{"id":1120989,"date":"2025-01-08T19:04:15","date_gmt":"2025-01-08T11:04:15","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1120989.html"},"modified":"2025-01-08T19:04:17","modified_gmt":"2025-01-08T11:04:17","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e6%95%b0%e6%8d%ae%e8%be%93%e5%87%ba%e4%b8%ba%e8%a1%a8%e6%a0%bc%e5%bd%a2%e5%bc%8f","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1120989.html","title":{"rendered":"python\u5982\u4f55\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f"},"content":{"rendered":"

\"python\u5982\u4f55\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\"<\/p>\n

Python\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\uff0c\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001PrettyTable\u5e93\u3001Tabulate\u5e93\u3001\u4ee5\u53ca\u76f4\u63a5\u4f7f\u7528CSV\u6a21\u5757\u7b49\u3002<\/strong>\u5176\u4e2d\uff0cPandas\u5e93\u56e0\u4e3a\u5176\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u529f\u80fd\uff0c\u662f\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u4e4b\u4e00\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pandas\u5e93<\/h2>\n<\/p>\n

Pandas\u662fPython\u4e2d\u6700\u6d41\u884c\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5e93\u4e4b\u4e00\u3002\u5b83\u63d0\u4f9b\u4e86DataFrame\u6570\u636e\u7ed3\u6784\uff0c\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u8868\u683c\u5f62\u5f0f\u3002<\/p>\n<\/p>\n

1.1 \u5b89\u88c5Pandas<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86Pandas\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.2 \u521b\u5efaDataFrame<\/h3>\n<\/p>\n
\u521b\u5efa\u4e00\u4e2aDataFrame\u662f\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u8868\u683c\u5f62\u5f0f\u7684\u7b2c\u4e00\u6b65\u3002\u4f60\u53ef\u4ee5\u4ece\u591a\u79cd\u6570\u636e\u6e90\u521b\u5efaDataFrame\uff0c\u5305\u62ec\u5b57\u5178\u3001\u5217\u8868\u3001Excel\u6587\u4ef6\u548cSQL\u6570\u636e\u5e93\u7b49\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u4ece\u5b57\u5178\u521b\u5efaDataFrame<\/strong><\/h2>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [24, 27, 22],<\/p>\n
    'City': ['New York', 'San Francisco', 'Los Angeles']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.3 \u8f93\u51fa\u4e3aCSV\u6587\u4ef6<\/h3>\n<\/p>\n
Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u5c06DataFrame\u8f93\u51fa\u4e3a\u4e0d\u540c\u683c\u5f0f\u7684\u6587\u4ef6\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u662fCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
# \u8f93\u51fa\u4e3aCSV\u6587\u4ef6<\/p>\n
df.to_csv('output.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.4 \u8f93\u51fa\u4e3aExcel\u6587\u4ef6<\/h3>\n<\/p>\n
Pandas\u4e5f\u53ef\u4ee5\u5c06DataFrame\u8f93\u51fa\u4e3aExcel\u6587\u4ef6\uff0c\u524d\u63d0\u662f\u9700\u8981\u5b89\u88c5openpyxl<\/code>\u5e93\u3002<\/p>\n<\/p>\n
pip install openpyxl<\/p>\n
<\/code><\/pre>\n<\/p>\n
# \u8f93\u51fa\u4e3aExcel\u6587\u4ef6<\/p>\n
df.to_excel('output.xlsx', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528PrettyTable\u5e93<\/h2>\n<\/p>\n
PrettyTable\u5e93\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u5c06\u6570\u636e\u683c\u5f0f\u5316\u4e3a\u6f02\u4eae\u7684\u8868\u683c\u5f62\u5f0f\uff0c\u9002\u5408\u5728\u63a7\u5236\u53f0\u8f93\u51fa\u3002<\/p>\n<\/p>\n
2.1 \u5b89\u88c5PrettyTable<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u5b89\u88c5PrettyTable\u5e93\uff1a<\/p>\n<\/p>\n
pip install prettytable<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.2 \u521b\u5efaPrettyTable\u5bf9\u8c61<\/h3>\n<\/p>\n
\u521b\u5efaPrettyTable\u5bf9\u8c61\u5e76\u6dfb\u52a0\u6570\u636e\u3002<\/p>\n<\/p>\n
from prettytable import PrettyTable<\/p>\n
\u521b\u5efaPrettyTable\u5bf9\u8c61<\/strong><\/h2>\n
