{"id":1133552,"date":"2025-01-08T21:07:27","date_gmt":"2025-01-08T13:07:27","guid":{"rendered":""},"modified":"2025-01-08T21:07:29","modified_gmt":"2025-01-08T13:07:29","slug":"%e5%9c%a8python%e4%b8%ad%e5%a6%82%e4%bd%95%e6%88%aa%e5%8f%96csv%e6%95%b0%e6%8d%ae%e7%9a%84%e6%9f%90%e5%88%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1133552.html","title":{"rendered":"\u5728python\u4e2d\u5982\u4f55\u622a\u53d6csv\u6570\u636e\u7684\u67d0\u5217"},"content":{"rendered":"

\"\u5728python\u4e2d\u5982\u4f55\u622a\u53d6csv\u6570\u636e\u7684\u67d0\u5217\"<\/p>\n

\u5728Python\u4e2d\u622a\u53d6CSV\u6570\u636e\u7684\u67d0\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528pandas\u5e93\u6765\u7b80\u5316\u64cd\u4f5c\u3001\u8bfb\u53d6CSV\u6587\u4ef6\u3001\u63d0\u53d6\u7279\u5b9a\u5217\u3002<\/strong> \u4f7f\u7528pandas\u5e93\u4e0d\u4ec5\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u548c\u5904\u7406CSV\u6587\u4ef6\uff0c\u8fd8\u53ef\u4ee5\u5229\u7528\u5176\u5f3a\u5927\u7684\u6570\u636e\u64cd\u4f5c\u529f\u80fd\u6765\u8fdb\u884c\u5404\u79cd\u6570\u636e\u5206\u6790\u4efb\u52a1\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5728Python\u4e2d\u5982\u4f55\u4f7f\u7528pandas\u5e93\u6765\u622a\u53d6CSV\u6570\u636e\u7684\u67d0\u5217\uff0c\u5e76\u5bf9\u63d0\u53d6\u7279\u5b9a\u5217\u7684\u8be6\u7ec6\u6b65\u9aa4\u8fdb\u884c\u89e3\u91ca\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u548c\u5bfc\u5165pandas\u5e93<\/h3>\n<\/p>\n

\u5728\u5f00\u59cb\u4f7f\u7528pandas\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86pandas\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u6765\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5bfc\u5165pandas\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
\u5728\u8bfb\u53d6CSV\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528pandas\u7684read_csv<\/code>\u51fd\u6570\u3002\u8fd9\u4e2a\u51fd\u6570\u53ef\u4ee5\u5c06CSV\u6587\u4ef6\u8bfb\u53d6\u4e3aDataFrame\u683c\u5f0f\uff0c\u4ece\u800c\u65b9\u4fbf\u540e\u7eed\u7684\u64cd\u4f5c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('your_file.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u63d0\u53d6\u7279\u5b9a\u5217<\/h3>\n<\/p>\n
\u63d0\u53d6\u7279\u5b9a\u5217\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u8981\u4f7f\u7528DataFrame\u7684\u5217\u540d\u5373\u53ef\u3002\u5047\u8bbe\u6211\u4eec\u8981\u63d0\u53d6\u540d\u4e3acolumn_name<\/code>\u7684\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
specific_column = df['column_name']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u8be6\u7ec6\u6b65\u9aa4\u548c\u793a\u4f8b<\/h3>\n<\/p>\n
\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u6574\u4e2a\u8fc7\u7a0b\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e2a\u8be6\u7ec6\u7684\u793a\u4f8b\uff0c\u5305\u62ec\u5982\u4f55\u8bfb\u53d6CSV\u6587\u4ef6\u5e76\u63d0\u53d6\u7279\u5b9a\u5217\u3002<\/p>\n<\/p>\n
1. \u793a\u4f8bCSV\u6587\u4ef6\u5185\u5bb9<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3adata.csv<\/code>\u7684CSV\u6587\u4ef6\uff0c\u5185\u5bb9\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
