{"id":1170384,"date":"2025-01-15T16:21:55","date_gmt":"2025-01-15T08:21:55","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1170384.html"},"modified":"2025-01-15T16:21:57","modified_gmt":"2025-01-15T08:21:57","slug":"%e6%b1%87%e6%80%bb%e5%b9%b4%e5%b7%a5%e8%b5%84%e5%a6%82%e4%bd%95%e7%94%a8python","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1170384.html","title":{"rendered":"\u6c47\u603b\u5e74\u5de5\u8d44\u5982\u4f55\u7528python"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/26071112\/b7269d28-1ff9-4bb5-9d47-cc8bd23f2106.webp\" alt=\"\u6c47\u603b\u5e74\u5de5\u8d44\u5982\u4f55\u7528python\" \/><\/p>\n<p><p> \u4e00\u3001\u6c47\u603b\u5e74\u5de5\u8d44\u5982\u4f55\u7528Python<\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u3001\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u5de5\u8d44\u6570\u636e\u3001\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u8ba1\u7b97<\/strong>\u3002\u5176\u4e2d\uff0c<strong>\u4f7f\u7528Pandas\u5e93<\/strong>\u662f\u6700\u4e3a\u63a8\u8350\u7684\u65b9\u6cd5\u3002Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u80fd\u591f\u7b80\u5316\u6570\u636e\u64cd\u4f5c\u8fc7\u7a0b\u3002\u901a\u8fc7Pandas\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u5206\u6790\u5de5\u8d44\u6570\u636e\uff0c\u5b9e\u73b0\u5e74\u5de5\u8d44\u7684\u6c47\u603b\u3002<\/p>\n<\/p>\n<p><p>\u4f7f\u7528Pandas\u5e93\u8fdb\u884c\u5e74\u5de5\u8d44\u6c47\u603b\uff0c\u53ea\u9700\u51e0\u884c\u4ee3\u7801\u5373\u53ef\u5b8c\u6210\u3002\u9996\u5148\uff0c\u5bfc\u5165Pandas\u5e93\uff0c\u5e76\u8bfb\u53d6\u5305\u542b\u5de5\u8d44\u6570\u636e\u7684\u6587\u4ef6\uff08\u5982CSV\u6587\u4ef6\uff09\u3002\u7136\u540e\uff0c\u901a\u8fc7Pandas\u7684<code>DataFrame<\/code>\u5bf9\u8c61\u8fdb\u884c\u6570\u636e\u64cd\u4f5c\uff0c\u5305\u62ec\u6570\u636e\u7b5b\u9009\u3001\u5206\u7ec4\u3001\u805a\u5408\u7b49\u3002\u6700\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7Pandas\u63d0\u4f9b\u7684\u5404\u79cd\u65b9\u6cd5\u548c\u5c5e\u6027\uff0c\u5bf9\u6c47\u603b\u7ed3\u679c\u8fdb\u884c\u8fdb\u4e00\u6b65\u5904\u7406\u548c\u5206\u6790\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;salaries.csv&#39;)<\/p>\n<h2><strong>\u6309\u5e74\u4efd\u6c47\u603b\u5de5\u8d44\u6570\u636e<\/strong><\/h2>\n<p>annual_salary = df.groupby(&#39;Year&#39;)[&#39;Salary&#39;].sum()<\/p>\n<p>print(annual_salary)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e8c\u3001\u4f7f\u7528Pandas\u5e93<\/p>\n<\/p>\n<p><p>Pandas\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u5206\u6790\u5e93\u4e4b\u4e00\u3002\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u80fd\u591f\u7b80\u5316\u6570\u636e\u64cd\u4f5c\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5c06\u5de5\u8d44\u6570\u636e\u8bfb\u53d6\u5230Pandas\u7684<code>DataFrame<\/code>\u5bf9\u8c61\u4e2d\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3a<code>salaries.csv<\/code>\u7684CSV\u6587\u4ef6\uff0c\u5305\u542b\u5458\u5de5\u7684\u5de5\u8d44\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>pd.read_csv<\/code>\u51fd\u6570\u8bfb\u53d6\u8be5\u6587\u4ef6\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;salaries.csv&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u6570\u636e\u7b5b\u9009<\/h3>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u6570\u636e\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u7b5b\u9009\uff0c\u4ee5\u4fbf\u53ea\u4fdd\u7559\u9700\u8981\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u7b5b\u9009\u51fa\u7279\u5b9a\u5e74\u4efd\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7b5b\u9009\u51fa2022\u5e74\u7684\u5de5\u8d44\u6570\u636e<\/p>\n<p>df_2022 = df[df[&#39;Year&#39;] == 2022]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3\u3001\u6309\u5e74\u4efd\u6c47\u603b\u5de5\u8d44\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>groupby<\/code>\u65b9\u6cd5\u6309\u5e74\u4efd\u6c47\u603b\u5de5\u8d44\u6570\u636e\u3002<code>groupby<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5c06\u6570\u636e\u6309\u6307\u5b9a\u5217\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u5bf9\u6bcf\u4e2a\u5206\u7ec4\u5e94\u7528\u805a\u5408\u51fd\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6309\u5e74\u4efd\u6c47\u603b\u5de5\u8d44\u6570\u636e<\/p>\n<p>annual_salary = df.groupby(&#39;Year&#39;)[&#39;Salary&#39;].sum()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>4\u3001\u5904\u7406\u6c47\u603b\u7ed3\u679c<\/h3>\n<\/p>\n<p><p>\u6c47\u603b\u7ed3\u679c\u662f\u4e00\u4e2a<code>Series<\/code>\u5bf9\u8c61\uff0c\u5305\u542b\u6bcf\u4e2a\u5e74\u4efd\u7684\u603b\u5de5\u8d44\u3002\u6211\u4eec\u53ef\u4ee5\u5bf9\u6c47\u603b\u7ed3\u679c\u8fdb\u884c\u8fdb\u4e00\u6b65\u5904\u7406\u548c\u5206\u6790\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u6c47\u603b\u7ed3\u679c\u4fdd\u5b58\u5230\u65b0\u7684CSV\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5c06\u6c47\u603b\u7ed3\u679c\u4fdd\u5b58\u5230\u65b0\u7684CSV\u6587\u4ef6\u4e2d<\/p>\n<p>annual_salary.to_csv(&#39;annual_salary.csv&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>5\u3001\u53ef\u89c6\u5316\u6c47\u603b\u7ed3\u679c<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528Pandas\u548cMatplotlib\u5e93\u5bf9\u6c47\u603b\u7ed3\u679c\u8fdb\u884c\u53ef\u89c6\u5316\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u7ed8\u5236\u6bcf\u5e74\u5de5\u8d44\u603b\u989d\u7684\u6298\u7ebf\u56fe\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>annual_salary.plot(kind=&#39;line&#39;)<\/p>\n<p>plt.xlabel(&#39;Year&#39;)<\/p>\n<p>plt.ylabel(&#39;Total Salary&#39;)<\/p>\n<p>plt.title(&#39;Annual Salary Summary&#39;)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e09\u3001\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f<\/p>\n<\/p>\n<p><p>\u5217\u8868\u63a8\u5bfc\u5f0f\u662fPython\u4e2d\u975e\u5e38\u5f3a\u5927\u7684\u7279\u6027\u4e4b\u4e00\uff0c\u80fd\u591f\u4ee5\u7b80\u6d01\u7684\u65b9\u5f0f\u521b\u5efa\u5217\u8868\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u5bf9\u5de5\u8d44\u6570\u636e\u8fdb\u884c\u6c47\u603b\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5c06\u5de5\u8d44\u6570\u636e\u8bfb\u53d6\u5230\u5217\u8868\u4e2d\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3a<code>salaries.csv<\/code>\u7684CSV\u6587\u4ef6\uff0c\u5305\u542b\u5458\u5de5\u7684\u5de5\u8d44\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>csv<\/code>\u6a21\u5757\u8bfb\u53d6\u8be5\u6587\u4ef6\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;salaries.csv&#39;, &#39;r&#39;) as file:<\/p>\n<p>    reader = csv.reader(file)<\/p>\n<p>    data = list(reader)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u6570\u636e\u7b5b\u9009<\/h3>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u6570\u636e\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u7b5b\u9009\uff0c\u4ee5\u4fbf\u53ea\u4fdd\u7559\u9700\u8981\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u7b5b\u9009\u51fa\u7279\u5b9a\u5e74\u4efd\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7b5b\u9009\u51fa2022\u5e74\u7684\u5de5\u8d44\u6570\u636e<\/p>\n<p>data_2022 = [row for row in data if