{"id":1142246,"date":"2025-01-08T22:38:07","date_gmt":"2025-01-08T14:38:07","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1142246.html"},"modified":"2025-01-08T22:38:10","modified_gmt":"2025-01-08T14:38:10","slug":"%e5%a6%82%e4%bd%95%e5%9c%a8python%e4%b8%ad%e9%80%89%e6%8b%a9%e8%a1%a8%e6%a0%bc%e4%b8%ad%e7%9a%84%e6%9f%90%e4%b8%80%e8%a1%8c","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1142246.html","title":{"rendered":"\u5982\u4f55\u5728Python\u4e2d\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c"},"content":{"rendered":"

\"\u5982\u4f55\u5728Python\u4e2d\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c\"<\/p>\n

\u5982\u4f55\u5728Python\u4e2d\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c<\/strong><\/p>\n<\/p>\n

\u5728Python\u4e2d\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u3001\u7d22\u5f15\u4f4d\u7f6e\u3001\u6761\u4ef6\u8fc7\u6ee4\u3001DataFrame\u7684loc\u548ciloc\u65b9\u6cd5<\/strong>\u3002\u5176\u4e2d\uff0cPandas\u5e93<\/strong>\u662f\u6700\u5e38\u7528\u548c\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002\u901a\u8fc7Pandas\u5e93\uff0c\u53ef\u4ee5\u8f7b\u677e\u8bfb\u53d6\u8868\u683c\u6570\u636e\uff0c\u5e76\u4f7f\u7528loc\u548ciloc\u65b9\u6cd5\u7cbe\u786e\u9009\u62e9\u7279\u5b9a\u884c\u3002\u4ee5\u4e0b\u5185\u5bb9\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Pandas\u5e93\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c\u3002<\/p>\n<\/p>\n

\u4e00\u3001Pandas\u5e93\u6982\u8ff0<\/h3>\n<\/p>\n

Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u5f00\u6e90\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u5e93\uff0c\u5b83\u4e3aPython\u63d0\u4f9b\u4e86\u9ad8\u6027\u80fd\u3001\u6613\u7528\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002Pandas\u4e3b\u8981\u7684\u6570\u636e\u7ed3\u6784\u662fSeries\uff08\u4e00\u7ef4\u6570\u7ec4\uff09\u548cDataFrame\uff08\u4e8c\u7ef4\u6570\u7ec4\uff09\uff0cDataFrame\u7c7b\u4f3c\u4e8eExcel\u4e2d\u7684\u8868\u683c\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Pandas<\/h4>\n<\/p>\n

