{"id":1019487,"date":"2024-12-27T13:00:49","date_gmt":"2024-12-27T05:00:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1019487.html"},"modified":"2024-12-27T13:00:54","modified_gmt":"2024-12-27T05:00:54","slug":"%e5%a6%82%e4%bd%95%e6%89%93%e5%bc%80python%e6%95%b0%e6%8d%ae%e5%a4%aa","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1019487.html","title":{"rendered":"\u5982\u4f55\u6253\u5f00python\u6570\u636e\u592a"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25161942\/ec446e31-d690-4e7e-8bbf-be7d86e1aa88.webp\" alt=\"\u5982\u4f55\u6253\u5f00python\u6570\u636e\u592a\" \/><\/p>\n<p><p> \u8981\u6253\u5f00Python\u6570\u636e\u6587\u4ef6\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u6765\u5904\u7406\u548c\u5206\u6790\u8fd9\u4e9b\u6570\u636e\u6587\u4ef6\u3002<strong>\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684Python\u5e93\u3001\u7b2c\u4e09\u65b9\u5e93\u5982pandas\u3001csv\u3001json\u7b49\u6765\u8bfb\u53d6\u548c\u5904\u7406\u6570\u636e\u6587\u4ef6\u3001\u9009\u62e9\u9002\u5f53\u7684\u6587\u4ef6\u8bfb\u53d6\u65b9\u6cd5\u662f\u9ad8\u6548\u5904\u7406\u6570\u636e\u7684\u5173\u952e\u3001\u638c\u63e1\u4e0d\u540c\u683c\u5f0f\u6587\u4ef6\u7684\u8bfb\u53d6\u65b9\u5f0f\u53ef\u4ee5\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002<\/strong>\u5728\u8fd9\u4e9b\u9009\u9879\u4e2d\uff0cpandas\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u5c24\u5176\u9002\u5408\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u3002\u901a\u8fc7pandas\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u8bfb\u53d6CSV\u3001Excel\u3001SQL\u6570\u636e\u5e93\u7b49\u591a\u79cd\u683c\u5f0f\u7684\u6570\u636e\uff0c\u5e76\u5bf9\u5176\u8fdb\u884c\u5206\u6790\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><p><strong>pandas\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u8be6\u7ec6\u63cf\u8ff0<\/strong>\uff1aCSV\uff08Comma Separated Values\uff09\u6587\u4ef6\u662f\u6700\u5e38\u89c1\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u4e4b\u4e00\u3002\u8981\u4f7f\u7528pandas\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u4f60\u9700\u8981\u9996\u5148\u5b89\u88c5pandas\u5e93\uff0c\u7136\u540e\u4f7f\u7528<code>pandas.read_csv()<\/code>\u51fd\u6570\u3002\u8be5\u51fd\u6570\u4e0d\u4ec5\u53ef\u4ee5\u8bfb\u53d6\u6587\u4ef6\uff0c\u8fd8\u80fd\u81ea\u52a8\u8bc6\u522b\u6570\u636e\u7c7b\u578b\u3001\u8bbe\u7f6e\u7d22\u5f15\u5217\u4ee5\u53ca\u5904\u7406\u7f3a\u5931\u503c\u7b49\u3002\u6b64\u5916\uff0cpandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u53c2\u6570\u9009\u9879\uff0c\u4f7f\u8bfb\u53d6\u64cd\u4f5c\u66f4\u52a0\u7075\u6d3b\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528<code>delimiter<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u5206\u9694\u7b26\uff0c\u4ee5\u9002\u5e94\u4e0d\u540c\u683c\u5f0f\u7684CSV\u6587\u4ef6\uff1b\u901a\u8fc7<code>dtype<\/code>\u53c2\u6570\uff0c\u53ef\u4ee5\u8bbe\u5b9a\u5217\u7684\u6570\u636e\u7c7b\u578b\uff1b\u800c<code>na_values<\/code>\u53c2\u6570\u5219\u5141\u8bb8\u4f60\u5b9a\u4e49\u7f3a\u5931\u503c\u7684\u6807\u8bc6\u7b26\u3002<\/p>\n<\/p>\n<p><p>\u4ee5\u4e0b\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u5904\u7406\u4e0d\