table = PrettyTable()<\/p>\n
\u6dfb\u52a0\u5217<\/strong><\/h2>\n
table.field_names = ["Name", "Age", "City"]<\/p>\n
table.add_row(["Alice", 24, "New York"])<\/p>\n
table.add_row(["Bob", 27, "San Francisco"])<\/p>\n
table.add_row(["Charlie", 22, "Los Angeles"])<\/p>\n
print(table)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Tabulate\u5e93<\/h2>\n<\/p>\n
Tabulate\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u8868\u683c\u6837\u5f0f\uff0c\u53ef\u4ee5\u5c06\u6570\u636e\u683c\u5f0f\u5316\u4e3a\u4e0d\u540c\u98ce\u683c\u7684\u8868\u683c\u3002<\/p>\n<\/p>\n
3.1 \u5b89\u88c5Tabulate<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u5b89\u88c5Tabulate\u5e93\uff1a<\/p>\n<\/p>\n
pip install tabulate<\/p>\n
<\/code><\/pre>\n<\/p>\n
3.2 \u4f7f\u7528Tabulate\u683c\u5f0f\u5316\u6570\u636e<\/h3>\n<\/p>\n
\u4f7f\u7528Tabulate\u5e93\u5c06\u6570\u636e\u683c\u5f0f\u5316\u4e3a\u8868\u683c\u5f62\u5f0f\u3002<\/p>\n<\/p>\n
from tabulate import tabulate<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
data = [<\/p>\n
    ["Alice", 24, "New York"],<\/p>\n
    ["Bob", 27, "San Francisco"],<\/p>\n
    ["Charlie", 22, "Los Angeles"]<\/p>\n
]<\/p>\n
\u8868\u5934<\/strong><\/h2>\n
headers = ["Name", "Age", "City"]<\/p>\n
print(tabulate(data, headers, tablefmt="grid"))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528CSV\u6a21\u5757<\/h2>\n<\/p>\n
Python\u7684\u5185\u7f6eCSV\u6a21\u5757\u4e5f\u53ef\u4ee5\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\uff0c\u9002\u5408\u7b80\u5355\u7684CSV\u6587\u4ef6\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
4.1 \u5bfc\u5165CSV\u6a21\u5757<\/h3>\n<\/p>\n
\u4f7f\u7528CSV\u6a21\u5757\u5c06\u6570\u636e\u8f93\u51fa\u4e3aCSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
import csv<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
data = [<\/p>\n
    ["Name", "Age", "City"],<\/p>\n
    ["Alice", 24, "New York"],<\/p>\n
    ["Bob", 27, "San Francisco"],<\/p>\n
    ["Charlie", 22, "Los Angeles"]<\/p>\n
]<\/p>\n
\u8f93\u51fa\u4e3aCSV\u6587\u4ef6<\/strong><\/h2>\n
with open('output.csv', 'w', newline='') as file:<\/p>\n
    writer = csv.writer(file)<\/p>\n
    writer.writerows(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u7efc\u5408\u4f7f\u7528<\/h2>\n<\/p>\n
\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\uff0c\u4f60\u53ef\u80fd\u9700\u8981\u7efc\u5408\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\u3002\u6bd4\u5982\uff0c\u4f60\u53ef\u4ee5\u5148\u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u5904\u7406\uff0c\u7136\u540e\u4f7f\u7528PrettyTable\u6216Tabulate\u5e93\u5c06\u7ed3\u679c\u683c\u5f0f\u5316\u4e3a\u6f02\u4eae\u7684\u8868\u683c\u3002<\/p>\n<\/p>\n
5.1 \u7efc\u5408\u793a\u4f8b<\/h3>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7efc\u5408\u793a\u4f8b\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528Pandas\u5904\u7406\u6570\u636e\uff0c\u5e76\u4f7f\u7528Tabulate\u5e93\u5c06\u7ed3\u679c\u683c\u5f0f\u5316\u8f93\u51fa\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
from tabulate import tabulate<\/p>\n
\u521b\u5efaDataFrame<\/strong><\/h2>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [24, 27, 22],<\/p>\n
    'City': ['New York', 'San Francisco', 'Los Angeles']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u6570\u636e\u5904\u7406\uff08\u4f8b\u5982\u7b5b\u9009\u5e74\u9f84\u5927\u4e8e23\u7684\u4eba\uff09<\/strong><\/h2>\n
filtered_df = df[df['Age'] > 23]<\/p>\n
\u4f7f\u7528Tabulate\u683c\u5f0f\u5316\u8f93\u51fa<\/strong><\/h2>\n
