{"id":926626,"date":"2024-12-26T15:54:16","date_gmt":"2024-12-26T07:54:16","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/926626.html"},"modified":"2024-12-26T15:54:18","modified_gmt":"2024-12-26T07:54:18","slug":"python%e5%a6%82%e4%bd%95%e5%88%86%e5%9d%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/926626.html","title":{"rendered":"python\u5982\u4f55\u5206\u5757"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25063118\/5d9a68a1-f3d5-4345-9d1c-e016e4dbc357.webp\" alt=\"python\u5982\u4f55\u5206\u5757\" \/><\/p>\n<p><p> <strong>Python\u5206\u5757\u53ef\u4ee5\u901a\u8fc7\u5207\u7247\u64cd\u4f5c\u3001itertools\u6a21\u5757\u4e2d\u7684islice\u51fd\u6570\u3001pandas\u5e93\u4e2d\u7684DataFrame\u65b9\u6cd5\u7b49\u6765\u5b9e\u73b0<\/strong>\u3002\u5176\u4e2d\uff0c<strong>\u5207\u7247\u64cd\u4f5c<\/strong>\u662f\u6700\u57fa\u7840\u7684\u65b9\u5f0f\uff0c\u53ef\u4ee5\u7528\u4e8e\u5b57\u7b26\u4e32\u3001\u5217\u8868\u7b49\u53ef\u8fed\u4ee3\u5bf9\u8c61\uff1b<strong>itertools.islice<\/strong>\u51fd\u6570\u53ef\u4ee5\u66f4\u7075\u6d3b\u5730\u5904\u7406\u8fed\u4ee3\u5668\uff1b\u800c\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c<strong>pandas\u5e93\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u5206\u5757\u65b9\u6cd5<\/strong>\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u7684\u5904\u7406\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\u7684\u5177\u4f53\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528\u5207\u7247\u64cd\u4f5c\u8fdb\u884c\u5206\u5757<\/h3>\n<\/p>\n<p><p>\u5207\u7247\u64cd\u4f5c\u662fPython\u4e2d\u4e00\u4e2a\u57fa\u672c\u800c\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u5b83\u5141\u8bb8\u6211\u4eec\u4ece\u5e8f\u5217\uff08\u5982\u5b57\u7b26\u4e32\u3001\u5217\u8868\u3001\u5143\u7ec4\u7b49\uff09\u4e2d\u63d0\u53d6\u5b50\u5e8f\u5217\u3002\u8fd9\u662f\u5b9e\u73b0\u5206\u5757\u7684\u6700\u7b80\u5355\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>\u5207\u7247\u7684\u57fa\u7840\u7528\u6cd5<\/h4>\n<\/p>\n<p><p>\u5207\u7247\u8bed\u6cd5\u4e3a<code>sequence[start:stop:step]<\/code>\uff0c\u5176\u4e2d<code>start<\/code>\u662f\u8d77\u59cb\u7d22\u5f15\uff0c<code>stop<\/code>\u662f\u7ed3\u675f\u7d22\u5f15\uff0c<code>step<\/code>\u662f\u6b65\u957f\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\uff1a\u5bf9\u5217\u8868\u8fdb\u884c\u5206\u5757<\/p>\n<p>data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]<\/p>\n<p>chunk_size = 3<\/p>\n<p>chunks = [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]<\/p>\n<p>print(chunks)  # \u8f93\u51fa\uff1a[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10]]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u5c06\u4e00\u4e2a\u5217\u8868\u5206\u6210\u591a\u4e2a\u5927\u5c0f\u4e3a3\u7684\u5757\u3002\u901a\u8fc7\u5217\u8868\u63a8\u5bfc\u5f0f\u548c\u5207\u7247\u64cd\u4f5c\uff0c\u53ef\u4ee5\u5feb\u901f\u5b9e\u73b0\u5206\u5757\u3002<\/p>\n<\/p>\n<p><h4>\u4f18\u5316\u5207\u7247\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>\u5728\u5904\u7406\u66f4\u5927\u7684\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u751f\u6210\u5668\u6765\u4f18\u5316\u5185\u5b58\u4f7f\u7528\u3002\u751f\u6210\u5668\u4e0d\u4f1a\u7acb\u5373\u521b\u5efa\u6574\u4e2a\u5217\u8868\uff0c\u800c\u662f\u6309\u9700\u751f\u6210\u5143\u7d20\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def