{"id":928024,"date":"2024-12-26T16:25:41","date_gmt":"2024-12-26T08:25:41","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/928024.html"},"modified":"2024-12-26T16:25:43","modified_gmt":"2024-12-26T08:25:43","slug":"python%e5%a6%82%e4%bd%95%e5%8f%96%e5%b9%b3%e5%9d%87","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/928024.html","title":{"rendered":"python\u5982\u4f55\u53d6\u5e73\u5747"},"content":{"rendered":"

\"python\u5982\u4f55\u53d6\u5e73\u5747\"<\/p>\n

\u5728Python\u4e2d\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6765\u8ba1\u7b97\u5e73\u5747\u503c\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3001NumPy\u5e93\u3001Pandas\u5e93\u7b49\u3002\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u5185\u7f6e\u7684sum()\u548clen()\u51fd\u6570\u3001NumPy\u5e93\u63d0\u4f9b\u7684mean()\u51fd\u6570\u3001Pandas\u5e93\u7684mean()\u65b9\u6cd5\u3002<\/strong> \u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u65b9\u4fbf\u5730\u8ba1\u7b97\u6570\u636e\u96c6\u4e2d\u5143\u7d20\u7684\u5e73\u5747\u503c\u3002\u4e0b\u9762\u6211\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u51e0\u79cd\u65b9\u6cd5\uff0c\u5e76\u63d0\u4f9b\u4ee3\u7801\u793a\u4f8b\u548c\u6ce8\u610f\u4e8b\u9879\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u8ba1\u7b97\u5e73\u5747\u503c<\/p>\n<\/p>\n

Python\u63d0\u4f9b\u4e86\u7b80\u5355\u7684\u5185\u7f6e\u51fd\u6570\u6765\u8ba1\u7b97\u5217\u8868\u6216\u5176\u4ed6\u53ef\u8fed\u4ee3\u5bf9\u8c61\u7684\u5e73\u5747\u503c\u3002\u6700\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u4f7f\u7528sum()\u548clen()\u51fd\u6570\u3002<\/p>\n<\/p>\n

def calculate_average(numbers):<\/p>\n
    return sum(numbers) \/ len(numbers)<\/p>\n
numbers = [1, 2, 3, 4, 5]<\/p>\n
average = calculate_average(numbers)<\/p>\n
print("Average using built-in functions:", average)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0csum()\u51fd\u6570\u7528\u4e8e\u8ba1\u7b97\u6240\u6709\u5143\u7d20\u7684\u603b\u548c\uff0clen()\u51fd\u6570\u7528\u4e8e\u8ba1\u7b97\u5143\u7d20\u7684\u6570\u91cf\uff0c\u7136\u540e\u7528\u603b\u548c\u9664\u4ee5\u6570\u91cf\u5f97\u5230\u5e73\u5747\u503c\u3002\u8fd9\u79cd\u65b9\u6cd5\u7b80\u5355\u76f4\u63a5\uff0c\u9002\u7528\u4e8e\u5c0f\u578b\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528NumPy\u5e93\u8ba1\u7b97\u5e73\u5747\u503c<\/p>\n<\/p>\n
NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u4fbf\u7684\u6570\u7ec4\u64cd\u4f5c\u51fd\u6570\u3002\u5176\u4e2d\uff0cmean()\u51fd\u6570\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u6570\u7ec4\u7684\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
numbers = np.array([1, 2, 3, 4, 5])<\/p>\n
average = np.mean(numbers)<\/p>\n
print("Average using NumPy:", average)<\/p>\n
<\/code><\/pre>\n<\/p>\n
NumPy\u7684mean()\u51fd\u6570\u4e0d\u4ec5\u53ef\u4ee5\u7528\u4e8e\u4e00\u7ef4\u6570\u7ec4\uff0c\u4e5f\u53ef\u4ee5\u7528\u4e8e\u591a\u7ef4\u6570\u7ec4\uff0c\u8ba1\u7b97\u6cbf\u6307\u5b9a\u8f74\u7684\u5e73\u5747\u503c\u3002\u5b83\u7684\u6027\u80fd\u4f18\u4e8ePython\u5185\u7f6e\u51fd\u6570\uff0c\u7279\u522b\u662f\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Pandas\u5e93\u8ba1\u7b97\u5e73\u5747\u503c<\/p>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u6570\u636e\u5206\u6790\u5e93\uff0c\u63d0\u4f9b\u4e86\u7075\u6d3b\u7684\u6570\u636e\u7ed3\u6784\u548c\u4e30\u5bcc\u7684\u6570\u636e\u64cd\u4f5c\u529f\u80fd\u3002\u5bf9\u4e8e\u6570\u636e\u6846\u548c\u5e8f\u5217\uff0cPandas\u7684mean()\u65b9\u6cd5\u53ef\u4ee5\u8ba1\u7b97\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = {'numbers': [1, 2, 3, 4, 5]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
