{"id":1057617,"date":"2024-12-31T15:09:31","date_gmt":"2024-12-31T07:09:31","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1057617.html"},"modified":"2024-12-31T15:09:33","modified_gmt":"2024-12-31T07:09:33","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e6%95%b0%e6%8d%ae%e6%95%b4%e7%90%86%e6%88%90%e8%a1%a8%e6%a0%bc","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1057617.html","title":{"rendered":"python\u5982\u4f55\u5c06\u6570\u636e\u6574\u7406\u6210\u8868\u683c"},"content":{"rendered":"

\"python\u5982\u4f55\u5c06\u6570\u636e\u6574\u7406\u6210\u8868\u683c\"<\/p>\n

Python\u5c06\u6570\u636e\u6574\u7406\u6210\u8868\u683c\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001PrettyTable\u5e93\u3001Tabulate\u5e93\u3001csv\u6a21\u5757\u3002<\/strong>\u5176\u4e2d\uff0cPandas\u5e93\u662f\u6700\u5e38\u7528\u7684\uff0c\u56e0\u4e3a\u5b83\u529f\u80fd\u5f3a\u5927\uff0c\u652f\u6301\u591a\u79cd\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u3002Pandas\u4e0d\u4ec5\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u5b58\u50a8\u6570\u636e\uff0c\u8fd8\u80fd\u591f\u5c06\u6570\u636e\u4ee5\u8868\u683c\u7684\u5f62\u5f0f\u5c55\u793a\u51fa\u6765\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u6765\u6574\u7406\u6570\u636e\u6210\u8868\u683c\u3002<\/p>\n<\/p>\n

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

Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u548c\u6570\u636e\u5904\u7406\u5de5\u5177\u5e93\uff0c\u5e7f\u6cdb\u7528\u4e8e\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60<\/a>\u9886\u57df\u3002\u5b83\u7684\u6838\u5fc3\u6570\u636e\u7ed3\u6784\u662fDataFrame\uff0c\u7c7b\u4f3c\u4e8eExcel\u4e2d\u7684\u8868\u683c\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Pandas\u5e93<\/h3>\n<\/p>\n