u540c\u683c\u5f0f\u7684\u6570\u636e\u6587\u4ef6\u4ee5\u53ca\u8fd9\u4e9b\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528Pandas\u8bfb\u53d6\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>pandas\u662fPython\u4e2d\u6700\u4e3a\u6d41\u884c\u7684\u6570\u636e\u5206\u6790\u5e93\u4e4b\u4e00\uff0c\u63d0\u4f9b\u4e86\u5f3a\u5927\u800c\u4fbf\u6377\u7684\u63a5\u53e3\u6765\u8bfb\u53d6\u591a\u79cd\u683c\u5f0f\u7684\u6570\u636e\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><h4>1.1 \u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>CSV\u6587\u4ef6\u662f\u4e00\u79cd\u7b80\u5355\u800c\u5e7f\u6cdb\u4f7f\u7528\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u3002\u8981\u8bfb\u53d6CSV\u6587\u4ef6\uff0cpandas\u63d0\u4f9b\u4e86<code>read_csv<\/code>\u51fd\u6570\u3002\u8fd9\u4e2a\u51fd\u6570\u975e\u5e38\u7075\u6d3b\uff0c\u53ef\u4ee5\u5904\u7406\u5206\u9694\u7b26\u3001\u5934\u6587\u4ef6\u3001\u7d22\u5f15\u5217\u3001\u7f3a\u5931\u503c\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n<p>df = pd.read_csv(&#39;data.csv&#39;)<\/p>\n<h2><strong>\u67e5\u770b\u6570\u636e<\/strong><\/h2>\n<p>print(df.head())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528<code>pd.read_csv()<\/code>\u8bfb\u53d6\u4e86\u4e00\u4e2a\u540d\u4e3a<code>data.csv<\/code>\u7684\u6587\u4ef6\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u5728\u4e00\u4e2aDataFrame\u5bf9\u8c61\u4e2d\u3002<code>DataFrame<\/code>\u662fpandas\u7684\u6838\u5fc3\u6570\u636e\u7ed3\u6784\uff0c\u53ef\u4ee5\u770b\u4f5c\u662f\u4e00\u4e2a\u589e\u5f3a\u7248\u7684\u7535\u5b50\u8868\u683c\u3002<\/p>\n<\/p>\n<p><h4>1.2 \u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>Excel\u6587\u4ef6\u5728\u8bb8\u591a\u884c\u4e1a\u4e2d\u5e7f\u6cdb\u5e94\u7528\u3002pandas\u63d0\u4f9b\u4e86<code>read_excel<\/code>\u51fd\u6570\u6765\u8bfb\u53d6Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n<p>df = pd.read_excel(&#39;data.xlsx&#39;, sheet_name=&#39;Sheet1&#39;)<\/p>\n<h2><strong>\u67e5\u770b\u6570\u636e<\/strong><\/h2>\n<p>print(df.head())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><code>read_excel<\/code>\u51fd\u6570\u5141\u8bb8\u4f60\u6307\u5b9a\u8981\u8bfb\u53d6\u7684\u5de5\u4f5c\u8868\uff0c\u5e76\u652f\u6301\u8bfb\u53d6\u591a\u5f20\u5de5\u4f5c\u8868\u7684\u6570\u636e\u3002\u901a\u8fc7<code>sheet_name<\/code>\u53c2\u6570\uff0c\u4f60\u53ef\u4ee5\u6307\u5b9a\u5de5\u4f5c\u8868\u540d\u79f0\u6216\u7d22\u5f15\u3002<\/p>\n<\/p>\n<p><h4>1.3 \u8bfb\u53d6JSON\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>JSON\u662f\u4e00\u79cd\u8f7b\u91cf\u7ea7\u7684\u6570\u636e\u4ea4\u6362\u683c\u5f0f\uff0c\u6613\u4e8e\u4eba\u548c\u673a\u5668\u9605\u8bfb\u3002pandas\u7684<code>read_json<\/code>\u51fd\u6570\u53ef\u4ee5\u76f4\u63a5\u8bfb\u53d6JSON\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u8bfb\u53d6JSON\u6587\u4ef6<\/strong><\/h2>\n<p>df = pd.read_json(&#39;data.json&#39;)<\/p>\n<h2><strong>\u67e5\u770b\u6570\u636e<\/strong><\/h2>\n<p>print(df.head())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>JSON\u6570\u636e\u901a\u5e38\u4ee5\u5d4c\u5957\u7ed3\u6784\u5b58\u50a8\uff0c<code>read_json<\/code>\u51fd\u6570\u80fd\u591f\u81ea\u52a8\u89e3\u6790\u8fd9\u4e9b\u5d4c\u5957\u7ed3\u6784\u4e3aDataFrame\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528\u5176\u4ed6Python\u5e93\u8bfb\u53d6\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>\u9664\u4e86pandas\uff0cPython\u8fd8\u6709\u5176\u4ed6\u4e00\u4e9b\u5e93\u53ef\u4ee5\u7528\u6765\u5904\u7406\u6570\u636e\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><h4>2.1 \u4f7f\u7528csv\u5e93\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>Python\u5185\u7f6e\u7684csv\u5e93\u63d0\u4f9b\u4e86\u57fa\u672c\u7684CSV\u8bfb\u53d6\u529f\u80fd\u3002\u5bf9\u4e8e\u7b80\u5355\u7684CSV\u6587\u4ef6\uff0ccsv\u5e93\u662f\u4e00\u4e2a\u8f7b\u91cf\u7ea7\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import csv<\/p>\n<h2><strong>\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n<p>with open(&#39;data.csv&#39;, mode=&#39;r&#39;) as file:<\/p>\n<p>    reader = csv.reader(file)<\/p>\n<p>    for row in reader:<\/p>\n<p>        print(row)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5c3d\u7ba1csv\u5e93\u529f\u80fd\u4e0d\u5982pandas\u4e30\u5bcc\uff0c\u4f46\u5728\u5904\u7406\u5c0f\u578b\u3001\u7b80\u5355CSV\u6587\u4ef6\u65f6\uff0c\u5b83\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n<p><h4>2.2 \u4f7f\u7528openpyxl\u5e93\u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>openpyxl\u662f\u4e00\u4e2a\u4e13\u95e8\u7528\u4e8e\u5904\u7406Excel\u6587\u4ef6\u7684\u7b2c\u4e09\u65b9\u5e93\uff0c\u652f\u6301\u8bfb\u53d6\u548c\u5199\u5165Excel 2010\u683c\u5f0f\uff08.xlsx\u6587\u4ef6\uff09\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from openpyxl import load_workbook<\/p>\n<h2><strong>\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n<p>workbook = load_workbook(filename=&#39;data.xlsx&#39;)<\/p>\n<p>sheet = workbook.active<\/p>\n<h2><strong>\u6253\u5370\u6bcf\u4e00\u884c\u7684\u6570\u636e<\/strong><\/h2>\n<p>for row in sheet.iter_rows(values_only=True):<\/p>\n<p>    print(row)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>openpyxl\u5e93\u63d0\u4f9b\u4e86\u5bf9Excel\u6587\u4ef6\u7684\u66f4\u7ec6\u7c92\u5ea6\u63a7\u5236\uff0c\u9002\u5408\u9700\u8981\u5bf9Excel\u6587\u4ef6\u8fdb\u884c\u590d\u6742\u64cd\u4f5c\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u6570\u636e\u6e05\u6d17\u4e0e\u9884\u5904\u7406<\/h3>\n<\/p>\n<p><p>\u8bfb\u53d6\u6570\u636e\u6587\u4ef6\u540e\uff0c\u4e0b\u4e00\u6b65\u901a\u5e38\u662f\u5bf9\u6570\u636e\u8fdb\u884c\u6e05\u6d17\u548c\u9884\u5904\u7406\u3002\u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u5206\u6790\u4e2d\u975e\u5e38\u91cd\u8981\u7684\u4e00\u6b65\uff0c\u53ef\u4ee5\u63d0\u9ad8\u6570\u636e\u7684\u8d28\u91cf\u548c\u5206\u6790\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n<p><h4>3.1 \u5904\u7406\u7f3a\u5931\u503c<\/h4>\n<\/p>\n<p><p>\u7f3a\u5931\u503c\u662f\u6570\u636e\u5206\u6790\u4e2d\u5e38\u89c1\u7684\u95ee\u9898\uff0c\u5904\u7406\u7f3a\u5931\u503c\u7684\u65b9\u6cd5\u5305\u62ec\u5220\u9664\u7f3a\u5931\u503c\u3001\u586b\u5145\u7f3a\u5931\u503c\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5220\u9664\u7f3a\u5931\u503c<\/p>\n<p>df.dropna(inplace=True)<\/p>\n<h2><strong>\u586b\u5145\u7f3a\u5931\u503c<\/strong><\/h2>\n<p>df.fillna(value=0, inplace=True)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u9009\u62e9\u4f55\u79cd\u65b9\u5f0f\u5904\u7406\u7f3a\u5931\u503c\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u5e94\u7528\u573a\u666f\u548c\u6570\u636e\u7279\u5f81\u3002<\/p>\n<\/p>\n<p><h4>3.2 \u6570\u636e\u7c7b\u578b\u8f6c\u6362<\/h4>\n<\/p>\n<p><p>\u6709\u65f6\u8bfb\u53d6\u7684\u6570\u636e\u7c7b\u578b\u53ef\u80fd\u4e0d\u7b26\u5408\u5206\u6790\u7684\u9700\u6c42\uff0c\u56e0\u6b64\u9700\u8981\u5bf9\u6570\u636e\u7c7b\u578b\u8fdb\u884c\u8f6c\u6362\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5c06\u5217\u8f6c\u6362\u4e3a\u6574\u6570\u7c7b\u578b<\/p>\n<p>df[&#39;column_name&#39;] = df[&#39;column_name&#39;].astype(int)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u6570\u636e\u7c7b\u578b\u7684\u51c6\u786e\u6027\u5bf9\u4e8e\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u548c\u5efa\u6a21\u81f3\u5173\u91cd\u8981\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u6570\u636e\u5206\u6790\u4e0e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n<p><p>\u6570\u636e\u5206\u6790\u4e0e\u53ef\u89c6\u5316\u662f\u6570\u636e\u79d1\u5b66\u4e2d\u4e0d\u53ef\u6216\u7f3a\u7684\u7ec4\u6210\u90e8\u5206\u3002\u901a\u8fc7\u6570\u636e\u5206\u6790\uff0c\u6211\u4eec\u53ef\u4ee5\u4ece\u6570\u636e\u4e2d\u63d0\u53d6\u51fa\u6709\u7528\u7684\u4fe1\u606f\uff0c\u800c\u6570\u636e\u53ef\u89c6\u5316\u5219\u5e2e\u52a9\u6211\u4eec\u4ee5\u76f4\u89c2\u7684\u65b9\u5f0f\u5c55\u793a\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h4>4.1 \u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u5206\u6790<\/h4>\n<\/p>\n<p><p>pandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5206\u6790\u529f\u80fd\uff0c\u4f8b\u5982\u63cf\u8ff0\u6027\u7edf\u8ba1\u3001\u6570\u636e\u5206\u7ec4\u3001\u6570\u636e\u5408\u5e76\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u63cf\u8ff0\u6027\u7edf\u8ba1<\/p>\n<p>print(df.describe())<\/p>\n<h2><strong>\u6570\u636e\u5206\u7ec4<\/strong><\/h2>\n<p>grouped = df.groupby(&#39;column_name&#39;).mean()<\/p>\n<p>print(grouped)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e9b\u529f\u80fd\u4f7f\u5f97pandas\u6210\u4e3a\u6570\u636e\u5206\u6790\u7684\u5f3a\u5927\u5de5\u5177\u3002<\/p>\n<\/p>\n<p><h4>4.2 \u4f7f\u7528Matplotlib\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n<p><p>Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u80fd\u591f\u751f\u6210\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<h2><strong>\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n<p>df[&#39;column_name&#39;].plot(kind=&#39;line&#39;)<\/p>\n<p>plt.title(&#39;Line Plot&#39;)<\/p>\n<p>plt.xlabel(&#39;X-axis&#39;)<\/p>\n<p>plt.ylabel(&#39;Y-axis&#39;)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7Matplotlib\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u7ed8\u5236\u5404\u79cd\u7edf\u8ba1\u56fe\u8868\uff0c\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u6570\u636e\u5b58\u50a8\u4e0e\u5bfc\u51fa<\/h3>\n<\/p>\n<p><p>\u5904\u7406\u5b8c\u6570\u636e\u540e\uff0c\u901a\u5e38\u9700\u8981\u5c06\u6570\u636e\u5b58\u50a8\u6216\u5bfc\u51fa\u4e3a\u7279\u5b9a\u7684\u6587\u4ef6\u683c\u5f0f\uff0c\u4ee5\u4f9b\u540e\u7eed\u4f7f\u7528\u6216\u5206\u4eab\u3002<\/p>\n<\/p>\n<p><h4>5.1 \u4f7f\u7528Pandas\u5bfc\u51faCSV\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>pandas\u63d0\u4f9b\u4e86<code>to_csv<\/code>\u51fd\u6570\uff0c\u7528\u4e8e\u5c06DataFrame\u5bfc\u51fa\u4e3aCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5bfc\u51fa\u4e3aCSV\u6587\u4ef6<\/p>\n<p>df.to_csv(&#39;output.csv&#39;, index=False)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u51fd\u6570\u652f\u6301\u591a\u79cd\u53c2\u6570\u8bbe\u7f6e\uff0c\u53ef\u4ee5\u63a7\u5236\u8f93\u51fa\u6587\u4ef6\u7684\u683c\u5f0f\u548c\u5185\u5bb9\u3002<\/p>\n<\/p>\n<p><h4>5.2 \u4f7f\u7528Pandas\u5bfc\u51faExcel\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>\u7c7b\u4f3c\u5730\uff0cpandas\u7684<code>to_excel<\/code>\u51fd\u6570\u7528\u4e8e\u5c06DataFrame\u5bfc\u51fa\u4e3aExcel\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5bfc\u51fa\u4e3aExcel\u6587\u4ef6<\/p>\n<p>df.to_excel(&#39;output.xlsx&#39;, index=False)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7<code>to_excel<\/code>\uff0c\u53ef\u4ee5\u6307\u5b9a\u5de5\u4f5c\u8868\u540d\u79f0\u3001\u5217\u5bbd\u3001\u5355\u5143\u683c\u683c\u5f0f\u7b49\u3002<\/p>\n<\/p>\n<p><h3>\u516d\u3001\u6570\u636e\u5904\u7406\u4e2d\u7684\u6ce8\u610f\u4e8b\u9879<\/h3>\n<\/p>\n<p><p>\u5728\u6570\u636e\u5904\u7406\u8fc7\u7a0b\u4e2d\uff0c\u6709\u4e00\u4e9b\u5e38\u89c1\u7684\u95ee\u9898\u9700\u8981\u6ce8\u610f\uff0c\u4ee5\u786e\u4fdd\u6570\u636e\u5206\u6790\u7684\u51c6\u786e\u6027\u548c\u6548\u7387\u3002<\/p>\n<\/p>\n<p><h4>6.1 \u6570\u636e\u51c6\u786e\u6027<\/h4>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u548c\u5904\u7406\u6570\u636e\u65f6\uff0c\u786e\u4fdd\u6570\u636e\u7684\u51c6\u786e\u6027\u975e\u5e38\u91cd\u8981\u3002\u9700\u8981\u4ed4\u7ec6\u68c0\u67e5\u6570\u636e\u6e90\uff0c\u9a8c\u8bc1\u6570\u636e\u7684\u4e00\u81f4\u6027\u548c\u5b8c\u6574\u6027\u3002<\/p>\n<\/p>\n<p><h4>6.2 \u6570\u636e\u5b89\u5168\u6027<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u5b89\u5168\u6027\u4e5f\u662f\u4e00\u4e2a\u9700\u8981\u5173\u6ce8\u7684\u95ee\u9898\u3002\u5728\u5904\u7406\u654f\u611f\u6570\u636e\u65f6\uff0c\u786e\u4fdd\u6570\u636e\u7684\u5b89\u5168\u5b58\u50a8\u548c\u4f20\u8f93\uff0c\u907f\u514d\u6570\u636e\u6cc4\u9732\u548c\u672a\u6388\u6743\u8bbf\u95ee\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u51e0\u79cd\u65b9\u6cd5\u548c\u6280\u5de7\uff0c\u4f60\u53ef\u4ee5\u9ad8\u6548\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u5206\u6790Python\u6570\u636e\u6587\u4ef6\uff0c\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002\u638c\u63e1\u8fd9\u4e9b\u6280\u80fd\u5c06\u6781\u5927\u5730\u589e\u5f3a\u4f60\u7684\u6570\u636e\u5206\u6790\u80fd\u529b\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u9009\u62e9\u5408\u9002\u7684Python\u6570\u636e\u5206\u6790\u5de5\u5177\uff1f<\/strong><br \/>\u5728\u9009\u62e9Python\u6570\u636e\u5206\u6790\u5de5\u5177\u65f6\uff0c\u8003\u8651\u6570\u636e\u7684\u7c7b\u578b\u548c\u5206\u6790\u9700\u6c42\u81f3\u5173\u91cd\u8981\u3002\u5e38\u7528\u7684\u5de5\u5177\u5305\u62ecPandas\u3001NumPy\u548cMatplotlib\u3002Pandas\u9002\u5408\u5904\u7406\u8868\u683c\u6570\u636e\uff0cNumPy\u5219\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\uff0c\u800cMatplotlib\u548cSeaborn\u5219\u975e\u5e38\u9002\u5408\u6570\u636e\u53ef\u89c6\u5316\u3002\u6b64\u5916\uff0cJupyter