print(tabulate(filtered_df, headers='keys', tablefmt='grid'))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u7075\u6d3b\u5730\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\uff0c\u5e76\u6839\u636e\u9700\u8981\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u683c\u5f0f\u5316\u3002\u8fd9\u4e9b\u65b9\u6cd5\u4e0d\u4ec5\u9002\u7528\u4e8e\u7b80\u5355\u7684\u6570\u636e\u8f93\u51fa\uff0c\u8fd8\u53ef\u4ee5\u7528\u4e8e\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u548c\u62a5\u544a\u751f\u6210\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\uff1f<\/strong>
Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5e93\u6765\u5c06\u6570\u636e\u5bfc\u51fa\u4e3aCSV\u683c\u5f0f\uff0c\u4f8b\u5982pandas<\/code>\u5e93\u3002\u4f7f\u7528pandas<\/code>\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06DataFrame\u5bf9\u8c61\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\u3002\u53ea\u9700\u4f7f\u7528to_csv()<\/code>\u65b9\u6cd5\uff0c\u5e76\u6307\u5b9a\u6587\u4ef6\u540d\u548c\u5176\u4ed6\u53c2\u6570\uff0c\u5982\u5206\u9694\u7b26\u548c\u662f\u5426\u5305\u542b\u7d22\u5f15\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n
import pandas as pd\n\ndata = {'\u59d3\u540d': ['\u5f20\u4e09', '\u674e\u56db'], '\u5e74\u9f84': [28, 22]}\ndf = pd.DataFrame(data)\ndf.to_csv('output.csv', index=False)\n<\/code><\/pre>\n
\u5728Python\u4e2d\u5982\u4f55\u5c06\u6570\u636e\u8f6c\u6362\u4e3aExcel\u683c\u5f0f\uff1f<\/strong>
\u5982\u679c\u9700\u8981\u5c06\u6570\u636e\u8f93\u51fa\u4e3aExcel\u6587\u4ef6\uff0cpandas<\/code>\u5e93\u540c\u6837\u53ef\u4ee5\u5b8c\u6210\u8fd9\u9879\u4efb\u52a1\u3002\u4f7f\u7528to_excel()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5c06DataFrame\u76f4\u63a5\u4fdd\u5b58\u4e3aExcel\u6587\u4ef6\u3002\u786e\u4fdd\u5b89\u88c5\u4e86openpyxl<\/code>\u6216xlsxwriter<\/code>\u7b49\u5e93\u4f5c\u4e3aExcel\u6587\u4ef6\u7684\u5f15\u64ce\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
import pandas as pd\n\ndata = {'\u59d3\u540d': ['\u5f20\u4e09', '\u674e\u56db'], '\u5e74\u9f84': [28, 22]}\ndf = pd.DataFrame(data)\ndf.to_excel('output.xlsx', index=False)\n<\/code><\/pre>\n
\u6709\u6ca1\u6709\u5176\u4ed6\u65b9\u6cd5\u53ef\u4ee5\u5728Python\u4e2d\u521b\u5efa\u8868\u683c\uff1f<\/strong>
\u9664\u4e86\u4f7f\u7528pandas<\/code>\uff0c\u8fd8\u53ef\u4ee5\u501f\u52a9PrettyTable<\/code>\u5e93\u6765\u5728\u63a7\u5236\u53f0\u4e2d\u4ee5\u8868\u683c\u5f62\u5f0f\u8f93\u51fa\u6570\u636e\u3002PrettyTable<\/code>\u5141\u8bb8\u7528\u6237\u521b\u5efa\u7f8e\u89c2\u7684ASCII\u8868\u683c\uff0c\u5e76\u652f\u6301\u591a\u79cd\u683c\u5f0f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a  <\/p>\n
from prettytable import PrettyTable\n\ntable = PrettyTable()\ntable.field_names = ["\u59d3\u540d", "\u5e74\u9f84"]\ntable.add_row(["\u5f20\u4e09", 28])\ntable.add_row(["\u674e\u56db", 22])\nprint(table)\n<\/code><\/pre>\n
\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u7528\u6237\u53ef\u4ee5\u7075\u6d3b\u5730\u5c06\u6570\u636e\u4ee5\u8868\u683c\u5f62\u5f0f\u8f93\u51fa\uff0c\u6ee1\u8db3\u4e0d\u540c\u7684\u9700\u6c42\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5c06\u6570\u636e\u8f93\u51fa\u4e3a\u8868\u683c\u5f62\u5f0f\uff0c\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001PrettyTable\u5e93\u3001Tabula […]","protected":false},"author":3,"featured_media":1121000,"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\/1120989"}],"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=1120989"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1120989\/revisions"}],"predecessor-version":[{"id":1121001,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1120989\/revisions\/1121001"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1121000"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1120989"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1120989"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1120989"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}