chunked_generator(data, chunk_size):<\/p>\n<p>    for i in range(0, len(data), chunk_size):<\/p>\n<p>        yield data[i:i + chunk_size]<\/p>\n<h2><strong>\u4f7f\u7528\u751f\u6210\u5668\u8fdb\u884c\u5206\u5757<\/strong><\/h2>\n<p>for chunk in chunked_generator(data, 3):<\/p>\n<p>    print(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528itertools.islice\u8fdb\u884c\u5206\u5757<\/h3>\n<\/p>\n<p><p><code>itertools.islice<\/code>\u662f\u5904\u7406\u8fed\u4ee3\u5668\u7684\u4e00\u4e2a\u5f3a\u5927\u5de5\u5177\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u6570\u636e\u6d41\u6216\u5927\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n<p><h4>islice\u7684\u57fa\u672c\u7528\u6cd5<\/h4>\n<\/p>\n<p><p><code>islice<\/code>\u53ef\u4ee5\u4ece\u8fed\u4ee3\u5668\u4e2d\u63d0\u53d6\u5207\u7247\uff0c\u800c\u4e0d\u9700\u8981\u5c06\u6574\u4e2a\u6570\u636e\u96c6\u52a0\u8f7d\u5230\u5185\u5b58\u4e2d\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from itertools import islice<\/p>\n<h2><strong>\u793a\u4f8b\uff1a\u4f7f\u7528islice\u8fdb\u884c\u5206\u5757<\/strong><\/h2>\n<p>data = range(1, 11)  # \u4f7f\u7528range\u751f\u6210\u4e00\u4e2a\u8fed\u4ee3\u5668<\/p>\n<p>chunk_size = 3<\/p>\n<p>def chunked_islice(iterable, chunk_size):<\/p>\n<p>    iterator = iter(iterable)<\/p>\n<p>    for first in iterator:<\/p>\n<p>        yield [first] + list(islice(iterator, chunk_size - 1))<\/p>\n<h2><strong>\u4f7f\u7528islice\u5206\u5757<\/strong><\/h2>\n<p>for chunk in chunked_islice(data, chunk_size):<\/p>\n<p>    print(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u4f18\u52bf\u548c\u5e94\u7528\u573a\u666f<\/h4>\n<\/p>\n<p><p><code>islice<\/code>\u7684\u4f18\u52bf\u5728\u4e8e\u5b83\u652f\u6301\u65e0\u9650\u8fed\u4ee3\u5668\u548c\u5927\u6570\u636e\u96c6\u7684\u5206\u5757\u64cd\u4f5c\uff0c\u9002\u5408\u5185\u5b58\u6709\u9650\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528pandas\u8fdb\u884c\u5206\u5757<\/h3>\n<\/p>\n<p><p>\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0cpandas\u662f\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002<\/p>\n<\/p>\n<p><h4>pandas\u7684DataFrame\u5206\u5757<\/h4>\n<\/p>\n<p><p>pandas\u7684DataFrame\u5bf9\u8c61\u63d0\u4f9b\u4e86\u4e00\u79cd\u7075\u6d3b\u7684\u65b9\u5f0f\u6765\u5904\u7406\u8868\u683c\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>groupby<\/code>\u6216<code>iloc<\/code>\u65b9\u6cd5\u5bf9DataFrame\u8fdb\u884c\u5206\u5757\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u793a\u4f8b\uff1a\u4f7f\u7528pandas\u8fdb\u884c\u5206\u5757<\/strong><\/h2>\n<p>data = {&#39;A&#39;: range(1, 11), &#39;B&#39;: range(11, 