{"id":963644,"date":"2024-12-27T04:20:19","date_gmt":"2024-12-26T20:20:19","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/963644.html"},"modified":"2024-12-27T04:20:21","modified_gmt":"2024-12-26T20:20:21","slug":"python%e5%a6%82%e4%bd%95%e8%ae%a1%e7%ae%97%e4%b8%ad%e4%bd%8d%e6%95%b0","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/963644.html","title":{"rendered":"python\u5982\u4f55\u8ba1\u7b97\u4e2d\u4f4d\u6570"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24180827\/9ce10ae8-66c5-417d-9d12-3ddac8dd7ace.webp\" alt=\"python\u5982\u4f55\u8ba1\u7b97\u4e2d\u4f4d\u6570\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u4e3b\u8981\u65b9\u6cd5\u662f\u4f7f\u7528\u5185\u7f6e\u7684\u7edf\u8ba1\u6a21\u5757<code>statistics<\/code>\u4e2d\u7684<code>median<\/code>\u51fd\u6570\u3001\u5229\u7528\u6392\u5e8f\u548c\u7d22\u5f15\u624b\u52a8\u8ba1\u7b97\u3001\u4ee5\u53ca\u4f7f\u7528NumPy\u5e93\u7684<code>median<\/code>\u51fd\u6570\u3002\u6700\u5e38\u7528\u4e14\u7b80\u4fbf\u7684\u65b9\u6cd5\u662f\u4f7f\u7528<code>statistics.median<\/code>\u51fd\u6570\uff0c\u56e0\u4e3a\u5b83\u76f4\u63a5\u63d0\u4f9b\u4e86\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u529f\u80fd\u3002<\/strong><\/p>\n<\/p>\n<p><p>\u8be6\u7ec6\u63cf\u8ff0\uff1a<code>statistics.median<\/code>\u51fd\u6570\u53ef\u4ee5\u5904\u7406\u5217\u8868\u3001\u5143\u7ec4\u7b49\u53ef\u8fed\u4ee3\u5bf9\u8c61\uff0c\u5e76\u81ea\u52a8\u5bf9\u6570\u636e\u8fdb\u884c\u6392\u5e8f\u4ee5\u627e\u51fa\u4e2d\u4f4d\u6570\u3002\u5bf9\u4e8e\u5947\u6570\u4e2a\u5143\u7d20\u7684\u6570\u636e\u96c6\uff0c\u5b83\u8fd4\u56de\u4e2d\u95f4\u7684\u90a3\u4e2a\u5143\u7d20\uff1b\u5bf9\u4e8e\u5076\u6570\u4e2a\u5143\u7d20\u7684\u6570\u636e\u96c6\uff0c\u5b83\u8fd4\u56de\u4e2d\u95f4\u4e24\u4e2a\u5143\u7d20\u7684\u5e73\u5747\u503c\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528<code>statistics.median<\/code>\u51fd\u6570\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import statistics<\/p>\n<p>data = [1, 3, 5, 7, 9]<\/p>\n<p>median_value = statistics.median(data)<\/p>\n<p>print(&quot;The median is:&quot;, median_value)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u8ba8\u8bbaPython\u4e2d\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u5176\u4ed6\u65b9\u6cd5\u548c\u76f8\u5173\u77e5\u8bc6\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528STATISTICS\u6a21\u5757<\/h3>\n<\/p>\n<p><p>Python\u7684<code>statistics<\/code>\u6a21\u5757\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u65b9\u6cd5\u6765\u8ba1\u7b97\u4e2d\u4f4d\u6570\uff0c\u8fd9\u5bf9\u4e8e\u5904\u7406\u4e00\u7ef4\u6570\u636e\u96c6\u975e\u5e38\u65b9\u4fbf\u3002<\/p>\n<\/p>\n<p><h4>1. <code>median<\/code>\u51fd\u6570<\/h4>\n<\/p>\n<p><p><code>median<\/code>\u51fd\u6570\u662f\u6700\u5e38\u7528\u7684\u7528\u4e8e\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u65b9\u6cd5\u3002\u5b83\u53ef\u4ee5\u5904\u7406\u4efb\u4f55\u53ef\u8fed\u4ee3\u7684\u6570\u503c\u7c7b\u578b\u6570\u636e\uff0c\u5982\u5217\u8868\u3001\u5143\u7ec4\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import statistics<\/p>\n<p>data = [2, 4, 6, 8, 10]<\/p>\n<p>median_value = statistics.median(data)<\/p>\n<p>print(f&quot;The