average = df['numbers'].mean()<\/p>\n
print("Average using Pandas:", average)<\/p>\n
<\/code><\/pre>\n<\/p>\n
Pandas\u7684mean()\u65b9\u6cd5\u4e0d\u4ec5\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u5355\u5217\u7684\u5e73\u5747\u503c\uff0c\u8fd8\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u6574\u4e2a\u6570\u636e\u6846\u7684\u5e73\u5747\u503c\u3002Pandas\u5904\u7406\u6570\u636e\u65f6\u4fdd\u7559\u4e86\u6570\u636e\u7684\u6807\u7b7e\u4fe1\u606f\uff0c\u9002\u5408\u4e0e\u6570\u636e\u6846\u7ed3\u5408\u4f7f\u7528\u3002<\/p>\n<\/p>\n
\u56db\u3001\u8ba1\u7b97\u52a0\u6743\u5e73\u5747\u503c<\/p>\n<\/p>\n
\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u9700\u8981\u8ba1\u7b97\u52a0\u6743\u5e73\u5747\u503c\u3002\u52a0\u6743\u5e73\u5747\u503c\u8003\u8651\u4e86\u6bcf\u4e2a\u6570\u636e\u70b9\u7684\u91cd\u8981\u6027\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u5b9e\u73b0\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
values = np.array([1, 2, 3, 4, 5])<\/p>\n
weights = np.array([0.1, 0.2, 0.3, 0.2, 0.2])<\/p>\n
weighted_average = np.average(values, weights=weights)<\/p>\n
print("Weighted Average:", weighted_average)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0cnp.average()\u51fd\u6570\u63a5\u53d7\u4e00\u4e2a\u6743\u91cd\u53c2\u6570\uff0c\u7528\u4e8e\u8ba1\u7b97\u52a0\u6743\u5e73\u5747\u503c\u3002\u6743\u91cd\u6570\u7ec4\u7684\u957f\u5ea6\u5e94\u4e0e\u6570\u636e\u6570\u7ec4\u76f8\u540c\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u5904\u7406\u7a7a\u503c\u548c\u5f02\u5e38\u503c<\/p>\n<\/p>\n
\u5728\u5b9e\u9645\u6570\u636e\u5904\u7406\u4e2d\uff0c\u7ecf\u5e38\u4f1a\u9047\u5230\u7a7a\u503c\uff08NaN\uff09\u6216\u5f02\u5e38\u503c\u3002Pandas\u63d0\u4f9b\u4e86\u4e00\u4e9b\u65b9\u6cd5\u6765\u5904\u7406\u8fd9\u4e9b\u60c5\u51b5\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import numpy as np<\/p>\n
data = {'numbers': [1, 2, np.nan, 4, 5]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
average = df['numbers'].mean(skipna=True)<\/p>\n
print("Average with NaN handling:", average)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7skipna=True\u53c2\u6570\uff0cPandas\u7684mean()\u65b9\u6cd5\u53ef\u4ee5\u5ffd\u7565NaN\u503c\u8ba1\u7b97\u5e73\u5747\u503c\u3002\u6b64\u5916\uff0c\u53ef\u4ee5\u4f7f\u7528fillna()\u65b9\u6cd5\u586b\u5145NaN\u503c\u6216apply\u51fd\u6570\u5904\u7406\u5f02\u5e38\u503c\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/p>\n<\/p>\n