21)}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<h2><strong>\u4f7f\u7528iloc\u5206\u5757<\/strong><\/h2>\n<p>chunk_size = 3<\/p>\n<p>chunks = [df.iloc[i:i + chunk_size] for i in range(0, len(df), chunk_size)]<\/p>\n<p>for chunk in chunks:<\/p>\n<p>    print(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>groupby\u65b9\u6cd5<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u67d0\u4e9b\u9700\u8981\u57fa\u4e8e\u7279\u5b9a\u5217\u8fdb\u884c\u5206\u7ec4\u7684\u64cd\u4f5c\uff0c<code>groupby<\/code>\u65b9\u6cd5\u662f\u975e\u5e38\u6709\u6548\u7684\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\uff1a\u4f7f\u7528groupby\u8fdb\u884c\u5206\u5757<\/p>\n<p>df[&#39;C&#39;] = [&#39;X&#39;, &#39;Y&#39;, &#39;X&#39;, &#39;Y&#39;, &#39;X&#39;, &#39;Y&#39;, &#39;X&#39;, &#39;Y&#39;, &#39;X&#39;, &#39;Y&#39;]<\/p>\n<p>grouped = df.groupby(&#39;C&#39;)<\/p>\n<p>for name, group in grouped:<\/p>\n<p>    print(f&quot;Group {name}:&quot;)<\/p>\n<p>    print(group)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u5176\u4ed6\u5206\u5757\u6280\u5de7<\/h3>\n<\/p>\n<p><p>\u9664\u4e86\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u8fd8\u6709\u5176\u4ed6\u4e00\u4e9b\u6280\u5de7\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8fdb\u884c\u5206\u5757\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h4>\u4f7f\u7528NumPy\u8fdb\u884c\u6570\u7ec4\u5206\u5757<\/h4>\n<\/p>\n<p><p>NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u503c\u8ba1\u7b97\u5e93\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u591a\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u793a\u4f8b\uff1a\u4f7f\u7528NumPy\u8fdb\u884c\u5206\u5757<\/strong><\/h2>\n<p>array = np.arange(1, 11)<\/p>\n<p>chunk_size = 3<\/p>\n<p>chunks = np.array_split(array, len(array) \/\/ chunk_size + (len(array) % chunk_size &gt; 0))<\/p>\n<p>for chunk in chunks:<\/p>\n<p>    print(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u81ea\u5b9a\u4e49\u5206\u5757\u51fd\u6570<\/h4>\n<\/p>\n<p><p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u6839\u636e\u7279\u5b9a\u7684\u903b\u8f91\u6765\u8fdb\u884c\u5206\u5757\uff0c\u6b64\u65f6\u53ef\u4ee5\u81ea\u5b9a\u4e49\u51fd\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def custom_chunk(data, condition_func):<\/p>\n<p>    chunk = []<\/p>\n<p>    for item in data:<\/p>\n<p>        if condition_func(item):<\/p>\n<p>            if chunk:<\/p>\n<p>                yield chunk<\/p>\n<p>                chunk = []<\/p>\n<p>        chunk.append(item)<\/p>\n<p>    if chunk:<\/p>\n<p>        yield chunk<\/p>\n<h2><strong>\u793a\u4f8b\uff1a\u81ea\u5b9a\u4e49\u5206\u5757\u51fd\u6570<\/strong><\/h2>\n<p>data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]<\/p>\n<h2><strong>\u6761\u4ef6\u51fd\u6570\uff1a\u5c06\u5076\u6570\u4f5c\u4e3a\u5206\u5757\u7684\u754c\u9650<\/strong><\/h2>\n<p>def is_even(num):<\/p>\n<p>    return num % 2 == 0<\/p>\n<p>for chunk in custom_chunk(data, is_even):<\/p>\n<p>    