{"id":1079439,"date":"2025-01-08T12:20:55","date_gmt":"2025-01-08T04:20:55","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1079439.html"},"modified":"2025-01-08T12:20:58","modified_gmt":"2025-01-08T04:20:58","slug":"python%e5%a6%82%e4%bd%95%e7%bb%99%e5%af%bc%e5%85%a5%e7%9a%84%e6%95%b0%e6%8d%ae%e6%b7%bb%e5%8a%a0%e8%a1%a8%e5%a4%b4-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1079439.html","title":{"rendered":"python\u5982\u4f55\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934"},"content":{"rendered":"

\"python\u5982\u4f55\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\"<\/p>\n

Python\u5982\u4f55\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934<\/strong><\/p>\n<\/p>\n

\u5728Python\u4e2d\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u3002\u5229\u7528Pandas\u5e93\u5bfc\u5165\u6570\u636e\u3001\u4f7f\u7528columns\u53c2\u6570\u8bbe\u7f6e\u8868\u5934\u3001\u624b\u52a8\u6dfb\u52a0\u8868\u5934<\/strong>\u3002\u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u5229\u7528Pandas\u5e93\u5bfc\u5165\u6570\u636e\u65f6\u76f4\u63a5\u8bbe\u7f6ecolumns\u53c2\u6570\uff0c\u8fd9\u6837\u53ef\u4ee5\u5728\u8bfb\u53d6\u6570\u636e\u7684\u540c\u65f6\u76f4\u63a5\u7ed9\u6570\u636e\u6dfb\u52a0\u8868\u5934\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u901a\u8fc7\u8fd9\u51e0\u79cd\u65b9\u6cd5\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5229\u7528Pandas\u5e93\u5bfc\u5165\u6570\u636e<\/p>\n<\/p>\n

Pandas\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5e93\uff0c\u80fd\u591f\u65b9\u4fbf\u5730\u5bfc\u5165\u548c\u5904\u7406\u5404\u79cd\u683c\u5f0f\u7684\u6570\u636e\u3002\u5bfc\u5165\u6570\u636e\u65f6\uff0c\u53ef\u4ee5\u76f4\u63a5\u8bbe\u7f6e\u8868\u5934\u3002\u4f8b\u5982\uff0c\u5bfc\u5165CSV\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7read_csv\u51fd\u6570\u7684header\u53c2\u6570\u548cnames\u53c2\u6570\u6765\u8bbe\u7f6e\u8868\u5934\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
\u5bfc\u5165\u6570\u636e\u5e76\u8bbe\u7f6e\u8868\u5934<\/strong><\/h2>\n
data = pd.read_csv('data.csv', header=None, names=['Column1', 'Column2', 'Column3'])<\/p>\n
print(data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u4e86read_csv\u51fd\u6570\uff0c\u5e76\u901a\u8fc7header=None\u53c2\u6570\u8868\u793aCSV\u6587\u4ef6\u4e2d\u6ca1\u6709\u8868\u5934\uff0c\u7136\u540e\u901a\u8fc7names\u53c2\u6570\u8bbe\u7f6e\u8868\u5934\u3002\u8fd9\u6837\u5bfc\u5165\u7684\u6570\u636e\u5c31\u4f1a\u6709\u6307\u5b9a\u7684\u8868\u5934\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528columns\u53c2\u6570\u8bbe\u7f6e\u8868\u5934<\/p>\n<\/p>\n
\u5982\u679c\u6570\u636e\u5df2\u7ecf\u5bfc\u5165\uff0c\u4f46\u6ca1\u6709\u8868\u5934\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6eDataFrame\u7684columns\u5c5e\u6027\u6765\u6dfb\u52a0\u8868\u5934\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5bfc\u5165\u6570\u636e<\/strong><\/h2>\n
data = pd.read_csv('data.csv', header=None)<\/p>\n