\u5728\u4f7f\u7528Pandas\u5e93\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5\u8be5\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Pandas\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u521b\u5efaDataFrame<\/h3>\n<\/p>\n
DataFrame\u662fPandas\u4e2d\u6700\u91cd\u8981\u7684\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u4e8c\u7ef4\u8868\u683c\u6570\u636e\u3002\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u521b\u5efaDataFrame\uff0c\u4f8b\u5982\u4ece\u5b57\u5178\u3001\u5217\u8868\u3001CSV\u6587\u4ef6\u7b49\u3002\u4ee5\u4e0b\u662f\u51e0\u79cd\u5e38\u89c1\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
\u4ece\u5b57\u5178\u521b\u5efaDataFrame<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [24, 27, 22],<\/p>\n
    'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ece\u5217\u8868\u521b\u5efaDataFrame<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n
data = [<\/p>\n
    ['Alice', 24, 'New York'],<\/p>\n
    ['Bob', 27, 'Los Angeles'],<\/p>\n
    ['Charlie', 22, 'Chicago']<\/p>\n
]<\/p>\n
df = pd.DataFrame(data, columns=['Name', 'Age', 'City'])<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4eceCSV\u6587\u4ef6\u521b\u5efaDataFrame<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u64cd\u4f5c\u548c\u5904\u7406DataFrame<\/h3>\n<\/p>\n
Pandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u64cd\u4f5c\u548c\u5904\u7406DataFrame\u7684\u65b9\u6cd5\uff0c\u4f8b\u5982\u7b5b\u9009\u3001\u6392\u5e8f\u3001\u5206\u7ec4\u3001\u805a\u5408\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n
\u7b5b\u9009\u6570\u636e<\/h4>\n<\/p>\n
# \u7b5b\u9009\u5e74\u9f84\u5927\u4e8e25\u7684\u6570\u636e<\/p>\n
filtered_df = df[df['Age'] > 25]<\/p>\n
print(filtered_df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6392\u5e8f\u6570\u636e<\/h4>\n<\/p>\n
# \u6309\u5e74\u9f84\u5347\u5e8f\u6392\u5e8f<\/p>\n
sorted_df = df.sort_values(by='Age')<\/p>\n
print(sorted_df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5206\u7ec4\u548c\u805a\u5408\u6570\u636e<\/h4>\n<\/p>\n
# \u6309\u57ce\u5e02\u5206\u7ec4\uff0c\u5e76\u8ba1\u7b97\u5e73\u5747\u5e74\u9f84<\/p>\n
grouped_df = df.groupby('City').mean()<\/p>\n
print(grouped_df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5c06DataFrame\u8f6c\u6362\u4e3a\u5176\u4ed6\u683c\u5f0f<\/h3>\n<\/p>\n
Pandas\u8fd8\u53ef\u4ee5\u5c06DataFrame\u8f6c\u6362\u4e3a\u5176\u4ed6\u683c\u5f0f\uff0c\u4f8b\u5982CSV\u6587\u4ef6\u3001Excel\u6587\u4ef6\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u8f6c\u6362\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
\u8f6c\u6362\u4e3aCSV\u6587\u4ef6<\/h4>\n<\/p>\n
df.to_csv('output.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f6c\u6362\u4e3aExcel\u6587\u4ef6<\/h4>\n<\/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\u662f\u4e00\u4e2a\u7528\u4e8e\u5728\u7ec8\u7aef\u6253\u5370\u6f02\u4eae\u8868\u683c\u7684\u5e93\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u5c55\u793a\u5c0f\u89c4\u6a21\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528PrettyTable\u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5PrettyTable\u5e93<\/h3>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5PrettyTable\uff1a<\/p>\n<\/p>\n
pip install prettytable<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u521b\u5efaPrettyTable<\/h3>\n<\/p>\n
\u4ee5\u4e0b\u662f\u521b\u5efa\u5e76\u5c55\u793a\u4e00\u4e2aPrettyTable\u7684\u793a\u4f8b\uff1a<\/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.add_column('Name', ['Alice', 'Bob', 'Charlie'])<\/p>\n
table.add_column('Age', [24, 27, 22])<\/p>\n
table.add_column('City', ['New York', 'Los Angeles', 'Chicago'])<\/p>\n
\u6253\u5370\u8868\u683c<\/strong><\/h2>\n
print(table)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Tabulate\u5e93<\/h2>\n<\/p>\n
Tabulate\u662f\u53e6\u4e00\u4e2a\u7528\u4e8e\u5728\u7ec8\u7aef\u6253\u5370\u6f02\u4eae\u8868\u683c\u7684\u5e93\uff0c\u652f\u6301\u591a\u79cd\u8f93\u51fa\u683c\u5f0f\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Tabulate\u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5Tabulate\u5e93<\/h3>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Tabulate\uff1a<\/p>\n<\/p>\n
pip install tabulate<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Tabulate\u521b\u5efa\u8868\u683c<\/h3>\n<\/p>\n
\u4ee5\u4e0b\u662f\u521b\u5efa\u5e76\u5c55\u793a\u4e00\u4e2aTabulate\u8868\u683c\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from tabulate import tabulate<\/p>\n
data = [<\/p>\n
    ['Alice', 24, 'New York'],<\/p>\n
    ['Bob', 27, 'Los Angeles'],<\/p>\n
    ['Charlie', 22, 'Chicago']<\/p>\n
]<\/p>\n
\u6253\u5370\u8868\u683c<\/strong><\/h2>\n
print(tabulate(data, headers=['Name', 'Age', 'City']))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528csv\u6a21\u5757<\/h2>\n<\/p>\n
