{"id":1135916,"date":"2025-01-08T21:30:33","date_gmt":"2025-01-08T13:30:33","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1135916.html"},"modified":"2025-01-08T21:30:35","modified_gmt":"2025-01-08T13:30:35","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%81%9a%e6%8f%8f%e8%bf%b0%e6%80%a7%e7%bb%9f%e8%ae%a1%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1135916.html","title":{"rendered":"\u5982\u4f55\u7528python\u505a\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u505a\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\"<\/p>\n

\u5982\u4f55\u7528Python\u505a\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790<\/strong><\/p>\n<\/p>\n

\u4f7f\u7528Python\u8fdb\u884c\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\uff0c\u5173\u952e\u6b65\u9aa4\u5305\u62ec\uff1a\u5bfc\u5165\u6570\u636e\u3001\u6570\u636e\u6e05\u6d17\u3001\u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf\u3001\u7ed8\u5236\u6570\u636e\u5206\u5e03\u56fe\u3001\u8bc6\u522b\u5f02\u5e38\u503c\u3002<\/strong> \u5176\u4e2d\uff0c\u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf<\/strong>\u662f\u6700\u4e3a\u57fa\u7840\u548c\u6838\u5fc3\u7684\u4e00\u6b65\u3002\u4f8b\u5982\uff0c\u901a\u8fc7Python\u7684pandas<\/code>\u5e93\u53ef\u4ee5\u8f7b\u677e\u8ba1\u7b97\u51fa\u6570\u636e\u7684\u5747\u503c\u3001\u65b9\u5dee\u3001\u6807\u51c6\u5dee\u7b49\u57fa\u672c\u7edf\u8ba1\u91cf\uff0c\u8fd9\u4e9b\u7edf\u8ba1\u91cf\u80fd\u5e2e\u52a9\u6211\u4eec\u5feb\u901f\u4e86\u89e3\u6570\u636e\u7684\u6574\u4f53\u7279\u5f81\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5bfc\u5165\u6570\u636e<\/h2>\n<\/p>\n

\u8fdb\u884c\u4efb\u4f55\u6570\u636e\u5206\u6790\u7684\u7b2c\u4e00\u6b65\u90fd\u662f\u83b7\u53d6\u548c\u5bfc\u5165\u6570\u636e\u3002Python\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u4fbf\u7684\u6570\u636e\u5bfc\u5165\u65b9\u6cd5\uff0c\u4f8b\u5982\u4eceCSV\u6587\u4ef6\u3001Excel\u6587\u4ef6\u6216\u6570\u636e\u5e93\u4e2d\u8bfb\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n