row[1] == &#39;2022&#39;]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3\u3001\u8ba1\u7b97\u603b\u5de5\u8d44<\/h3>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u8ba1\u7b97\u603b\u5de5\u8d44\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8ba1\u7b97\u603b\u5de5\u8d44<\/p>\n<p>total_salary = sum([float(row[2]) for row in data_2022])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>4\u3001\u8f93\u51fa\u7ed3\u679c<\/h3>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8f93\u51fa\u603b\u5de5\u8d44\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">print(f&#39;Total Salary in 2022: {total_salary}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u56db\u3001\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u5de5\u8d44\u6570\u636e<\/p>\n<\/p>\n<p><p>\u5b57\u5178\u662fPython\u4e2d\u975e\u5e38\u7075\u6d3b\u7684\u6570\u636e\u7ed3\u6784\uff0c\u80fd\u591f\u4ee5\u952e\u503c\u5bf9\u7684\u5f62\u5f0f\u5b58\u50a8\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u5de5\u8d44\u6570\u636e\uff0c\u5e76\u8fdb\u884c\u6c47\u603b\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5c06\u5de5\u8d44\u6570\u636e\u8bfb\u53d6\u5230\u5b57\u5178\u4e2d\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3a<code>salaries.csv<\/code>\u7684CSV\u6587\u4ef6\uff0c\u5305\u542b\u5458\u5de5\u7684\u5de5\u8d44\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>csv<\/code>\u6a21\u5757\u8bfb\u53d6\u8be5\u6587\u4ef6\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;salaries.csv&#39;, &#39;r&#39;) as file:<\/p>\n<p>    reader = csv.reader(file)<\/p>\n<p>    data = {row[0]: float(row[2]) for row in reader}<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u6570\u636e\u7b5b\u9009<\/h3>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u6570\u636e\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u7b5b\u9009\uff0c\u4ee5\u4fbf\u53ea\u4fdd\u7559\u9700\u8981\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u7b5b\u9009\u51fa\u7279\u5b9a\u5e74\u4efd\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7b5b\u9009\u51fa2022\u5e74\u7684\u5de5\u8d44\u6570\u636e<\/p>\n<p>data_2022 = {k: v for k, v in data.items() if k.split(&#39;-&#39;)[0] == &#39;2022&#39;}<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3\u3001\u8ba1\u7b97\u603b\u5de5\u8d44<\/h3>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u8ba1\u7b97\u603b\u5de5\u8d44\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8ba1\u7b97\u603b\u5de5\u8d44<\/p>\n<p>total_salary = sum(data_2022.values())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>4\u3001\u8f93\u51fa\u7ed3\u679c<\/h3>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8f93\u51fa\u603b\u5de5\u8d44\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">print(f&#39;Total Salary in 2022: {total_salary}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e94\u3001\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u8ba1\u7b97<\/p>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u5e38\u7528\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u548c\u6570\u5b66\u51fd\u6570\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u5de5\u8d44\u6c47\u603b\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5c06\u5de5\u8d44\u6570\u636e\u8bfb\u53d6\u5230NumPy\u6570\u7ec4\u4e2d\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3a<code>salaries.csv<\/code>\u7684CSV\u6587\u4ef6\uff0c\u5305\u542b\u5458\u5de5\u7684\u5de5\u8d44\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>numpy.genfromtxt<\/code>\u51fd\u6570\u8bfb\u53d6\u8be5\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n<p>data = np.genfromtxt(&#39;salaries.csv&#39;, delimiter=&#39;,&#39;, skip_header=1, usecols=(1, 2), dtype=None, encoding=&#39;utf-8&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u6570\u636e\u7b5b\u9009<\/h3>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u6570\u636e\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u7b5b\u9009\uff0c\u4ee5\u4fbf\u53ea\u4fdd\u7559\u9700\u8981\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u7b5b\u9009\u51fa\u7279\u5b9a\u5e74\u4efd\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u7b5b\u9009\u51fa2022\u5e74\u7684\u5de5\u8d44\u6570\u636e<\/p>\n<p>data_2022 = data[data[:, 0] == &#39;2022&#39;]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3\u3001\u8ba1\u7b97\u603b\u5de5\u8d44<\/h3>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528NumPy\u7684<code>sum<\/code>\u51fd\u6570\u8ba1\u7b97\u603b\u5de5\u8d44\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8ba1\u7b97\u603b\u5de5\u8d44<\/p>\n<p>total_salary = np.sum(data_2022[:, 1].astype(float))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>4\u3001\u8f93\u51fa\u7ed3\u679c<\/h3>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8f93\u51fa\u603b\u5de5\u8d44\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">print(f&#39;Total Salary in 2022: {total_salary}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u516d\u3001\u603b\u7ed3<\/p>\n<\/p>\n<p><p>\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528Python\u8fdb\u884c\u5e74\u5de5\u8d44\u6c47\u603b\u3002\u6211\u4eec\u8ba8\u8bba\u4e86\u56db\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u3001\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u5de5\u8d44\u6570\u636e\u3001\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528Pandas\u5e93<\/strong>\u662f\u6700\u4e3a\u63a8\u8350\u7684\u65b9\u6cd5\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u80fd\u591f\u7b80\u5316\u6570\u636e\u64cd\u4f5c\u8fc7\u7a0b\u3002\u540c\u65f6\uff0cPandas\u8fd8\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u529f\u80fd\uff0c\u80fd\u591f\u6ee1\u8db3\u5927\u591a\u6570\u6570\u636e\u5206\u6790\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f<\/strong>\u548c<strong>\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u5de5\u8d44\u6570\u636e<\/strong>\u4e5f\u662f\u53ef\u884c\u7684\u65b9\u6cd5\uff0c\u9002\u7528\u4e8e\u6570\u636e\u91cf\u8f83\u5c0f\u7684\u60c5\u51b5\u3002\u8fd9\u4e24\u79cd\u65b9\u6cd5\u7684\u4f18\u70b9\u662f\u4ee3\u7801\u7b80\u6d01\u3001\u6613\u4e8e\u7406\u89e3\uff0c\u4f46\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\u53ef\u80fd\u4f1a\u9047\u5230\u6027\u80fd\u74f6\u9888\u3002<\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u8ba1\u7b97<\/strong>\u4e5f\u662f\u4e00\u79cd\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u9002\u7528\u4e8e\u9700\u8981\u8fdb\u884c\u5927\u91cf\u6570\u503c\u8ba1\u7b97\u7684\u60c5\u51b5\u3002NumPy\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u548c\u6570\u5b66\u51fd\u6570\uff0c\u80fd\u591f\u663e\u8457\u63d0\u9ad8\u8ba1\u7b97\u6027\u80fd\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u8fd9\u51e0\u79cd\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5b9e\u73b0\u5e74\u5de5\u8d44\u7684\u6c47\u603b\uff0c\u5e76\u5bf9\u6c47\u603b\u7ed3\u679c\u8fdb\u884c\u8fdb\u4e00\u6b65\u5904\u7406\u548c\u5206\u6790\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff0c\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u5e94\u7528Python\u8fdb\u884c\u6570\u636e\u5206\u6790\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u8ba1\u7b97\u5e74\u5de5\u8d44\u7684\u603b\u548c\uff1f<\/strong><br \/>\u8981\u8ba1\u7b97\u5e74\u5de5\u8d44\u7684\u603b\u548c\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u4e2d\u7684\u57fa\u672c\u7b97\u672f\u8fd0\u7b97\u3002\u9996\u5148\uff0c\u5c06\u6bcf\u6708\u5de5\u8d44\u5b58\u50a8\u5728\u4e00\u4e2a\u5217\u8868\u4e2d\uff0c\u7136\u540e\u4f7f\u7528<code>sum()<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u603b\u548c\u3002\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">monthly_salaries = [3000, 3200, 2900, 3100, 3000, 3500, 3600, 3700, 3800, 3900, 4000, 4100]\nannual_salary = sum(monthly_salaries)\nprint(&quot;\u5e74\u5de5\u8d44\u603b\u548c\u4e3a:&quot;, annual_salary)\n<\/code><\/pre>\n<p><strong>\u6211\u53ef\u4ee5\u7528Python\u751f\u6210\u5de5\u8d44\u6761\u5417\uff1f<\/strong><br \/>\u662f\u7684\uff0cPython\u53ef\u4ee5\u7528\u6765\u751f\u6210\u5de5\u8d44\u6761\u3002\u53ef\u4ee5\u4f7f\u7528Python\u7684\u5185\u7f6e\u5e93\uff0c\u6bd4\u5982<code>pandas<\/code>\uff0c\u6765\u521b\u5efa\u4e00\u4e2a\u6570\u636e\u6846\uff0c\u7136\u540e\u5c06\u5de5\u8d44\u4fe1\u606f\u5bfc\u51fa\u4e3aExcel\u6216CSV\u6587\u4ef6\u3002\u8fd9\u6837\u53ef\u4ee5\u65b9\u4fbf\u5730\u67e5\u770b\u548c\u7ba1\u7406\u5de5\u8d44\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a  <\/p>\n<pre><code class=\"language-python\">import pandas as pd\n\ndata = {&#39;\u6708\u4efd&#39;: [&#39;\u4e00\u6708&#39;, &#39;\u4e8c\u6708&#39;, &#39;\u4e09\u6708&#39;, &#39;\u56db\u6708&#39;],\n        &#39;\u5de5\u8d44&#39;: [3000, 3200, 2900, 3100]}\ndf = pd.DataFrame(data)\ndf.to_csv(&#39;\u5de5\u8d44\u6761.csv&#39;, index=False)\n<\/code><\/pre>\n<p><strong>\u5728Python\u4e2d\u5982\u4f55\u5904\u7406\u4e0d\u540c\u7684\u5de5\u8d44\u8ba1\u7b97\u89c4\u5219\uff1f<\/strong><br \/>\u5904\u7406\u4e0d\u540c\u7684\u5de5\u8d44\u8ba1\u7b97\u89c4\u5219\u53ef\u4ee5\u901a\u8fc7\u5b9a\u4e49\u51fd\u6570\u6765\u5b9e\u73b0\u3002\u6839\u636e\u516c\u53f8\u653f\u7b56\uff0c\u53ef\u4ee5\u521b\u5efa\u4e0d\u540c\u7684\u8ba1\u7b97\u903b\u8f91\uff0c\u5982\u57fa\u672c\u5de5\u8d44\u3001\u52a0\u73ed\u8d39\u3001\u5956\u91d1\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a  <\/p>\n<pre><code class=\"language-python\">def calculate_salary(base_salary, overtime_hours, overtime_rate):\n    return base_salary + (overtime_hours * overtime_rate)\n\ntotal_salary = calculate_salary(3000, 10, 150)\nprint(&quot;\u603b\u5de5\u8d44\u4e3a:&quot;, total_salary)\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u5f0f\u4f7f\u5f97\u4ee3\u7801\u66f4\u5177\u53ef\u8bfb\u6027\u548c\u53ef\u7ef4\u62a4\u6027\uff0c\u65b9\u4fbf\u540e\u7eed\u7684\u8c03\u6574\u548c\u6269\u5c55\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u4e00\u3001\u6c47\u603b\u5e74\u5de5\u8d44\u5982\u4f55\u7528Python \u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u3001\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u5de5\u8d44\u6570\u636e\u3001\u4f7f\u7528NumPy\u5e93\u8fdb [&hellip;]","protected":false},"author":3,"featured_media":1170388,"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\/1170384"}],"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=1170384"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1170384\/revisions"}],"predecessor-version":[{"id":1170391,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1170384\/revisions\/1170391"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1170388"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1170384"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1170384"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1170384"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}