name,age,gender<\/p>\n
Alice,30,F<\/p>\n
Bob,25,M<\/p>\n
Charlie,35,M<\/p>\n
Diana,28,F<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u4f7f\u7528pandas\u8bfb\u53d6CSV\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u63d0\u53d6\u7279\u5b9a\u5217<\/h4>\n<\/p>\n
\u63d0\u53d6age<\/code>\u5217\u7684\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
age_column = df['age']<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u8f93\u51fa\u63d0\u53d6\u7684\u5217<\/h4>\n<\/p>\n
\u53ef\u4ee5\u6253\u5370\u63d0\u53d6\u7684\u5217\u6765\u67e5\u770b\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
print(age_column)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u4e3a\uff1a<\/p>\n<\/p>\n
0    30<\/p>\n
1    25<\/p>\n
2    35<\/p>\n
3    28<\/p>\n
Name: age, dtype: int64<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u64cd\u4f5c\u4e2d\uff0c\u7ecf\u5e38\u4f1a\u9047\u5230\u7f3a\u5931\u503c\u7684\u95ee\u9898\u3002\u5728\u63d0\u53d6\u7279\u5b9a\u5217\u4e4b\u524d\uff0c\u53ef\u4ee5\u5148\u68c0\u67e5\u5e76\u5904\u7406\u7f3a\u5931\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528dropna<\/code>\u51fd\u6570\u6765\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\uff1a<\/p>\n<\/p>\n
df = df.dropna(subset=['age'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u6570\u636e\u7c7b\u578b\u8f6c\u6362<\/h3>\n<\/p>\n
\u6709\u65f6\u63d0\u53d6\u7684\u5217\u6570\u636e\u7c7b\u578b\u53ef\u80fd\u4e0d\u662f\u6211\u4eec\u671f\u671b\u7684\uff0c\u53ef\u4ee5\u4f7f\u7528astype<\/code>\u51fd\u6570\u6765\u8fdb\u884c\u7c7b\u578b\u8f6c\u6362\u3002\u4f8b\u5982\uff0c\u5c06age<\/code>\u5217\u8f6c\u6362\u4e3a\u6574\u6570\u7c7b\u578b\uff1a<\/p>\n<\/p>\n
df['age'] = df['age'].astype(int)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5728Python\u4e2d\u4f7f\u7528pandas\u5e93\u6765\u622a\u53d6CSV\u6570\u636e\u7684\u67d0\u5217\u3002\u6838\u5fc3\u6b65\u9aa4\u5305\u62ec\u5b89\u88c5\u548c\u5bfc\u5165pandas\u5e93\u3001\u8bfb\u53d6CSV\u6587\u4ef6\u3001\u63d0\u53d6\u7279\u5b9a\u5217\u3001\u5904\u7406\u7f3a\u5931\u503c\u548c\u8fdb\u884c\u6570\u636e\u7c7b\u578b\u8f6c\u6362\u3002<\/strong> \u8fd9\u4e9b\u6b65\u9aa4\u4e0d\u4ec5\u9002\u7528\u4e8e\u7b80\u5355\u7684CSV\u6587\u4ef6\u64cd\u4f5c\uff0c\u8fd8\u53ef\u4ee5\u6269\u5c55\u5230\u66f4\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u4efb\u52a1\u3002\u5e0c\u671b\u672c\u6587\u80fd\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u638c\u63e1\u5728Python\u4e2d\u5904\u7406CSV\u6570\u636e\u7684\u6280\u5de7\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6CSV\u6587\u4ef6\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u6216pandas<\/code>\u5e93\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u4f7f\u7528pandas<\/code>\u65f6\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5\u8be5\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7pip install pandas<\/code>\u547d\u4ee4\u6765\u5b89\u88c5\u3002\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u57fa\u672c\u65b9\u6cd5\u662f\u4f7f\u7528pandas.read_csv()<\/code>\u51fd\u6570\u3002\u4f8b\u5982\uff0cdf = pd.read_csv('file.csv')<\/code>\u5c06\u4f1a\u5c06CSV\u6587\u4ef6\u52a0\u8f7d\u5230\u4e00\u4e2aDataFrame\u4e2d\u3002<\/p>\n