1\u3001\u4eceCSV\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n

CSV\u6587\u4ef6\u662f\u6700\u5e38\u89c1\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u4e4b\u4e00\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684read_csv<\/code>\u51fd\u6570\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
data = pd.read_csv('data.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4eceExcel\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n
\u9664\u4e86CSV\u6587\u4ef6\uff0cExcel\u6587\u4ef6\u4e5f\u662f\u5e38\u7528\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684read_excel<\/code>\u51fd\u6570\u6765\u8bfb\u53d6Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n
# \u8bfb\u53d6Excel\u6587\u4ef6<\/p>\n
data = pd.read_excel('data.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u4ece\u6570\u636e\u5e93\u8bfb\u53d6\u6570\u636e<\/h3>\n<\/p>\n
\u6709\u65f6\u6570\u636e\u5b58\u50a8\u5728\u6570\u636e\u5e93\u4e2d\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684read_sql<\/code>\u51fd\u6570\u6765\u8bfb\u53d6\u6570\u636e\u5e93\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
import sqlite3<\/p>\n
\u8fde\u63a5\u5230\u6570\u636e\u5e93<\/strong><\/h2>\n
conn = sqlite3.connect('database.db')<\/p>\n
\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
data = pd.read_sql('SELECT * FROM table_name', conn)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u6570\u636e\u6e05\u6d17<\/h2>\n<\/p>\n
\u5728\u5bfc\u5165\u6570\u636e\u4e4b\u540e\uff0c\u6570\u636e\u6e05\u6d17\u662f\u975e\u5e38\u91cd\u8981\u7684\u4e00\u6b65\u3002\u6570\u636e\u6e05\u6d17\u7684\u76ee\u7684\u662f\u786e\u4fdd\u6570\u636e\u7684\u8d28\u91cf\u548c\u4e00\u81f4\u6027\uff0c\u8fd9\u6837\u624d\u80fd\u8fdb\u884c\u51c6\u786e\u7684\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\u3002<\/p>\n<\/p>\n
1\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h3>\n<\/p>\n
\u7f3a\u5931\u503c\u662f\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e38\u89c1\u95ee\u9898\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684isnull<\/code>\u548cdropna<\/code>\u51fd\u6570\u6765\u5904\u7406\u7f3a\u5931\u503c\u3002<\/p>\n<\/p>\n
# \u68c0\u67e5\u7f3a\u5931\u503c<\/p>\n
data.isnull().sum()<\/p>\n
\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c<\/strong><\/h2>\n
data = data.dropna()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5904\u7406\u91cd\u590d\u503c<\/h3>\n<\/p>\n
\u91cd\u590d\u503c\u4e5f\u662f\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e38\u89c1\u95ee\u9898\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684duplicated<\/code>\u548cdrop_duplicates<\/code>\u51fd\u6570\u6765\u5904\u7406\u91cd\u590d\u503c\u3002<\/p>\n<\/p>\n
# \u68c0\u67e5\u91cd\u590d\u503c<\/p>\n
data.duplicated().sum()<\/p>\n
\u5220\u9664\u91cd\u590d\u503c<\/strong><\/h2>\n
data = data.drop_duplicates()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5904\u7406\u5f02\u5e38\u503c<\/h3>\n<\/p>\n
\u5f02\u5e38\u503c\u53ef\u80fd\u4f1a\u5f71\u54cd\u7edf\u8ba1\u5206\u6790\u7684\u7ed3\u679c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u7bb1\u7ebf\u56fe\uff08boxplot\uff09\u6765\u8bc6\u522b\u548c\u5904\u7406\u5f02\u5e38\u503c\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u7ed8\u5236\u7bb1\u7ebf\u56fe<\/strong><\/h2>\n
plt.boxplot(data['column_name'])<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf<\/h2>\n<\/p>\n
\u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf\u662f\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\u7684\u6838\u5fc3\u6b65\u9aa4\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684describe<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf\u3002<\/p>\n<\/p>\n
# \u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf<\/p>\n
data.describe()<\/p>\n
<\/code><\/pre>\n<\/p>\n
1\u3001\u5747\u503c<\/h3>\n<\/p>\n
\u5747\u503c\u662f\u6570\u636e\u7684\u5e73\u5747\u503c\uff0c\u8868\u793a\u6570\u636e\u7684\u4e2d\u5fc3\u4f4d\u7f6e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684mean<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u5747\u503c\u3002<\/p>\n<\/p>\n
# \u8ba1\u7b97\u5747\u503c<\/p>\n
data['column_name'].mean()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4e2d\u4f4d\u6570<\/h3>\n<\/p>\n
\u4e2d\u4f4d\u6570\u662f\u5c06\u6570\u636e\u6392\u5e8f\u540e\u4f4d\u4e8e\u4e2d\u95f4\u4f4d\u7f6e\u7684\u503c\uff0c\u8868\u793a\u6570\u636e\u7684\u4e2d\u5fc3\u8d8b\u52bf\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684median<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u4e2d\u4f4d\u6570\u3002<\/p>\n<\/p>\n
# \u8ba1\u7b97\u4e2d\u4f4d\u6570<\/p>\n
data['column_name'].median()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u6807\u51c6\u5dee<\/h3>\n<\/p>\n
\u6807\u51c6\u5dee\u662f\u6570\u636e\u7684\u79bb\u6563\u7a0b\u5ea6\uff0c\u8868\u793a\u6570\u636e\u7684\u6ce2\u52a8\u8303\u56f4\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u4e2d\u7684std<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u6807\u51c6\u5dee\u3002<\/p>\n<\/p>\n