median is: {median_value}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. <code>median_low<\/code>\u548c<code>median_high<\/code><\/h4>\n<\/p>\n<p><p>\u9664\u4e86<code>median<\/code>\u51fd\u6570\uff0c<code>statistics<\/code>\u6a21\u5757\u8fd8\u63d0\u4f9b\u4e86<code>median_low<\/code>\u548c<code>median_high<\/code>\u51fd\u6570\u3002<code>median_low<\/code>\u8fd4\u56de\u6570\u636e\u96c6\u4e2d\u95f4\u7684\u8f83\u4f4e\u503c\uff0c\u800c<code>median_high<\/code>\u8fd4\u56de\u8f83\u9ad8\u503c\u3002\u8fd9\u5728\u5904\u7406\u5076\u6570\u4e2a\u5143\u7d20\u7684\u6570\u636e\u96c6\u65f6\u5c24\u5176\u6709\u7528\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">data_even = [1, 3, 5, 7, 9, 11]<\/p>\n<p>median_low = statistics.median_low(data_even)<\/p>\n<p>median_high = statistics.median_high(data_even)<\/p>\n<p>print(f&quot;The lower median is: {median_low}&quot;)<\/p>\n<p>print(f&quot;The higher median is: {median_high}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u624b\u52a8\u8ba1\u7b97\u4e2d\u4f4d\u6570<\/h3>\n<\/p>\n<p><p>\u6709\u65f6\uff0c\u4f60\u53ef\u80fd\u60f3\u8981\u5728\u4e0d\u4f7f\u7528\u4efb\u4f55\u5e93\u7684\u60c5\u51b5\u4e0b\u8ba1\u7b97\u4e2d\u4f4d\u6570\u3002\u8fd9\u9700\u8981\u624b\u52a8\u5bf9\u6570\u636e\u8fdb\u884c\u6392\u5e8f\uff0c\u7136\u540e\u6839\u636e\u6570\u636e\u957f\u5ea6\u9009\u62e9\u5408\u9002\u7684\u7d22\u5f15\u6765\u67e5\u627e\u4e2d\u4f4d\u6570\u3002<\/p>\n<\/p>\n<p><h4>1. \u6392\u5e8f\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u5728\u624b\u52a8\u8ba1\u7b97\u4e2d\u4f4d\u6570\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u6392\u5e8f\u3002\u53ef\u4ee5\u4f7f\u7528Python\u5185\u7f6e\u7684<code>sorted()<\/code>\u51fd\u6570\u8fdb\u884c\u6392\u5e8f\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">data = [5, 3, 8, 1, 7]<\/p>\n<p>sorted_data = sorted(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u8ba1\u7b97\u4e2d\u4f4d\u6570<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u5947\u6570\u4e2a\u5143\u7d20\u7684\u6570\u636e\u96c6\uff0c\u4e2d\u4f4d\u6570\u662f\u4e2d\u95f4\u7684\u5143\u7d20\uff1b\u5bf9\u4e8e\u5076\u6570\u4e2a\u5143\u7d20\u7684\u6570\u636e\u96c6\uff0c\u4e2d\u4f4d\u6570\u662f\u4e2d\u95f4\u4e24\u4e2a\u5143\u7d20\u7684\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def calculate_median(data):<\/p>\n<p>    n = len(data)<\/p>\n<p>    sorted_data = sorted(data)<\/p>\n<p>    if n % 2 == 1:<\/p>\n<p>        # \u5947\u6570\u4e2a\u5143\u7d20\uff0c\u8fd4\u56de\u4e2d\u95f4\u5143\u7d20<\/p>\n<p>        return sorted_data[n \/\/ 2]<\/p>\n<p>    else:<\/p>\n<p>        # \u5076\u6570\u4e2a\u5143\u7d20\uff0c\u8fd4\u56de\u4e2d\u95f4\u4e24\u4e2a\u5143\u7d20\u7684\u5e73\u5747\u503c<\/p>\n<p>        mid1 = sorted_data[n \/\/ 2 - 1]<\/p>\n<p>        mid2 = sorted_data[n \/\/ 2]<\/p>\n<p>        return (mid1 + mid2) \/ 2<\/p>\n<p>median_value = calculate_median(data)<\/p>\n<p>print(f&quot;The median is: {median_value}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528NUMPY\u5e93<\/h3>\n<\/p>\n<p><p>NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u4e5f\u63d0\u4f9b\u4e86\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u529f\u80fd\u3002\u5b83\u7279\u522b\u9002\u5408\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u548c\u591a\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h4>1. <code>numpy.median<\/code>\u51fd\u6570<\/h4>\n<\/p>\n<p><p>NumPy\u7684<code>median<\/code>\u51fd\u6570\u53ef\u4ee5\u76f4\u63a5\u7528\u4e8e\u8ba1\u7b97\u6570\u7ec4\u7684\u4e2d\u4f4d\u6570\u3002\u5b83\u53ef\u4ee5\u5904\u7406\u591a\u7ef4\u6570\u7ec4\uff0c\u5e76\u4e14\u5141\u8bb8\u6307\u5b9a\u8f74\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>data = np.array([1, 3, 5, 7, 9])<\/p>\n<p>median_value = np.median(data)<\/p>\n<p>print(f&quot;The median is: {median_value}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u5904\u7406\u591a\u7ef4\u6570\u7ec4<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u591a\u7ef4\u6570\u7ec4\uff0c\u53ef\u4ee5\u6307\u5b9a\u4e00\u4e2a\u8f74\u6765\u8ba1\u7b97\u8be5\u8f74\u4e0a\u7684\u4e2d\u4f4d\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">data_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])<\/p>\n<p>median_axis0 = np.median(data_2d, axis=0)<\/p>\n<p>median_axis1 = np.median(data_2d, axis=1)<\/p>\n<p>print(f&quot;The median along axis 0 is: {median_axis0}&quot;)<\/p>\n<p>print(f&quot;The median along axis 1 is: {median_axis1}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u4e2d\u4f4d\u6570\u7684\u5e94\u7528\u4e0e\u91cd\u8981\u6027<\/h3>\n<\/p>\n<p><p>\u4e2d\u4f4d\u6570\u5728\u6570\u636e\u5206\u6790\u4e2d\u5177\u6709\u91cd\u8981\u7684\u610f\u4e49\uff0c\u5c24\u5176\u5728\u4ee5\u4e0b\u60c5\u51b5\u4e0b\uff1a<\/p>\n<\/p>\n<p><h4>1. \u6297\u5e72\u6270\u80fd\u529b\u5f3a<\/h4>\n<\/p>\n<p><p>\u4e2d\u4f4d\u6570\u4e0d\u53d7\u6781\u7aef\u503c\u6216\u5f02\u5e38\u503c\u7684\u5f71\u54cd\uff0c\u6bd4\u5747\u503c\u66f4\u80fd\u4ee3\u8868\u6570\u636e\u7684\u4e2d\u5fc3\u8d8b\u52bf\u3002\u4f8b\u5982\uff0c\u5728\u6536\u5165\u6570\u636e\u4e2d\uff0c\u5c11\u6570\u6781\u9ad8\u6536\u5165\u53ef\u80fd\u4f1a\u663e\u8457\u63d0\u9ad8\u5e73\u5747\u503c\uff0c\u800c\u4e2d\u4f4d\u6570\u5219\u4fdd\u6301\u7a33\u5b9a\u3002<\/p>\n<\/p>\n<p><h4>2. \u63cf\u8ff0\u6570\u636e\u5206\u5e03<\/h4>\n<\/p>\n<p><p>\u4e2d\u4f4d\u6570\u5e38\u7528\u4e8e\u63cf\u8ff0\u6570\u636e\u7684\u5bf9\u79f0\u6027\u548c\u504f\u6001\u3002\u7ed3\u5408\u56db\u5206\u4f4d\u6570\uff08\u5982\u7b2c\u4e00\u548c\u7b2c\u4e09\u56db\u5206\u4f4d\u6570\uff09\uff0c\u4e2d\u4f4d\u6570\u53ef\u4ee5\u5e2e\u52a9\u6784\u5efa\u7bb1\u7ebf\u56fe\uff0c\u5c55\u793a\u6570\u636e\u7684\u5206\u5e03\u60c5\u51b5\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u4f18\u5316\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u6027\u80fd<\/h3>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u65f6\uff0c\u8ba1\u7b97\u4e2d\u4f4d\u6570\u53ef\u80fd\u4f1a\u6bd4\u8f83\u8017\u65f6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u4f18\u5316\u8ba1\u7b97\u6027\u80fd\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n<p><h4>1. \u4f7f\u7528NumPy<\/h4>\n<\/p>\n<p><p>NumPy\u7684\u5e95\u5c42\u5b9e\u73b0\u662f\u7528C\u7f16\u5199\u7684\uff0c\u6027\u80fd\u4f18\u4e8e\u7eafPython\u4ee3\u7801\uff0c\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h4>2. \u91c7\u6837<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u975e\u5e38\u5927\u7684\u6570\u636e\u96c6\uff0c\u4f7f\u7528\u91c7\u6837\u6280\u672f\u8ba1\u7b97\u4e2d\u4f4d\u6570\u53ef\u4ee5\u663e\u8457\u964d\u4f4e\u8ba1\u7b97\u65f6\u95f4\u3002\u5728\u4fdd\u8bc1\u7ed3\u679c\u7cbe\u5ea6\u7684\u524d\u63d0\u4e0b\uff0c\u968f\u673a\u91c7\u6837\u90e8\u5206\u6570\u636e\u8fdb\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import