print(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u5206\u5757\u64cd\u4f5c\u7684\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n<p><p>\u5206\u5757\u64cd\u4f5c\u5728\u5404\u79cd\u5b9e\u9645\u5e94\u7528\u4e2d\u90fd\u975e\u5e38\u91cd\u8981\uff0c\u7279\u522b\u662f\u5728\u4ee5\u4e0b\u573a\u666f\uff1a<\/p>\n<\/p>\n<p><h4>\u6570\u636e\u5904\u7406\u548c\u5206\u6790<\/h4>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\uff0c\u5206\u5757\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8282\u7701\u5185\u5b58\uff0c\u5e76\u63d0\u9ad8\u5904\u7406\u6548\u7387\u3002\u4f8b\u5982\uff0c\u5728\u8bfb\u53d6\u5927\u6587\u4ef6\u6216\u6570\u636e\u5e93\u65f6\uff0c\u53ef\u4ee5\u5c06\u6570\u636e\u5206\u5757\u8bfb\u53d6\uff0c\u9010\u5757\u5904\u7406\u3002<\/p>\n<\/p>\n<p><h4>\u5e76\u884c\u8ba1\u7b97<\/h4>\n<\/p>\n<p><p>\u5206\u5757\u64cd\u4f5c\u53ef\u4ee5\u7528\u4e8e\u5e76\u884c\u8ba1\u7b97\uff0c\u5c06\u6570\u636e\u5206\u6210\u591a\u4e2a\u5757\uff0c\u5206\u522b\u4ea4\u7ed9\u591a\u4e2a\u7ebf\u7a0b\u6216\u8fdb\u7a0b\u5904\u7406\uff0c\u4ee5\u52a0\u901f\u8ba1\u7b97\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n<p><h4>\u6d41\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u5728\u5b9e\u65f6\u6570\u636e\u6d41\u7684\u5904\u7406\u4e2d\uff0c\u5206\u5757\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5c06\u6570\u636e\u6d41\u5206\u6210\u5c0f\u5757\u8fdb\u884c\u9010\u6b65\u5904\u7406\uff0c\u4ece\u800c\u66f4\u597d\u5730\u7ba1\u7406\u548c\u54cd\u5e94\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>Python\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u5b9e\u73b0\u5206\u5757\u64cd\u4f5c\uff0c\u4ece\u57fa\u672c\u7684\u5207\u7247\u64cd\u4f5c\u5230\u9ad8\u7ea7\u7684pandas\u5e93\uff0c\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u7279\u5b9a\u7684\u5e94\u7528\u573a\u666f\u548c\u4f18\u52bf\u3002\u9009\u62e9\u5408\u9002\u7684\u5206\u5757\u65b9\u6cd5\u53ef\u4ee5\u6781\u5927\u5730\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u7075\u6d3b\u6027\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u9700\u8981\u6839\u636e\u6570\u636e\u7684\u89c4\u6a21\u548c\u5904\u7406\u7684\u9700\u6c42\uff0c\u9009\u62e9\u6700\u5408\u9002\u7684\u65b9\u6cd5\u6765\u5b9e\u73b0\u5206\u5757\u3002\u65e0\u8bba\u662f\u5904\u7406\u5c0f\u578b\u6570\u636e\u96c6\u8fd8\u662f\u5927\u578b\u6570\u636e\u6d41\uff0c\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u5206\u5757\u6280\u672f\u90fd\u80fd\u5e26\u6765\u663e\u8457\u7684\u6548\u7387\u63d0\u5347\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5b9e\u73b0\u6570\u636e\u5206\u5757\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u6570\u636e\u5206\u5757\u901a\u5e38\u53ef\u4ee5\u901a\u8fc7\u5217\u8868\u5207\u7247\u3001\u751f\u6210\u5668\u6216\u4f7f\u7528NumPy\u7b49\u5e93\u6765\u5b9e\u73b0\u3002\u5217\u8868\u5207\u7247\u65b9\u6cd5\u76f8\u5bf9\u7b80\u5355\uff0c\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u8d77\u59cb\u548c\u7ed3\u675f\u7d22\u5f15\u6765\u83b7\u53d6\u5b50\u5217\u8868\u3002\u751f\u6210\u5668\u5219\u53ef\u4ee5\u63d0\u4f9b\u66f4\u7075\u6d3b\u7684\u5904\u7406