{"id":1130653,"date":"2025-01-08T20:42:02","date_gmt":"2025-01-08T12:42:02","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1130653.html"},"modified":"2025-01-08T20:42:05","modified_gmt":"2025-01-08T12:42:05","slug":"python%e5%a6%82%e4%bd%95%e6%98%be%e7%a4%ba%e4%b8%80%e4%b8%aa%e5%88%97%e8%a1%a8%e4%b8%ad%e7%9a%84%e5%ad%97%e5%85%b8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1130653.html","title":{"rendered":"python\u5982\u4f55\u663e\u793a\u4e00\u4e2a\u5217\u8868\u4e2d\u7684\u5b57\u5178"},"content":{"rendered":"

\"python\u5982\u4f55\u663e\u793a\u4e00\u4e2a\u5217\u8868\u4e2d\u7684\u5b57\u5178\"<\/p>\n

Python \u663e\u793a\u4e00\u4e2a\u5217\u8868\u4e2d\u7684\u5b57\u5178\u7684\u65b9\u6cd5\u6709\u591a\u79cd<\/strong>\uff0c\u4f7f\u7528for\u5faa\u73af\u904d\u5386\u3001\u4f7f\u7528\u5217\u8868\u751f\u6210\u5f0f\u3001\u4f7f\u7528pprint\u6a21\u5757\u7b49<\/strong>\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u63a2\u8ba8\u6bcf\u79cd\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528for\u5faa\u73af\u904d\u5386<\/h3>\n<\/p>\n

for\u5faa\u73af\u904d\u5386\u662f\u6700\u5e38\u89c1\u4e14\u76f4\u89c2\u7684\u65b9\u6cd5<\/strong>\uff0c\u5176\u4f18\u70b9\u662f\u7b80\u5355\u6613\u61c2\uff0c\u9002\u5408\u521d\u5b66\u8005\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n

data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
for item in data:<\/p>\n
    print(item)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u6cd5\uff0c\u53ef\u4ee5\u9010\u4e2a\u6253\u5370\u5217\u8868\u4e2d\u7684\u6bcf\u4e2a\u5b57\u5178\u3002for\u5faa\u73af\u7684\u7075\u6d3b\u6027\u8f83\u9ad8\uff0c\u53ef\u4ee5\u5728\u904d\u5386\u8fc7\u7a0b\u4e2d\u5bf9\u5b57\u5178\u8fdb\u884c\u5904\u7406<\/strong>\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0cfor\u5faa\u73af\u904d\u5386\u975e\u5e38\u9002\u5408\u7528\u4e8e\u9700\u8981\u9010\u4e2a\u5904\u7406\u5217\u8868\u4e2d\u7684\u5b57\u5178\u7684\u573a\u666f\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
for item in data:<\/p>\n
    if item["age"] > 30:<\/p>\n
        print(f"{item['name']} is older than 30")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u5728\u904d\u5386\u8fc7\u7a0b\u4e2d\u5bf9\u5b57\u5178\u8fdb\u884c\u6761\u4ef6\u5224\u65ad\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u5217\u8868\u751f\u6210\u5f0f<\/h3>\n<\/p>\n
\u5217\u8868\u751f\u6210\u5f0f\u662f\u4e00\u79cd\u7b80\u6d01\u7684\u5199\u6cd5<\/strong>\uff0c\u53ef\u4ee5\u5728\u4e00\u884c\u4ee3\u7801\u4e2d\u5b9e\u73b0\u5bf9\u5217\u8868\u4e2d\u5b57\u5178\u7684\u904d\u5386\u548c\u5904\u7406\u3002\u5176\u4f18\u70b9\u662f\u4ee3\u7801\u7b80\u6d01\uff0c\u4f46\u53ef\u8bfb\u6027\u53ef\u80fd\u7a0d\u5dee\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
[print(item) for item in data]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5217\u8868\u751f\u6210\u5f0f\u9002\u5408\u7528\u4e8e\u7b80\u5355\u7684\u904d\u5386\u548c\u6253\u5370\u4efb\u52a1<\/strong>\uff0c\u4e0d\u9002\u5408\u590d\u6742\u7684\u5904\u7406\u903b\u8f91\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u9700\u8981\u5728\u904d\u5386\u8fc7\u7a0b\u4e2d\u8fdb\u884c\u7b80\u5355\u64cd\u4f5c\u7684\u573a\u666f\uff0c\u5217\u8868\u751f\u6210\u5f0f\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
[print(f"{item['name']} is {item['age']} years old") for item in data]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u5199\u6cd5\u7b80\u6d01\u660e\u4e86\uff0c\u9002\u5408\u5feb\u901f\u5b9e\u73b0\u7b80\u5355\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528pprint\u6a21\u5757<\/h3>\n<\/p>\n
pprint\u6a21\u5757\u63d0\u4f9b\u4e86\u5bf9\u590d\u6742\u6570\u636e\u7ed3\u6784\u7684\u7f8e\u5316\u6253\u5370\u529f\u80fd<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u9700\u8981\u66f4\u597d\u683c\u5f0f\u5316\u8f93\u51fa\u7684\u573a\u666f\u3002\u5176\u4f18\u70b9\u662f\u8f93\u51fa\u7f8e\u89c2\uff0c\u9002\u5408\u8c03\u8bd5\u548c\u5c55\u793a\u6570\u636e\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