\u5728\u4f7f\u7528Pandas\u4e4b\u524d\uff0c\u9700\u8981\u5148\u5b89\u88c5\u5b83\u3002\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n
Pandas\u652f\u6301\u8bfb\u53d6\u591a\u79cd\u683c\u5f0f\u7684\u6570\u636e\uff0c\u5982CSV\u3001Excel\u3001SQL\u6570\u636e\u5e93\u7b49\u3002\u4ee5\u4e0b\u662f\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_csv('data.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u7d22\u5f15\u4f4d\u7f6e\u9009\u62e9\u884c<\/h3>\n<\/p>\n
Pandas\u7684DataFrame\u5bf9\u8c61\u53ef\u4ee5\u901a\u8fc7\u884c\u7d22\u5f15\u4f4d\u7f6e\u6765\u9009\u62e9\u7279\u5b9a\u884c\u3002\u53ef\u4ee5\u4f7f\u7528iloc\u65b9\u6cd5\uff0c\u5b83\u5141\u8bb8\u901a\u8fc7\u6574\u6570\u4f4d\u7f6e\u9009\u62e9\u884c\u3002<\/p>\n<\/p>\n
1\u3001\u9009\u62e9\u5355\u884c<\/h4>\n<\/p>\n
# \u9009\u62e9\u7b2c2\u884c\uff08\u7d22\u5f15\u4f4d\u7f6e\u4ece0\u5f00\u59cb\uff09<\/p>\n
row = df.iloc[1]<\/p>\n
print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u9009\u62e9\u591a\u884c<\/h4>\n<\/p>\n
# \u9009\u62e9\u7b2c2\u884c\u5230\u7b2c4\u884c<\/p>\n
rows = df.iloc[1:4]<\/p>\n
print(rows)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528\u6761\u4ef6\u8fc7\u6ee4\u9009\u62e9\u884c<\/h3>\n<\/p>\n
Pandas\u5141\u8bb8\u6839\u636e\u6761\u4ef6\u8fc7\u6ee4\u6765\u9009\u62e9\u6ee1\u8db3\u7279\u5b9a\u6761\u4ef6\u7684\u884c\u3002\u53ef\u4ee5\u901a\u8fc7\u5e03\u5c14\u7d22\u5f15\u5b9e\u73b0\u8fd9\u4e00\u529f\u80fd\u3002<\/p>\n<\/p>\n
1\u3001\u9009\u62e9\u6ee1\u8db3\u6761\u4ef6\u7684\u884c<\/h4>\n<\/p>\n
# \u9009\u62e9\u5e74\u9f84\u5927\u4e8e30\u7684\u884c<\/p>\n
rows = df[df['age'] > 30]<\/p>\n
print(rows)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ec4\u5408\u591a\u4e2a\u6761\u4ef6<\/h4>\n<\/p>\n
# \u9009\u62e9\u5e74\u9f84\u5927\u4e8e30\u4e14\u6027\u522b\u4e3a\u7537\u6027\u7684\u884c<\/p>\n
rows = df[(df['age'] > 30) & (df['gender'] == 'male')]<\/p>\n
print(rows)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528loc\u65b9\u6cd5\u9009\u62e9\u884c<\/h3>\n<\/p>\n
loc\u65b9\u6cd5\u5141\u8bb8\u901a\u8fc7\u6807\u7b7e\uff08\u884c\u7d22\u5f15\u6807\u7b7e\u548c\u5217\u6807\u7b7e\uff09\u9009\u62e9\u884c\u548c\u5217\u3002\u4e0eiloc\u4e0d\u540c\uff0cloc\u4f7f\u7528\u7684\u662f\u6807\u7b7e\u800c\u4e0d\u662f\u6574\u6570\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n
1\u3001\u9009\u62e9\u5355\u884c<\/h4>\n<\/p>\n
# \u9009\u62e9\u7d22\u5f15\u4e3a2\u7684\u884c<\/p>\n
row = df.loc[2]<\/p>\n
print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u9009\u62e9\u591a\u884c<\/h4>\n<\/p>\n
# \u9009\u62e9\u7d22\u5f15\u4e3a2\u52304\u7684\u884c<\/p>\n
rows = df.loc[2:4]<\/p>\n
print(rows)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u4f7f\u7528Pandas\u5e93\u3001\u7d22\u5f15\u4f4d\u7f6e\u3001\u6761\u4ef6\u8fc7\u6ee4\u3001DataFrame\u7684loc\u548ciloc\u65b9\u6cd5<\/strong>\uff0c\u53ef\u4ee5\u5728Python\u4e2d\u65b9\u4fbf\u5730\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c\u3002Pandas\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u80fd\u591f\u5e2e\u52a9\u5f00\u53d1\u8005\u9ad8\u6548\u5730\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002\u65e0\u8bba\u662f\u901a\u8fc7\u7d22\u5f15\u4f4d\u7f6e\u3001\u6761\u4ef6\u8fc7\u6ee4\u8fd8\u662f\u6807\u7b7e\u9009\u62e9\uff0c\u90fd\u80fd\u8f7b\u677e\u5b9e\u73b0\u5bf9\u7279\u5b9a\u884c\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n