# \u8ba1\u7b97\u6807\u51c6\u5dee<\/p>\n
data['column_name'].std()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u7ed8\u5236\u6570\u636e\u5206\u5e03\u56fe<\/h2>\n<\/p>\n
\u7ed8\u5236\u6570\u636e\u5206\u5e03\u56fe\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u76f4\u89c2\u5730\u4e86\u89e3\u6570\u636e\u7684\u5206\u5e03\u60c5\u51b5\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528matplotlib<\/code>\u548cseaborn<\/code>\u5e93\u6765\u7ed8\u5236\u6570\u636e\u5206\u5e03\u56fe\u3002<\/p>\n<\/p>\n
1\u3001\u76f4\u65b9\u56fe<\/h3>\n<\/p>\n
\u76f4\u65b9\u56fe\u7528\u4e8e\u663e\u793a\u6570\u636e\u7684\u9891\u7387\u5206\u5e03\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528matplotlib<\/code>\u5e93\u4e2d\u7684hist<\/code>\u51fd\u6570\u6765\u7ed8\u5236\u76f4\u65b9\u56fe\u3002<\/p>\n<\/p>\n
# \u7ed8\u5236\u76f4\u65b9\u56fe<\/p>\n
plt.hist(data['column_name'], bins=10)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7bb1\u7ebf\u56fe<\/h3>\n<\/p>\n
\u7bb1\u7ebf\u56fe\u7528\u4e8e\u663e\u793a\u6570\u636e\u7684\u5206\u5e03\u60c5\u51b5\u548c\u5f02\u5e38\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528seaborn<\/code>\u5e93\u4e2d\u7684boxplot<\/code>\u51fd\u6570\u6765\u7ed8\u5236\u7bb1\u7ebf\u56fe\u3002<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
\u7ed8\u5236\u7bb1\u7ebf\u56fe<\/strong><\/h2>\n
sns.boxplot(x=data['column_name'])<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u6563\u70b9\u56fe<\/h3>\n<\/p>\n
\u6563\u70b9\u56fe\u7528\u4e8e\u663e\u793a\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528matplotlib<\/code>\u5e93\u4e2d\u7684scatter<\/code>\u51fd\u6570\u6765\u7ed8\u5236\u6563\u70b9\u56fe\u3002<\/p>\n<\/p>\n
# \u7ed8\u5236\u6563\u70b9\u56fe<\/p>\n
plt.scatter(data['column_x'], data['column_y'])<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u8bc6\u522b\u5f02\u5e38\u503c<\/h2>\n<\/p>\n
\u5f02\u5e38\u503c\u662f\u6307\u5728\u6570\u636e\u96c6\u4e2d\u660e\u663e\u504f\u79bb\u5176\u4ed6\u6570\u636e\u70b9\u7684\u503c\u3002\u8bc6\u522b\u548c\u5904\u7406\u5f02\u5e38\u503c\u5bf9\u4e8e\u786e\u4fdd\u6570\u636e\u5206\u6790\u7684\u51c6\u786e\u6027\u975e\u5e38\u91cd\u8981\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528\u7bb1\u7ebf\u56fe\u8bc6\u522b\u5f02\u5e38\u503c<\/h3>\n<\/p>\n
\u7bb1\u7ebf\u56fe\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8bc6\u522b\u5f02\u5e38\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528seaborn<\/code>\u5e93\u4e2d\u7684boxplot<\/code>\u51fd\u6570\u6765\u7ed8\u5236\u7bb1\u7ebf\u56fe\uff0c\u5e76\u8bc6\u522b\u5f02\u5e38\u503c\u3002<\/p>\n<\/p>\n
# \u7ed8\u5236\u7bb1\u7ebf\u56fe<\/p>\n
sns.boxplot(x=data['column_name'])<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Z-Score\u8bc6\u522b\u5f02\u5e38\u503c<\/h3>\n<\/p>\n
Z-Score\u662f\u4e00\u79cd\u6807\u51c6\u5316\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8bc6\u522b\u5f02\u5e38\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528scipy<\/code>\u5e93\u4e2d\u7684zscore<\/code>\u51fd\u6570\u6765\u8ba1\u7b97Z-Score\uff0c\u5e76\u8bc6\u522b\u5f02\u5e38\u503c\u3002<\/p>\n<\/p>\n
from scipy.stats import zscore<\/p>\n
\u8ba1\u7b97Z-Score<\/strong><\/h2>\n
data['zscore'] = zscore(data['column_name'])<\/p>\n
\u8bc6\u522b\u5f02\u5e38\u503c<\/strong><\/h2>\n
outliers = data[data['zscore'] > 3]<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5904\u7406\u5f02\u5e38\u503c<\/h3>\n<\/p>\n
\u8bc6\u522b\u51fa\u5f02\u5e38\u503c\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u9009\u62e9\u5220\u9664\u6216\u66ff\u6362\u8fd9\u4e9b\u5f02\u5e38\u503c\u3002\u5220\u9664\u5f02\u5e38\u503c\u53ef\u4ee5\u4f7f\u7528drop<\/code>\u51fd\u6570\uff0c\u66ff\u6362\u5f02\u5e38\u503c\u53ef\u4ee5\u4f7f\u7528fillna<\/code>\u51fd\u6570\u3002<\/p>\n<\/p>\n
# \u5220\u9664\u5f02\u5e38\u503c<\/p>\n
data = data.drop(outliers.index)<\/p>\n
\u66ff\u6362\u5f02\u5e38\u503c<\/strong><\/h2>\n
data['column_name'] = data['column_name'].replace(outliers['column_name'], data['column_name'].median())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h2>\n<\/p>\n
\u4f7f\u7528Python\u8fdb\u884c\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\u662f\u4e00\u9879\u975e\u5e38\u6709\u7528\u7684\u6280\u80fd\u3002\u901a\u8fc7\u5bfc\u5165\u6570\u636e\u3001\u6570\u636e\u6e05\u6d17\u3001\u8ba1\u7b97\u57fa\u672c\u7edf\u8ba1\u91cf\u3001\u7ed8\u5236\u6570\u636e\u5206\u5e03\u56fe\u548c\u8bc6\u522b\u5f02\u5e38\u503c\uff0c\u6211\u4eec\u53ef\u4ee5\u5168\u9762\u4e86\u89e3\u6570\u636e\u7684\u7279\u5f81\u548c\u5206\u5e03\u60c5\u51b5\u3002\u8fd9\u4e9b\u6b65\u9aa4\u548c\u65b9\u6cd5\u4e0d\u4ec5\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8fdb\u884c\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\uff0c\u8fd8\u53ef\u4ee5\u4e3a\u540e\u7eed\u7684\u63a8\u65ad\u6027\u7edf\u8ba1\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60<\/a>\u6a21\u578b\u63d0\u4f9b\u53ef\u9760\u7684\u6570\u636e\u57fa\u7840\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u7528Python\u8fdb\u884c\u63cf\u8ff0\u6027\u7edf\u8ba1\u5206\u6790\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
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