csv\u6a21\u5757\u662fPython\u5185\u7f6e\u7684\u7528\u4e8e\u5904\u7406CSV\u6587\u4ef6\u7684\u6a21\u5757\u3002\u867d\u7136\u5b83\u4e0d\u5982Pandas\u529f\u80fd\u5f3a\u5927\uff0c\u4f46\u5bf9\u4e8e\u7b80\u5355\u7684CSV\u64cd\u4f5c\u5df2\u7ecf\u8db3\u591f\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528csv\u6a21\u5757\u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
import csv<\/p>\n
with open('data.csv', mode='r') as file:<\/p>\n
    reader = csv.reader(file)<\/p>\n
    for row in reader:<\/p>\n
        print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5199\u5165CSV\u6587\u4ef6<\/h3>\n<\/p>\n
import csv<\/p>\n
data = [<\/p>\n
    ['Name', 'Age', 'City'],<\/p>\n
    ['Alice', 24, 'New York'],<\/p>\n
    ['Bob', 27, 'Los Angeles'],<\/p>\n
    ['Charlie', 22, 'Chicago']<\/p>\n
]<\/p>\n
with open('output.csv', mode='w', newline='') as file:<\/p>\n
    writer = csv.writer(file)<\/p>\n
    writer.writerows(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h2>\n<\/p>\n
\u901a\u8fc7\u4e0a\u9762\u7684\u4ecb\u7ecd\uff0c\u5df2\u7ecf\u8be6\u7ec6\u8bb2\u89e3\u4e86\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u3001PrettyTable\u5e93\u3001Tabulate\u5e93\u548ccsv\u6a21\u5757\u5c06\u6570\u636e\u6574\u7406\u6210\u8868\u683c\u3002Pandas\u5e93\u529f\u80fd\u6700\u4e3a\u5f3a\u5927\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u7684\u5904\u7406\u548c\u5206\u6790<\/strong>\uff0cPrettyTable\u548cTabulate\u5e93\u9002\u5408\u4e8e\u5c55\u793a\u5c0f\u89c4\u6a21\u6570\u636e<\/strong>\uff0ccsv\u6a21\u5757\u5219\u9002\u5408\u4e8e\u7b80\u5355\u7684CSV\u6587\u4ef6\u64cd\u4f5c<\/strong>\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u5c06\u6570\u636e\u6574\u7406\u6210\u8868\u683c\uff0c\u4fbf\u4e8e\u540e\u7eed\u7684\u5206\u6790\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u5c06\u6570\u636e\u5bfc\u5165\u5230\u8868\u683c\u4e2d\uff1f<\/strong>
\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u8f7b\u677e\u5c06\u6570\u636e\u5bfc\u5165\u5230\u8868\u683c\u4e2d\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5c06\u6570\u636e\u52a0\u8f7d\u5230DataFrame\u4e2d\uff0c\u4f8b\u5982\u4eceCSV\u6216Excel\u6587\u4ef6\u3002\u63a5\u7740\uff0c\u5229\u7528Pandas\u7684to_excel()<\/code>\u6216to_csv()<\/code>\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5c06DataFrame\u4fdd\u5b58\u4e3a\u8868\u683c\u6587\u4ef6\u3002\u786e\u4fdd\u5728\u4f7f\u7528\u524d\u5b89\u88c5Pandas\u5e93\uff0c\u5e76\u5bfc\u5165\u5b83\u3002<\/p>\n
\u5728Python\u4e2d\uff0c\u5982\u4f55\u6e05\u6d17\u548c\u6574\u7406\u6570\u636e\u4ee5\u4fbf\u4e8e\u8868\u683c\u5316\uff1f<\/strong>
\u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u6574\u7406\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u4f7f\u7528Pandas\u5e93\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7dropna()<\/code>\u65b9\u6cd5\u53bb\u9664\u7f3a\u5931\u503c\uff0c\u4f7f\u7528fillna()<\/code>\u586b\u8865\u7f3a\u5931\u6570\u636e\uff0c\u6216\u8005\u901a\u8fc7astype()<\/code>\u65b9\u6cd5\u8f6c\u6362\u6570\u636e\u7c7b\u578b\u3002\u8fd9\u4e9b\u65b9\u6cd5\u6709\u52a9\u4e8e\u786e\u4fdd\u6570\u636e\u5728\u8868\u683c\u4e2d\u8868\u73b0\u826f\u597d\uff0c\u5e76\u4fbf\u4e8e\u8fdb\u4e00\u6b65\u5206\u6790\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u4e00\u4e2a\u81ea\u5b9a\u4e49\u683c\u5f0f\u7684\u8868\u683c\uff1f<\/strong>
\u5982\u679c\u60a8\u60f3\u8981\u521b\u5efa\u81ea\u5b9a\u4e49\u683c\u5f0f\u7684\u8868\u683c\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7ed3\u5408\u5176\u4ed6\u5e93\uff0c\u5982Matplotlib\u6216Seaborn\uff0c\u6765\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002\u4f7f\u7528pivot_table()<\/code>\u51fd\u6570\u53ef\u4ee5\u521b\u5efa\u900f\u89c6\u8868\uff0c\u800cstyle<\/code>\u5c5e\u6027\u5219\u5141\u8bb8\u60a8\u81ea\u5b9a\u4e49\u8868\u683c\u7684\u5916\u89c2\uff0c\u5305\u62ec\u989c\u8272\u548c\u5b57\u4f53\u7b49\u3002\u8fd9\u6837\uff0c\u60a8\u53ef\u4ee5\u751f\u6210\u66f4\u5177\u5438\u5f15\u529b\u548c\u6613\u4e8e\u7406\u89e3\u7684\u8868\u683c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5c06\u6570\u636e\u6574\u7406\u6210\u8868\u683c\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001PrettyTable\u5e93\u3001Tabulate\u5e93\u3001csv […]","protected":false},"author":3,"featured_media":1057619,"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\/1057617"}],"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=1057617"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1057617\/revisions"}],"predecessor-version":[{"id":1057620,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1057617\/revisions\/1057620"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1057619"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1057617"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1057617"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1057617"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}