\u7ee7\u7eed\u6df1\u5165\u5b66\u4e60Pandas\u5e93\u7684\u4f7f\u7528\uff0c\u53ef\u4ee5\u66f4\u597d\u5730\u638c\u63e1\u6570\u636e\u5206\u6790\u7684\u6280\u80fd\uff0c\u4e3a\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60<\/a>\u6253\u4e0b\u575a\u5b9e\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5728Python\u4e2d\uff0c\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u9009\u62e9\u7279\u5b9a\u884c\u7684\u8868\u683c\u6570\u636e\uff1f<\/strong>
Pandas\u5e93\u662f\u5904\u7406\u8868\u683c\u6570\u636e\u7684\u5f3a\u5927\u5de5\u5177\u3002\u53ef\u4ee5\u4f7f\u7528loc<\/code>\u6216iloc<\/code>\u65b9\u6cd5\u6765\u9009\u62e9\u7279\u5b9a\u884c\u3002\u4f7f\u7528loc<\/code>\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u884c\u6807\u7b7e\u9009\u62e9\uff0c\u800c\u4f7f\u7528iloc<\/code>\u5219\u662f\u901a\u8fc7\u884c\u7d22\u5f15\u3002\u4f8b\u5982\uff0cdf.loc[2]<\/code>\u4f1a\u9009\u62e9\u6807\u7b7e\u4e3a2\u7684\u884c\uff0cdf.iloc[2]<\/code>\u4f1a\u9009\u62e9\u7b2c\u4e09\u884c\u3002\u786e\u4fdd\u5728\u4f7f\u7528\u524d\u5df2\u5bfc\u5165Pandas\u5e93\u5e76\u8bfb\u53d6\u4e86\u6570\u636e\u3002<\/p>\n
\u5982\u679c\u8868\u683c\u6570\u636e\u4e2d\u5305\u542b\u6761\u4ef6\uff0c\u5982\u4f55\u6839\u636e\u6761\u4ef6\u9009\u62e9\u884c\uff1f<\/strong>
\u4f7f\u7528\u5e03\u5c14\u7d22\u5f15\u53ef\u4ee5\u6839\u636e\u6761\u4ef6\u9009\u62e9\u884c\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u6709\u4e00\u4e2aDataFrame\u5bf9\u8c61df<\/code>\uff0c\u5e76\u5e0c\u671b\u9009\u62e9\u201c\u5e74\u9f84\u201d\u5217\u5927\u4e8e30\u7684\u6240\u6709\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528df[df['\u5e74\u9f84'] > 30]<\/code>\u3002\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u7075\u6d3b\uff0c\u80fd\u591f\u9488\u5bf9\u591a\u4e2a\u6761\u4ef6\u8fdb\u884c\u590d\u6742\u7684\u7b5b\u9009\u3002<\/p>\n
\u5728\u9009\u62e9\u884c\u540e\uff0c\u5982\u4f55\u5bf9\u8fd9\u4e9b\u884c\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u6570\u636e\u5904\u7406\uff1f<\/strong>
\u9009\u62e9\u884c\u540e\uff0c\u53ef\u4ee5\u76f4\u63a5\u5bf9\u8fd9\u4e9b\u6570\u636e\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\uff0c\u4f8b\u5982\u8ba1\u7b97\u5e73\u5747\u503c\u3001\u8fdb\u884c\u7edf\u8ba1\u5206\u6790\u6216\u8005\u7ed8\u5236\u56fe\u8868\u3002\u4f8b\u5982\uff0c\u4f7f\u7528selected_rows.mean()<\/code>\u53ef\u4ee5\u8ba1\u7b97\u6240\u9009\u62e9\u884c\u7684\u5e73\u5747\u503c\u3002\u8fd8\u53ef\u4ee5\u5229\u7528Pandas\u7684\u5176\u4ed6\u529f\u80fd\u5982groupby<\/code>\u3001apply<\/code>\u7b49\uff0c\u5bf9\u8fd9\u4e9b\u884c\u8fdb\u884c\u66f4\u6df1\u5165\u7684\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u5728Python\u4e2d\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c \u5728Python\u4e2d\u9009\u62e9\u8868\u683c\u4e2d\u7684\u67d0\u4e00\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u3001\u7d22\u5f15\u4f4d\u7f6e\u3001 […]","protected":false},"author":3,"featured_media":1142250,"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\/1142246"}],"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=1142246"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1142246\/revisions"}],"predecessor-version":[{"id":1142251,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1142246\/revisions\/1142251"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1142250"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1142246"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1142246"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1142246"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}