b5\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u5f02\u5e38\u70b9\u68c0\u6d4b<\/h4>\n<\/p>\n<p><p>\u5dee\u5206\u8ba1\u7b97\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8bc6\u522b\u65f6\u5e8f\u6570\u636e\u4e2d\u7684\u5f02\u5e38\u70b9\u3002\u901a\u5e38\u60c5\u51b5\u4e0b\uff0c\u5dee\u5206\u503c\u4f1a\u5728\u4e00\u5b9a\u8303\u56f4\u5185\u6ce2\u52a8\uff0c\u4f46\u5982\u679c\u67d0\u4e2a\u5dee\u5206\u503c\u663e\u8457\u504f\u79bb\u6b63\u5e38\u8303\u56f4\uff0c\u5219\u53ef\u80fd\u8868\u793a\u6570\u636e\u4e2d\u5b58\u5728\u5f02\u5e38\u70b9\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u68c0\u6d4b\u5f02\u5e38\u70b9<\/p>\n<p>threshold = 2<\/p>\n<p>df[&#39;Anomaly&#39;] = df[&#39;Diff&#39;].abs() &gt; threshold<\/p>\n<p>print(df[df[&#39;Anomaly&#39;]])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u8bbe\u7f6e\u4e86\u4e00\u4e2a\u9608\u503c\uff08\u4f8b\u59822\uff09\uff0c\u7528\u4e8e\u5224\u65ad\u5dee\u5206\u503c\u662f\u5426\u4e3a\u5f02\u5e38\u70b9\u3002\u901a\u8fc7\u8ba1\u7b97\u5dee\u5206\u503c\u7684\u7edd\u5bf9\u503c\u5e76\u4e0e\u9608\u503c\u8fdb\u884c\u6bd4\u8f83\uff0c\u6211\u4eec\u53ef\u4ee5\u6807\u8bb0\u51fa\u5dee\u5206\u503c\u663e\u8457\u504f\u79bb\u6b63\u5e38\u8303\u56f4\u7684\u5f02\u5e38\u70b9\u3002\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u80fd\u591f\u5feb\u901f\u8bc6\u522b\u5e76\u8fdb\u4e00\u6b65\u5206\u6790\u6570\u636e\u4e2d\u7684\u5f02\u5e38\u70b9\u3002<\/p>\n<\/p>\n<p><h4>3\u3001\u65f6\u5e8f\u6570\u636e\u7684\u5e73\u7a33\u5316\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u4e00\u4e9b\u65f6\u5e8f\u5206\u6790\u65b9\u6cd5\uff08\u4f8b\u5982ARIMA\u6a21\u578b\uff09\uff0c\u6570\u636e\u9700\u8981\u662f\u5e73\u7a33\u7684\u3002\u901a\u8fc7\u8ba1\u7b97\u5dee\u5206\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u975e\u5e73\u7a33\u7684\u65f6\u5e8f\u6570\u636e\u8f6c\u6362\u4e3a\u5e73\u7a33\u6570\u636e\uff0c\u4ece\u800c\u6ee1\u8db3\u5206\u6790\u65b9\u6cd5\u7684\u8981\u6c42\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from statsmodels.tsa.stattools import adfuller<\/p>\n<h2><strong>\u539f\u59cb\u6570\u636e\u7684ADF\u68c0\u9a8c<\/strong><\/h2>\n<p>result = adfuller(df[&#39;Value&#39;])<\/p>\n<p>print(&#39;ADF Statistic:&#39;, result[0])<\/p>\n<p>print(&#39;p-value:&#39;, result[1])<\/p>\n<h2><strong>\u5dee\u5206\u6570\u636e\u7684ADF\u68c0\u9a8c<\/strong><\/h2>\n<p>result_diff = adfuller(df[&#39;Diff&#39;].dropna())<\/p>\n<p>print(&#39;ADF Statistic (Differenced Data):&#39;, result_diff[0])<\/p>\n<p>print(&#39;p-value (Differenced Data):&#39;, result_diff[1])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528ADF\u68c0\u9a8c\uff08Augmented Dickey-Fuller