\u5728Python\u4e2d\u8ba1\u7b97\u5e73\u5747\u503c\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3001NumPy\u5e93\u3001Pandas\u5e93\u7b49\u3002\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u6570\u636e\u7684\u7ed3\u6784\u548c\u8ba1\u7b97\u9700\u6c42\u3002\u5bf9\u4e8e\u5927\u578b\u6570\u636e\u96c6\uff0c\u5efa\u8bae\u4f7f\u7528NumPy\u6216Pandas\u4ee5\u83b7\u5f97\u66f4\u597d\u7684\u6027\u80fd\u548c\u7075\u6d3b\u6027\u3002\u6b64\u5916\uff0c\u5904\u7406\u6570\u636e\u4e2d\u7684\u7a7a\u503c\u548c\u5f02\u5e38\u503c\u4e5f\u662f\u8ba1\u7b97\u5e73\u5747\u503c\u65f6\u9700\u8981\u6ce8\u610f\u7684\u95ee\u9898\u3002\u901a\u8fc7\u4e86\u89e3\u8fd9\u4e9b\u65b9\u6cd5\u548c\u6280\u5de7\uff0c\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u8ba1\u7b97\u5217\u8868\u7684\u5e73\u5747\u503c\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684sum()<\/code>\u51fd\u6570\u548clen()<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u5217\u8868\u7684\u5e73\u5747\u503c\u3002\u901a\u8fc7\u5c06\u5217\u8868\u4e2d\u7684\u6240\u6709\u5143\u7d20\u76f8\u52a0\uff0c\u7136\u540e\u9664\u4ee5\u5143\u7d20\u7684\u6570\u91cf\u5373\u53ef\u5f97\u5230\u5e73\u5747\u503c\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
numbers = [10, 20, 30, 40, 50]\naverage = sum(numbers) \/ len(numbers)\nprint(average)  # \u8f93\u51fa\uff1a30.0\n<\/code><\/pre>\n
Python\u4e2d\u662f\u5426\u6709\u4e13\u95e8\u7684\u5e93\u6765\u8ba1\u7b97\u5e73\u5747\u503c\uff1f<\/strong>
\u662f\u7684\uff0cPython\u7684statistics<\/code>\u5e93\u63d0\u4f9b\u4e86\u4e00\u4e2a\u65b9\u4fbf\u7684mean()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u76f4\u63a5\u8ba1\u7b97\u5e73\u5747\u503c\u3002\u4f7f\u7528\u8fd9\u4e2a\u5e93\u53ef\u4ee5\u4f7f\u4ee3\u7801\u66f4\u52a0\u7b80\u6d01\u548c\u6e05\u6670\u3002\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n
import statistics\n\nnumbers = [10, 20, 30, 40, 50]\naverage = statistics.mean(numbers)\nprint(average)  # \u8f93\u51fa\uff1a30\n<\/code><\/pre>\n
\u5982\u4f55\u5904\u7406\u5305\u542bNaN\u503c\u7684\u5217\u8868\u4ee5\u8ba1\u7b97\u5e73\u5747\u503c\uff1f<\/strong>
\u5728\u8ba1\u7b97\u5e73\u5747\u503c\u65f6\uff0c\u5982\u679c\u5217\u8868\u4e2d\u5305\u542bNaN\uff08\u4e0d\u662f\u6570\u5b57\uff09\u503c\uff0c\u5efa\u8bae\u4f7f\u7528numpy<\/code>\u5e93\u3002numpy<\/code>\u63d0\u4f9b\u7684nanmean()<\/code>\u51fd\u6570\u53ef\u4ee5\u5ffd\u7565NaN\u503c\u5e76\u8ba1\u7b97\u6709\u6548\u6570\u636e\u7684\u5e73\u5747\u503c\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
import numpy as np\n\nnumbers = [10, 20, np.nan, 40, 50]\naverage = np.nanmean(numbers)\nprint(average)  # \u8f93\u51fa\uff1a30.0\n<\/code><\/pre>\n
\u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u7528\u6237\u53ef\u4ee5\u65b9\u4fbf\u5730\u5728Python\u4e2d\u8ba1\u7b97\u5404\u79cd\u60c5\u51b5\u4e0b\u7684\u5e73\u5747\u503c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6765\u8ba1\u7b97\u5e73\u5747\u503c\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u51fd\u6570\u3001NumPy\u5e93\u3001Pandas\u5e93\u7b49\u3002\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f […]","protected":false},"author":3,"featured_media":928027,"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\/928024"}],"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=928024"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/928024\/revisions"}],"predecessor-version":[{"id":928029,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/928024\/revisions\/928029"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/928027"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=928024"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=928024"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=928024"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}