\u65b9\u5f0f\uff0c\u5141\u8bb8\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\u8282\u7701\u5185\u5b58\u3002NumPy\u5e93\u5219\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u7ec4\u64cd\u4f5c\u529f\u80fd\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5bf9\u591a\u7ef4\u6570\u7ec4\u8fdb\u884c\u5206\u5757\u5904\u7406\u3002<\/p>\n<p><strong>\u5728\u5904\u7406\u5927\u6570\u636e\u65f6\uff0c\u5206\u5757\u6709\u4ec0\u4e48\u4f18\u52bf\uff1f<\/strong><br \/>\u4f7f\u7528\u5206\u5757\u5904\u7406\u5927\u6570\u636e\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6548\u7387\u548c\u6027\u80fd\u3002\u901a\u8fc7\u5c06\u6570\u636e\u5206\u4e3a\u8f83\u5c0f\u7684\u90e8\u5206\uff0c\u53ef\u4ee5\u51cf\u5c11\u5185\u5b58\u5360\u7528\uff0c\u907f\u514d\u4e00\u6b21\u6027\u52a0\u8f7d\u6574\u4e2a\u6570\u636e\u96c6\u3002\u6b64\u5916\uff0c\u5728\u5206\u5757\u5904\u7406\u65f6\uff0c\u53ef\u4ee5\u5e76\u884c\u5904\u7406\u591a\u4e2a\u5757\uff0c\u4ece\u800c\u52a0\u901f\u8ba1\u7b97\u8fc7\u7a0b\u3002\u8fd9\u79cd\u65b9\u6cd5\u7279\u522b\u9002\u5408\u4e8e\u6570\u636e\u5206\u6790\u3001<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u7b49\u9886\u57df\u3002<\/p>\n<p><strong>\u6709\u54ea\u4e9b\u5e38\u7528\u7684Python\u5e93\u53ef\u4ee5\u5e2e\u52a9\u5b9e\u73b0\u5206\u5757\u5904\u7406\uff1f<\/strong><br \/>Python\u4e2d\u6709\u591a\u79cd\u5e93\u53ef\u4ee5\u5e2e\u52a9\u5b9e\u73b0\u5206\u5757\u5904\u7406\u3002Pandas\u662f\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u6570\u636e\u5206\u6790\u5e93\uff0c\u63d0\u4f9b\u4e86DataFrame\u7684\u5207\u7247\u548c\u5206\u7ec4\u529f\u80fd\uff0c\u65b9\u4fbf\u7528\u6237\u8fdb\u884c\u5206\u5757\u64cd\u4f5c\u3002Dask\u662f\u4e00\u4e2a\u9488\u5bf9\u5927\u6570\u636e\u7684\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u652f\u6301\u5c06\u6570\u636e\u96c6\u5206\u5757\u5e76\u5728\u591a\u4e2a\u7ebf\u7a0b\u6216\u8fdb\u7a0b\u4e2d\u5904\u7406\u3002\u6b64\u5916\uff0cNumPy\u548cSciPy\u4e5f\u63d0\u4f9b\u4e86\u5bf9\u6570\u7ec4\u8fdb\u884c\u5206\u5757\u548c\u64cd\u4f5c\u7684\u529f\u80fd\uff0c\u9002\u5408\u6570\u503c\u8ba1\u7b97\u548c\u79d1\u5b66\u7814\u7a76\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5206\u5757\u53ef\u4ee5\u901a\u8fc7\u5207\u7247\u64cd\u4f5c\u3001itertools\u6a21\u5757\u4e2d\u7684islice\u51fd\u6570\u3001pandas\u5e93\u4e2d\u7684DataFra [&hellip;]","protected":false},"author":3,"featured_media":926633,"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\/926626"}],"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=926626"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/926626\/revisions"}],"predecessor-version":[{"id":926636,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/926626\/revisions\/926636"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/926633"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=926626"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=926626"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=926626"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}