import pprint<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
pprint.pprint(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
pprint\u6a21\u5757\u7684\u7f8e\u5316\u8f93\u51fa\u529f\u80fd\uff0c\u4f7f\u5f97\u6570\u636e\u7ed3\u6784\u66f4\u52a0\u6e05\u6670\u6613\u8bfb<\/strong>\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u8c03\u8bd5\u548c\u5c55\u793a\u590d\u6742\u6570\u636e\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u9700\u8981\u5bf9\u590d\u6742\u6570\u636e\u7ed3\u6784\u8fdb\u884c\u8c03\u8bd5\u548c\u5c55\u793a\u65f6\uff0cpprint\u6a21\u5757\u662f\u4e00\u4e2a\u975e\u5e38\u6709\u7528\u7684\u5de5\u5177\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pprint<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25, "skills": ["Python", "Data Analysis"]},<\/p>\n
    {"name": "Bob", "age": 30, "skills": ["Java", "Project Management"]},<\/p>\n
    {"name": "Charlie", "age": 35, "skills": ["C++", "System Architecture"]}<\/p>\n
]<\/p>\n
pprint.pprint(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u6e05\u6670\u5730\u5c55\u793a\u6bcf\u4e2a\u4eba\u7684\u8be6\u7ec6\u4fe1\u606f\u548c\u6280\u80fd\u3002<\/p>\n<\/p>\n
\u56db\u3001\u4f7f\u7528json\u6a21\u5757<\/h3>\n<\/p>\n
json\u6a21\u5757\u53ef\u4ee5\u5c06Python\u5bf9\u8c61\u8f6c\u6362\u4e3aJSON\u683c\u5f0f\u7684\u5b57\u7b26\u4e32<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u9700\u8981\u5c06\u6570\u636e\u5bfc\u51fa\u6216\u4f20\u8f93\u7684\u573a\u666f\u3002\u5176\u4f18\u70b9\u662f\u53ef\u4ee5\u8f7b\u677e\u4e0e\u5176\u4ed6\u7cfb\u7edf\u8fdb\u884c\u6570\u636e\u4ea4\u4e92\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
import json<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
print(json.dumps(data, indent=4))<\/p>\n
<\/code><\/pre>\n<\/p>\n
json\u6a21\u5757\u7684indent\u53c2\u6570\u53ef\u4ee5\u7f8e\u5316\u8f93\u51fa\uff0c\u4f7f\u5f97JSON\u5b57\u7b26\u4e32\u66f4\u52a0\u6613\u8bfb<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u6570\u636e\u5bfc\u51fa\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u9700\u8981\u5c06\u6570\u636e\u5bfc\u51fa\u4e3aJSON\u683c\u5f0f\u8fdb\u884c\u5b58\u50a8\u6216\u4f20\u8f93\u65f6\uff0cjson\u6a21\u5757\u662f\u4e00\u4e2a\u975e\u5e38\u65b9\u4fbf\u7684\u5de5\u5177\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import json<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25, "skills": ["Python", "Data Analysis"]},<\/p>\n
    {"name": "Bob", "age": 30, "skills": ["Java", "Project Management"]},<\/p>\n
    {"name": "Charlie", "age": 35, "skills": ["C++", "System Architecture"]}<\/p>\n
]<\/p>\n
json_data = json.dumps(data, indent=4)<\/p>\n
with open('data.json', 'w') as f:<\/p>\n
    f.write(json_data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u5c06\u6570\u636e\u4fdd\u5b58\u4e3aJSON\u6587\u4ef6\uff0c\u65b9\u4fbf\u540e\u7eed\u4f7f\u7528\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u4f7f\u7528pandas\u6a21\u5757<\/h3>\n<\/p>\n
pandas\u6a21\u5757\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5c55\u793a\u529f\u80fd<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u9700\u8981\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u7684\u573a\u666f\u3002\u5176\u4f18\u70b9\u662f\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
pandas\u6a21\u5757\u7684DataFrame\u7ed3\u6784\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5206\u6790<\/strong>\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60<\/a>\u9886\u57df\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u590d\u6742\u5206\u6790\u548c\u5904\u7406\u65f6\uff0cpandas\u6a21\u5757\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u5de5\u5177\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25, "skills": ["Python", "Data Analysis"]},<\/p>\n