\u8bbe\u7f6e\u8868\u5934<\/strong><\/h2>\n
data.columns = ['Column1', 'Column2', 'Column3']<\/p>\n
print(data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u9996\u5148\u5bfc\u5165\u6570\u636e\uff0c\u7136\u540e\u901a\u8fc7\u8bbe\u7f6edata.columns\u5c5e\u6027\u6765\u6dfb\u52a0\u8868\u5934\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u624b\u52a8\u6dfb\u52a0\u8868\u5934<\/p>\n<\/p>\n
\u5982\u679c\u4f60\u60f3\u624b\u52a8\u6dfb\u52a0\u8868\u5934\uff0c\u53ef\u4ee5\u5148\u5c06\u6570\u636e\u5bfc\u5165\u4e3aDataFrame\u5bf9\u8c61\uff0c\u7136\u540e\u901a\u8fc7\u63d2\u5165\u65b0\u7684\u884c\u6765\u6dfb\u52a0\u8868\u5934\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5bfc\u5165\u6570\u636e<\/strong><\/h2>\n
data = pd.read_csv('data.csv', header=None)<\/p>\n
\u624b\u52a8\u6dfb\u52a0\u8868\u5934<\/strong><\/h2>\n
header = pd.DataFrame([['Column1', 'Column2', 'Column3']])<\/p>\n
data = pd.concat([header, data], ignore_index=True)<\/p>\n
print(data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u9002\u7528\u4e8e\u9700\u8981\u624b\u52a8\u64cd\u4f5c\u7684\u60c5\u51b5\uff0c\u5c06\u8868\u5934\u4f5c\u4e3a\u4e00\u4e2a\u65b0\u7684DataFrame\u63d2\u5165\u5230\u539f\u6570\u636e\u7684\u9876\u90e8\u3002<\/p>\n<\/p>\n
\u56db\u3001\u5982\u4f55\u5728\u4e0d\u540c\u573a\u666f\u4e0b\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5<\/p>\n<\/p>\n
\u5728\u4e0d\u540c\u7684\u573a\u666f\u4e0b\uff0c\u53ef\u4ee5\u6839\u636e\u6570\u636e\u6765\u6e90\u548c\u683c\u5f0f\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\u3002<\/p>\n<\/p>\n
1\u3001\u5bfc\u5165CSV\u6587\u4ef6\u65f6<\/p>\n<\/p>\n
\u5f53\u5bfc\u5165CSV\u6587\u4ef6\u65f6\uff0c\u901a\u5e38\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528read_csv\u51fd\u6570\u7684\u53c2\u6570\u8bbe\u7f6e\u8868\u5934\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5177\u4f53\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5bfc\u5165CSV\u6587\u4ef6\u5e76\u8bbe\u7f6e\u8868\u5934<\/strong><\/h2>\n
data = pd.read_csv('data.csv', header=0, names=['Name', 'Age', 'Gender'])<\/p>\n
print(data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0cheader=0\u8868\u793a\u7b2c\u4e00\u884c\u4e3a\u8868\u5934\uff0cnames\u53c2\u6570\u91cd\u65b0\u5b9a\u4e49\u4e86\u8868\u5934\u3002<\/p>\n<\/p>\n
2\u3001\u5bfc\u5165Excel\u6587\u4ef6\u65f6<\/p>\n<\/p>\n
\u5bfc\u5165Excel\u6587\u4ef6\u65f6\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u7684read_excel\u51fd\u6570\u8bbe\u7f6e\u8868\u5934\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5bfc\u5165Excel\u6587\u4ef6\u5e76\u8bbe\u7f6e\u8868\u5934<\/strong><\/h2>\n
data = pd.read_excel('data.xlsx', header=0)<\/p>\n
data.columns = ['Name', 'Age', 'Gender']<\/p>\n
print(data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0cread_excel\u51fd\u6570\u4f1a\u81ea\u52a8\u8bc6\u522bExcel\u6587\u4ef6\u7684\u8868\u5934\uff0c\u7136\u540e\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6ecolumns\u5c5e\u6027\u6765\u91cd\u65b0\u5b9a\u4e49\u8868\u5934\u3002<\/p>\n<\/p>\n