random<\/p>\n<p>def sample_median(data, sample_size):<\/p>\n<p>    sample = random.sample(data, sample_size)<\/p>\n<p>    return np.median(sample)<\/p>\n<p>data_large = np.random.rand(1000000)<\/p>\n<p>median_sample = sample_median(data_large, 10000)<\/p>\n<p>print(f&quot;The sampled median is: {median_sample}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516d\u3001\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u5e38\u89c1\u95ee\u9898<\/h3>\n<\/p>\n<p><p>\u5728\u4f7f\u7528Python\u8ba1\u7b97\u4e2d\u4f4d\u6570\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u4e00\u4e9b\u95ee\u9898\u6216\u9519\u8bef\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u95ee\u9898\u53ca\u5176\u89e3\u51b3\u65b9\u6848\uff1a<\/p>\n<\/p>\n<p><h4>1. \u6570\u636e\u7c7b\u578b\u9519\u8bef<\/h4>\n<\/p>\n<p><p>\u786e\u4fdd\u8f93\u5165\u7684\u6570\u636e\u7c7b\u578b\u662f\u53ef\u8fed\u4ee3\u7684\u6570\u503c\u7c7b\u578b\u3002\u975e\u6570\u503c\u7c7b\u578b\u4f1a\u5bfc\u81f4\u8ba1\u7b97\u9519\u8bef\u6216\u5f02\u5e38\u3002<\/p>\n<\/p>\n<p><h4>2. \u7a7a\u6570\u636e\u96c6<\/h4>\n<\/p>\n<p><p>\u5c1d\u8bd5\u8ba1\u7b97\u7a7a\u6570\u636e\u96c6\u7684\u4e2d\u4f4d\u6570\u4f1a\u5f15\u53d1\u9519\u8bef\u3002\u5e94\u5728\u8ba1\u7b97\u524d\u68c0\u67e5\u6570\u636e\u96c6\u662f\u5426\u4e3a\u7a7a\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">data_empty = []<\/p>\n<p>if len(data_empty) == 0:<\/p>\n<p>    print(&quot;Data set is empty.&quot;)<\/p>\n<p>else:<\/p>\n<p>    median_value = statistics.median(data_empty)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3. \u591a\u7ef4\u6570\u636e\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u5728\u5904\u7406\u591a\u7ef4\u6570\u636e\u65f6\uff0c\u9700\u660e\u786e\u6307\u5b9a\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u8f74\uff0c\u5426\u5219\u53ef\u80fd\u5bfc\u81f4\u7ed3\u679c\u4e0e\u9884\u671f\u4e0d\u7b26\u3002<\/p>\n<\/p>\n<p><h3>\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u5728Python\u4e2d\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837\uff0c\u4ece\u7b80\u5355\u4f7f\u7528<code>statistics<\/code>\u6a21\u5757\u5230\u590d\u6742\u7684NumPy\u5904\u7406\u591a\u7ef4\u6570\u7ec4\uff0c\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u9002\u7528\u573a\u666f\u3002\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53ef\u4ee5\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\uff0c\u5e76\u786e\u4fdd\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u4e2d\u4f4d\u6570\u662f\u4e00\u4e2a\u91cd\u8981\u7684\u7edf\u8ba1\u6307\u6807\uff0c\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u7684\u5206\u5e03\u548c\u4e2d\u5fc3\u8d8b\u52bf\u3002\u4e86\u89e3\u5e76\u638c\u63e1\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u652f\u6301\u6570\u636e\u5206\u6790\u548c\u79d1\u5b66\u7814