Notebook\u662f\u8fdb\u884c\u4ea4\u4e92\u5f0f\u5206\u6790\u7684\u7406\u60f3\u9009\u62e9\uff0c\u53ef\u4ee5\u66f4\u65b9\u4fbf\u5730\u8fdb\u884c\u4ee3\u7801\u548c\u7ed3\u679c\u7684\u5c55\u793a\u3002<\/p>\n<p><strong>Python\u4e2d\u5e38\u89c1\u7684\u6570\u636e\u683c\u5f0f\u6709\u54ea\u4e9b\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u5e38\u7528\u7684\u6570\u636e\u683c\u5f0f\u5305\u62ecCSV\u3001JSON\u3001Excel\u548cSQL\u6570\u636e\u5e93\u3002CSV\u6587\u4ef6\u9002\u5408\u5904\u7406\u7b80\u5355\u7684\u8868\u683c\u6570\u636e\uff0cJSON\u683c\u5f0f\u5219\u7528\u4e8e\u5b58\u50a8\u7ed3\u6784\u5316\u6570\u636e\uff0cExcel\u6587\u4ef6\u652f\u6301\u590d\u6742\u7684\u8868\u683c\u64cd\u4f5c\uff0c\u800cSQL\u6570\u636e\u5e93\u5219\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e\u5b58\u50a8\u548c\u67e5\u8be2\u3002\u4e86\u89e3\u4e0d\u540c\u6570\u636e\u683c\u5f0f\u7684\u7279\u70b9\u53ef\u4ee5\u5e2e\u52a9\u9009\u62e9\u6700\u5408\u9002\u7684\u65b9\u6cd5\u6765\u6253\u5f00\u548c\u5904\u7406\u6570\u636e\u3002<\/p>\n<p><strong>\u5982\u4f55\u6709\u6548\u5730\u6e05\u6d17\u548c\u5904\u7406Python\u4e2d\u7684\u6570\u636e\uff1f<\/strong><br \/>\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u6570\u636e\u6e05\u6d17\u662f\u4e00\u4e2a\u91cd\u8981\u7684\u6b65\u9aa4\u3002\u4f7f\u7528Pandas\u5e93\u4e2d\u7684<code>dropna()<\/code>\u548c<code>fillna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5904\u7406\u7f3a\u5931\u503c\uff0c<code>astype()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u7528\u6765\u8f6c\u6362\u6570\u636e\u7c7b\u578b\u3002\u6b64\u5916\uff0c\u4f7f\u7528<code>apply()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u81ea\u5b9a\u4e49\u6e05\u6d17\u64cd\u4f5c\u3002\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\u548c\u51c6\u786e\u6027\u662f\u5206\u6790\u7684\u57fa\u7840\uff0c\u56e0\u6b64\u5408\u7406\u5229\u7528\u8fd9\u4e9b\u5de5\u5177\u5c06\u5927\u5927\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u8981\u6253\u5f00Python\u6570\u636e\u6587\u4ef6\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u6765\u5904\u7406\u548c\u5206\u6790\u8fd9\u4e9b\u6570\u636e\u6587\u4ef6\u3002\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684Python\u5e93\u3001\u7b2c\u4e09\u65b9\u5e93 [&hellip;]","protected":false},"author":3,"featured_media":1019497,"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\/1019487"}],"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=1019487"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1019487\/revisions"}],"predecessor-version":[{"id":1019499,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1019487\/revisions\/1019499"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1019497"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1019487"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1019487"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1019487"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}