\u622a\u53d6\u67d0\u4e00\u5217\u6570\u636e\u7684\u6700\u4f73\u65b9\u6cd5\u662f\u4ec0\u4e48\uff1f<\/strong>
\u4f7f\u7528pandas<\/code>\u5e93\u65f6\uff0c\u622a\u53d6\u67d0\u4e00\u5217\u6570\u636e\u975e\u5e38\u7b80\u5355\u3002\u53ef\u4ee5\u901a\u8fc7DataFrame\u7684\u5217\u540d\u76f4\u63a5\u8bbf\u95ee\u3002\u4f8b\u5982\uff0c\u5982\u679c\u60f3\u8981\u83b7\u53d6\u540d\u4e3a'column_name'<\/code>\u7684\u5217\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528df['column_name']<\/code>\u3002\u8fd9\u5c06\u8fd4\u56de\u4e00\u4e2aSeries\u5bf9\u8c61\uff0c\u5176\u4e2d\u5305\u542b\u8be5\u5217\u7684\u6240\u6709\u6570\u636e\u3002\u6b64\u5916\uff0c\u8fd8\u53ef\u4ee5\u4f7f\u7528df.loc[:, 'column_name']<\/code>\u6765\u8fbe\u5230\u76f8\u540c\u7684\u6548\u679c\uff0c\u5c24\u5176\u5728\u9700\u8981\u8fdb\u884c\u5207\u7247\u65f6\u975e\u5e38\u6709\u7528\u3002<\/p>\n
\u5982\u4f55\u5904\u7406\u7f3a\u5931\u503c\u6216\u5f02\u5e38\u6570\u636e\uff1f<\/strong>
\u5728\u622a\u53d6CSV\u6570\u636e\u7684\u67d0\u5217\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u7f3a\u5931\u503c\u6216\u5f02\u5e38\u6570\u636e\u3002\u4f7f\u7528pandas<\/code>\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7df['column_name'].dropna()<\/code>\u6765\u5220\u9664\u7f3a\u5931\u503c\u3002\u6b64\u5916\uff0c\u5982\u679c\u60f3\u66ff\u6362\u7f3a\u5931\u503c\uff0c\u53ef\u4ee5\u4f7f\u7528df['column_name'].fillna(value)<\/code>\uff0c\u5176\u4e2dvalue<\/code>\u53ef\u4ee5\u662f\u4e00\u4e2a\u5177\u4f53\u7684\u503c\u6216\u8ba1\u7b97\u51fa\u7684\u7edf\u8ba1\u91cf\uff0c\u4f8b\u5982\u5747\u503c\u6216\u4e2d\u4f4d\u6570\u3002\u786e\u4fdd\u5728\u5904\u7406\u6570\u636e\u65f6\u8003\u8651\u8fd9\u4e9b\u5f02\u5e38\u60c5\u51b5\uff0c\u4ee5\u4fdd\u6301\u6570\u636e\u5206\u6790\u7684\u51c6\u786e\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u622a\u53d6CSV\u6570\u636e\u7684\u67d0\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528pandas\u5e93\u6765\u7b80\u5316\u64cd\u4f5c\u3001\u8bfb\u53d6CSV\u6587\u4ef6\u3001\u63d0\u53d6\u7279\u5b9a\u5217\u3002 \u4f7f\u7528pa […]","protected":false},"author":3,"featured_media":1133561,"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\/1133552"}],"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=1133552"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1133552\/revisions"}],"predecessor-version":[{"id":1133564,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1133552\/revisions\/1133564"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1133561"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1133552"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1133552"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1133552"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}