test\uff09\u6765\u5224\u65ad\u6570\u636e\u662f\u5426\u5e73\u7a33\u3002\u9996\u5148\uff0c\u6211\u4eec\u5bf9\u539f\u59cb\u6570\u636e\u8fdb\u884cADF\u68c0\u9a8c\uff0c\u8f93\u51faADF\u7edf\u8ba1\u91cf\u548cp\u503c\u3002\u63a5\u7740\uff0c\u6211\u4eec\u5bf9\u5dee\u5206\u6570\u636e\u8fdb\u884c\u540c\u6837\u7684ADF\u68c0\u9a8c\u3002\u901a\u8fc7\u6bd4\u8f83\u4e24\u8005\u7684\u7ed3\u679c\uff0c\u6211\u4eec\u53ef\u4ee5\u5224\u65ad\u5dee\u5206\u5904\u7406\u662f\u5426\u6709\u6548\u5730\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u5e73\u7a33\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u5728Python\u4e2d\u8fdb\u884c\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u503c\u8ba1\u7b97\u662f\u65f6\u5e8f\u5206\u6790\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u901a\u8fc7\u4f7f\u7528Pandas\u5e93\u4e2d\u7684diff()\u51fd\u6570\u3001shift()\u51fd\u6570\uff0c\u4ee5\u53ca\u81ea\u5b9a\u4e49\u51fd\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u7075\u6d3b\u5730\u8ba1\u7b97\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u5206\u3002\u8fd9\u4e9b\u65b9\u6cd5\u4e0d\u4ec5\u7b80\u5355\u6613\u7528\uff0c\u800c\u4e14\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5e94\u7528\u573a\u666f\uff0c\u5305\u62ec\u8d8b\u52bf\u5206\u6790\u3001\u5f02\u5e38\u70b9\u68c0\u6d4b\u3001\u548c\u5e73\u7a33\u5316\u5904\u7406\u7b49\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u5e76\u7ed3\u5408\u53ef\u89c6\u5316\u5de5\u5177\u548c\u7edf\u8ba1\u68c0\u9a8c\u65b9\u6cd5\uff0c\u6df1\u5165\u5206\u6790\u548c\u7406\u89e3\u65f6\u5e8f\u6570\u636e\u7684\u53d8\u5316\u89c4\u5f8b\u3002\u901a\u8fc7\u638c\u63e1\u8fd9\u4e9b\u6280\u672f\uff0c\u6211\u4eec\u80fd\u591f\u66f4\u52a0\u6709\u6548\u5730\u8fdb\u884c\u65f6\u5e8f\u6570\u636e\u7684\u5206\u6790\u548c\u5904\u7406\uff0c\u4ece\u800c\u5728\u5404\u79cd\u9886\u57df\uff08\u5982\u91d1\u878d\u3001\u6c14\u8c61\u3001\u4ea4\u901a\u7b49\uff09\u4e2d\u83b7\u5f97\u6709\u4ef7\u503c\u7684\u6d1e\u5bdf\u548c\u51b3\u7b56\u652f\u6301\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5904\u7406\u65f6\u5e8f\u6570\u636e\u4e2d\u7684\u7f3a\u5931\u503c\uff1f<\/strong><br \/>\u5904\u7406\u65f6\u5e8f\u6570\u636e\u65f6\uff0c\u7f3a\u5931\u503c\u662f\u4e00\u4e2a\u5e38\u89c1\u95ee\u9898\u3002\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u6765\u586b\u8865\u8fd9\u4e9b\u7f3a\u5931\u503c\uff0c\u4f8b\u5982\u7ebf\u6027\u63d2\u503c\u3001\u65f6\u95f4\u5e8f\u5217\u63d2\u503c\u6216\u4f7f\u7528\u66f4\u590d\u6742\u7684\u63d2\u503c\u65b9\u6cd5\u5982\u6837\u6761\u63d2\u503c\u3002Pandas\u5e93\u63d0\u4f9b\u4e86<code>interpolate()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5b9e\u73b0\u8fd9\u4e9b\u63d2\u503c\u65b9\u6cd5\u3002\u901a\u8fc7\u8bbe\u7f6e\u4e0d\u540c\u7684\u53c2\u6570\uff0c\u7528\u6237\u53ef\u4ee5\u9009\u62e9\u9002\u5408\u81ea\u5df1\u6570\u636e\u7279\u6027\u7684\u63d2\u503c\u65b9\u5f0f\u3002<\/p>\n<p><strong>\u5728\u8fdb\u884c\u65f6\u5e8f\u6570\u636e\u5dee\u503c\u65f6\uff0c\u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u63d2\u503c\u65b9\u6cd5\uff1f<\/strong><br \/>\u9009\u62e9\u63d2\u503c\u65b9\u6cd5\u65f6\uff0c\u8003\u8651\u6570\u636e\u7684\u6027\u8d28\u975e\u5e38\u91cd\u8981\u3002\u4f8b\u5982\uff0c\u5982\u679c\u6570\u636e\u53d8\u5316\u5e73\u6ed1\uff0c\u7ebf\u6027\u63d2\u503c\u6216\u6837\u6761\u63d2\u503c\u53ef\u80fd\u662f\u5408\u9002\u7684\u9009\u62e9\u3002\u5982\u679c\u6570\u636e\u5b58\u5728\u8f83\u5927\u7684\u6ce2\u52a8\uff0c\u53ef\u80fd\u9700\u8981\u66f4\u590d\u6742\u7684\u63d2\u503c\u65b9\u6cd5\uff0c\u4f8b\u5982\u591a\u9879\u5f0f\u63d2\u503c\u6216\u57fa\u4e8e\u76f8\u90bb\u70b9\u7684\u52a0\u6743\u5e73\u5747\u3002\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u53ef\u89c6\u5316\u6570\u636e\u6765\u5224\u65ad\u54ea\u79cd\u65b9\u6cd5\u6700\u5408\u9002\u3002<\/p>\n<p><strong>\u65f6\u5e8f\u6570\u636e\u63d2\u503c\u540e\uff0c\u5982\u4f55\u8bc4\u4f30\u63d2\u503c\u7ed3\u679c\u7684\u51c6\u786e\u6027\uff1f<\/strong><br \/>\u8bc4\u4f30\u63d2\u503c\u7ed3\u679c\u7684\u51c6\u786e\u6027\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u8fdb\u884c\uff0c\u4f8b\u5982\u4e0e\u5b9e\u9645\u503c\u6bd4\u8f83\u3001\u8ba1\u7b97\u63d2\u503c\u8bef\u5dee\u6216\u4f7f\u7528\u4ea4\u53c9\u9a8c\u8bc1\u65b9\u6cd5\u3002\u53ef\u4ee5\u4f7f\u7528\u5747\u65b9\u8bef\u5dee\uff08MSE\uff09\u7b49\u6307\u6807\u91cf\u5316\u63d2\u503c\u7684\u51c6\u786e\u6027\u3002\u6b64\u5916\uff0c\u7528\u6237\u8fd8\u53ef\u4ee5\u7ed8\u5236\u63d2\u503c\u540e\u7684\u6570\u636e\u4e0e\u539f\u59cb\u6570\u636e\u7684\u6bd4\u8f83\u56fe\uff0c\u4ece\u800c\u76f4\u89c2\u5730\u5224\u65ad\u63d2\u503c\u6548\u679c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u8fdb\u884c\u65f6\u5e8f\u6570\u636e\u7684\u5dee\u503c\u8ba1\u7b97\uff0c\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528Pandas\u5e93\u4e2d\u7684diff()\u51fd\u6570\u3001shift()\u51fd\u6570\u3001\u4ee5 [&hellip;]","protected":false},"author":3,"featured_media":1114411,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1114406"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1114406"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1114406\/revisions"}],"predecessor-version":[{"id":1114413,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1114406\/revisions\/1114413"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1114411"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1114406"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1114406"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1114406"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}