3\u3001\u5bfc\u5165\u6570\u636e\u5e93\u6570\u636e\u65f6<\/p>\n<\/p>\n
\u5f53\u4ece\u6570\u636e\u5e93\u5bfc\u5165\u6570\u636e\u65f6\uff0c\u901a\u5e38\u4e0d\u4f1a\u76f4\u63a5\u6709\u8868\u5934\u4fe1\u606f\uff0c\u9700\u8981\u624b\u52a8\u8bbe\u7f6e\u8868\u5934\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import sqlite3<\/p>\n
\u8fde\u63a5\u5230SQLite\u6570\u636e\u5e93<\/strong><\/h2>\n
conn = sqlite3.connect('database.db')<\/p>\n
\u5bfc\u5165\u6570\u636e<\/strong><\/h2>\n
data = pd.read_sql_query('SELECT * FROM table_name', conn)<\/p>\n
\u8bbe\u7f6e\u8868\u5934<\/strong><\/h2>\n
data.columns = ['ID', 'Name', 'Age', 'Gender']<\/p>\n
print(data.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u4eceSQLite\u6570\u636e\u5e93\u5bfc\u5165\u6570\u636e\u540e\uff0c\u901a\u8fc7\u8bbe\u7f6ecolumns\u5c5e\u6027\u6dfb\u52a0\u8868\u5934\u3002<\/p>\n<\/p>\n
\u56db\u3001\u5904\u7406\u5927\u578b\u6570\u636e\u96c6<\/p>\n<\/p>\n
\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u80fd\u9700\u8981\u66f4\u52a0\u9ad8\u6548\u7684\u65b9\u6cd5\u6765\u6dfb\u52a0\u8868\u5934\u3002\u4f8b\u5982\uff0c\u4f7f\u7528chunksize\u53c2\u6570\u5206\u5757\u8bfb\u53d6\u6570\u636e\uff0c\u53ef\u4ee5\u51cf\u5c11\u5185\u5b58\u5360\u7528\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5206\u5757\u8bfb\u53d6\u6570\u636e\u5e76\u8bbe\u7f6e\u8868\u5934<\/strong><\/h2>\n
chunks = pd.read_csv('large_data.csv', chunksize=10000, header=None, names=['Column1', 'Column2', 'Column3'])<\/p>\n
\u5904\u7406\u6bcf\u4e2a\u6570\u636e\u5757<\/strong><\/h2>\n
for chunk in chunks:<\/p>\n
    print(chunk.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u4f7f\u7528chunksize\u53c2\u6570\u5206\u5757\u8bfb\u53d6\u6570\u636e\uff0c\u5e76\u5728\u8bfb\u53d6\u65f6\u8bbe\u7f6e\u8868\u5934\u3002\u8fd9\u6837\u53ef\u4ee5\u66f4\u52a0\u9ad8\u6548\u5730\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n
\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\u662f\u6570\u636e\u5904\u7406\u4e2d\u7684\u5e38\u89c1\u64cd\u4f5c\uff0cPandas\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u5b9e\u73b0\u8fd9\u4e00\u529f\u80fd\u3002\u5229\u7528Pandas\u5e93\u5bfc\u5165\u6570\u636e\u3001\u4f7f\u7528columns\u53c2\u6570\u8bbe\u7f6e\u8868\u5934\u3001\u624b\u52a8\u6dfb\u52a0\u8868\u5934<\/strong>\u662f\u5e38\u7528\u7684\u4e09\u79cd\u65b9\u6cd5\u3002\u5728\u4e0d\u540c\u7684\u573a\u666f\u4e0b\uff0c\u53ef\u4ee5\u6839\u636e\u6570\u636e\u6765\u6e90\u548c\u683c\u5f0f\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u3002\u6b64\u5916\uff0c\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u5206\u5757\u8bfb\u53d6\u7684\u65b9\u6cd5\u6765\u63d0\u9ad8\u6548\u7387\u3002\u901a\u8fc7\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\uff0c\u4ece\u800c\u66f4\u597d\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\u4e3a\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