\u7a76\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u4e00\u7ec4\u6570\u636e\u7684\u4e2d\u4f4d\u6570\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684\u6392\u5e8f\u529f\u80fd\u548c\u5217\u8868\u5207\u7247\u6765\u8ba1\u7b97\u4e2d\u4f4d\u6570\u3002\u9996\u5148\uff0c\u5bf9\u6570\u636e\u8fdb\u884c\u6392\u5e8f\u3002\u5982\u679c\u6570\u636e\u7684\u957f\u5ea6\u662f\u5947\u6570\uff0c\u4e2d\u4f4d\u6570\u5c31\u662f\u4e2d\u95f4\u7684\u6570\uff1b\u5982\u679c\u662f\u5076\u6570\uff0c\u4e2d\u4f4d\u6570\u5219\u662f\u4e2d\u95f4\u4e24\u4e2a\u6570\u7684\u5e73\u5747\u503c\u3002\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">data = [3, 1, 4, 1, 5, 9]\ndata.sort()\nn = len(data)\nmedian = (data[n\/\/2] + data[(n-1)\/\/2]) \/ 2\n<\/code><\/pre>\n<p><strong>Python\u4e2d\u6709\u54ea\u4e9b\u5e93\u53ef\u4ee5\u5feb\u901f\u8ba1\u7b97\u4e2d\u4f4d\u6570\uff1f<\/strong><br \/>Python\u7684NumPy\u5e93\u662f\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u4e00\u4e2a\u975e\u5e38\u6709\u6548\u7684\u5de5\u5177\u3002\u4f7f\u7528NumPy\u7684<code>median()<\/code>\u51fd\u6570\u53ef\u4ee5\u76f4\u63a5\u8ba1\u7b97\u51fa\u4e2d\u4f4d\u6570\uff0c\u64cd\u4f5c\u7b80\u5355\u4e14\u6548\u7387\u9ad8\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n<pre><code class=\"language-python\">import numpy as np\ndata = [3, 1, 4, 1, 5, 9]\nmedian = np.median(data)\n<\/code><\/pre>\n<p><strong>\u5982\u679c\u6570\u636e\u4e2d\u5305\u542b\u7f3a\u5931\u503c\uff0cPython\u5982\u4f55\u5904\u7406\u8ba1\u7b97\u4e2d\u4f4d\u6570\uff1f<\/strong><br \/>\u5728\u5904\u7406\u5305\u542b\u7f3a\u5931\u503c\u7684\u6570\u636e\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u3002Pandas\u63d0\u4f9b\u4e86<code>median()<\/code>\u51fd\u6570\uff0c\u5e76\u4e14\u5728\u8ba1\u7b97\u65f6\u4f1a\u81ea\u52a8\u5ffd\u7565\u7f3a\u5931\u503c\u3002\u793a\u4f8b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u5904\u7406\uff1a  <\/p>\n<pre><code class=\"language-python\">import pandas as pd\ndata = [3, 1, None, 4, 5, None]\nseries = pd.Series(data)\nmedian = series.median()\n<\/code><\/pre>\n<p>\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u8ba1\u7b97\u51c6\u786e\u6027\uff0c\u907f\u514d\u56e0\u7f3a\u5931\u503c\u5bfc\u81f4\u7684\u9519\u8bef\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u8ba1\u7b97\u4e2d\u4f4d\u6570\u7684\u4e3b\u8981\u65b9\u6cd5\u662f\u4f7f\u7528\u5185\u7f6e\u7684\u7edf\u8ba1\u6a21\u5757statistics\u4e2d\u7684median\u51fd\u6570\u3001\u5229\u7528\u6392\u5e8f\u548c\u7d22 [&hellip;]","protected":false},"author":3,"featured_media":963650,"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\/963644"}],"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=963644"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/963644\/revisions"}],"predecessor-version":[{"id":963652,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/963644\/revisions\/963652"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/963650"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=963644"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=963644"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=963644"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}