u65b9\u4fbf\u5730\u4e3a\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\u3002\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9acolumns<\/code>\u53c2\u6570\u5728\u8bfb\u53d6\u6570\u636e\u65f6\u76f4\u63a5\u8bbe\u7f6e\u8868\u5934\uff0c\u6216\u8005\u5728\u5bfc\u5165\u6570\u636e\u540e\u4f7f\u7528DataFrame.columns<\/code>\u5c5e\u6027\u6765\u4fee\u6539\u8868\u5934\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a  <\/p>\n
import pandas as pd\n\n# \u8bfb\u53d6\u6570\u636e\u5e76\u6dfb\u52a0\u8868\u5934\ndata = pd.read_csv('data.csv', header=None, names=['\u5217\u540d1', '\u5217\u540d2', '\u5217\u540d3'])\n<\/code><\/pre>\n
\u5728\u4f7f\u7528Excel\u6587\u4ef6\u65f6\uff0c\u5982\u4f55\u4e3a\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\uff1f<\/strong>
\u5904\u7406Excel\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u540c\u6837\u4f7f\u7528Pandas\u5e93\u7684read_excel<\/code>\u51fd\u6570\u3002\u901a\u8fc7\u8bbe\u7f6eheader=None<\/code>\uff0c\u53ef\u4ee5\u5728\u5bfc\u5165\u65f6\u6307\u5b9a\u65b0\u8868\u5934\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n
import pandas as pd\n\n# \u8bfb\u53d6Excel\u6587\u4ef6\u5e76\u6dfb\u52a0\u8868\u5934\ndata = pd.read_excel('data.xlsx', header=None, names=['\u5217\u540d1', '\u5217\u540d2', '\u5217\u540d3'])\n<\/code><\/pre>\n
\u5982\u679c\u6570\u636e\u5df2\u7ecf\u5bfc\u5165\uff0c\u5982\u4f55\u4fee\u6539\u5df2\u5b58\u5728\u7684\u8868\u5934\uff1f<\/strong>
\u5728\u6570\u636e\u5df2\u7ecf\u5bfc\u5165\u540e\uff0c\u53ef\u4ee5\u76f4\u63a5\u4fee\u6539DataFrame<\/code>\u7684columns<\/code>\u5c5e\u6027\u3002\u53ef\u4ee5\u7528\u4e00\u4e2a\u5305\u542b\u65b0\u5217\u540d\u7684\u5217\u8868\u6765\u66ff\u6362\u73b0\u6709\u7684\u5217\u540d\u3002\u4ee5\u4e0b\u662f\u4ee3\u7801\u793a\u4f8b\uff1a  <\/p>\n
import pandas as pd\n\n# \u5047\u8bbedata\u662f\u5df2\u5bfc\u5165\u7684\u6570\u636e\ndata.columns = ['\u65b0\u5217\u540d1', '\u65b0\u5217\u540d2', '\u65b0\u5217\u540d3']\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"Python\u5982\u4f55\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934 \u5728Python\u4e2d\u7ed9\u5bfc\u5165\u7684\u6570\u636e\u6dfb\u52a0\u8868\u5934\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u3002\u5229\u7528Pan […]","protected":false},"author":3,"featured_media":1079449,"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\/1079439"}],"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=1079439"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1079439\/revisions"}],"predecessor-version":[{"id":1079453,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1079439\/revisions\/1079453"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1079449"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1079439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1079439"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1079439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}