    {"name": "Bob", "age": 30, "skills": ["Java", "Project Management"]},<\/p>\n
    {"name": "Charlie", "age": 35, "skills": ["C++", "System Architecture"]}<\/p>\n
]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
\u5c55\u793a\u6bcf\u4e2a\u4eba\u7684\u6280\u80fd<\/strong><\/h2>\n
for index, row in df.iterrows():<\/p>\n
    print(f"{row['name']} has skills: {', '.join(row['skills'])}")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u8be6\u7ec6\u5206\u6790\u548c\u5904\u7406\uff0c\u9002\u5408\u7528\u4e8e\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u9879\u76ee\u3002<\/p>\n<\/p>\n
\u516d\u3001\u4f7f\u7528tabulate\u6a21\u5757<\/h3>\n<\/p>\n
tabulate\u6a21\u5757\u63d0\u4f9b\u4e86\u5c06\u6570\u636e\u7ed3\u6784\u683c\u5f0f\u5316\u4e3a\u8868\u683c\u7684\u529f\u80fd<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u9700\u8981\u4ee5\u8868\u683c\u5f62\u5f0f\u5c55\u793a\u6570\u636e\u7684\u573a\u666f\u3002\u5176\u4f18\u70b9\u662f\u8f93\u51fa\u7f8e\u89c2\uff0c\u9002\u5408\u7528\u4e8e\u62a5\u544a\u548c\u5c55\u793a\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
from tabulate import tabulate<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
print(tabulate(data, headers="keys"))<\/p>\n
<\/code><\/pre>\n<\/p>\n
tabulate\u6a21\u5757\u7684\u8868\u683c\u683c\u5f0f\u8f93\u51fa\uff0c\u4f7f\u5f97\u6570\u636e\u66f4\u52a0\u76f4\u89c2\u548c\u6613\u8bfb<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u62a5\u544a\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u9700\u8981\u5c06\u6570\u636e\u4ee5\u8868\u683c\u5f62\u5f0f\u5c55\u793a\u65f6\uff0ctabulate\u6a21\u5757\u662f\u4e00\u4e2a\u975e\u5e38\u6709\u7528\u7684\u5de5\u5177\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
from tabulate import tabulate<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25, "skills": ["Python", "Data Analysis"]},<\/p>\n
    {"name": "Bob", "age": 30, "skills": ["Java", "Project Management"]},<\/p>\n
    {"name": "Charlie", "age": 35, "skills": ["C++", "System Architecture"]}<\/p>\n
]<\/p>\n
print(tabulate(data, headers="keys"))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u4ee5\u7f8e\u89c2\u7684\u8868\u683c\u5f62\u5f0f\u5c55\u793a\u6570\u636e\uff0c\u9002\u5408\u7528\u4e8e\u62a5\u544a\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n
\u4e03\u3001\u4f7f\u7528rich\u6a21\u5757<\/h3>\n<\/p>\n
rich\u6a21\u5757\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ec8\u7aef\u6253\u5370\u529f\u80fd<\/strong>\uff0c\u53ef\u4ee5\u663e\u793a\u5e26\u6709\u989c\u8272\u548c\u6837\u5f0f\u7684\u6587\u672c\uff0c\u9002\u5408\u7528\u4e8e\u9700\u8981\u7f8e\u89c2\u8f93\u51fa\u7684\u573a\u666f\u3002\u5176\u4f18\u70b9\u662f\u8f93\u51fa\u6548\u679c\u4e30\u5bcc\uff0c\u9002\u5408\u7528\u4e8e\u7ec8\u7aef\u5c55\u793a\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
from rich import print<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
for item in data:<\/p>\n
    print(item)<\/p>\n
<\/code><\/pre>\n<\/p>\n
rich\u6a21\u5757\u7684\u4e30\u5bcc\u8f93\u51fa\u6548\u679c\uff0c\u53ef\u4ee5\u63d0\u5347\u7ec8\u7aef\u5c55\u793a\u7684\u7f8e\u89c2\u5ea6<\/strong>\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u7ec8\u7aef\u5c55\u793a\u548c\u8c03\u8bd5\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u9700\u8981\u7f8e\u89c2\u8f93\u51fa\u6570\u636e\u5230\u7ec8\u7aef\u65f6\uff0crich\u6a21\u5757\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u5de5\u5177\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
from rich import print<\/p>\n
from rich.console import Console<\/p>\n
from rich.table import Table<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25, "skills": ["Python", "Data Analysis"]},<\/p>\n
    {"name": "Bob", "age": 30, "skills": ["Java", "Project Management"]},<\/p>\n
    {"name": "Charlie", "age": 35, "skills": ["C++", "System Architecture"]}<\/p>\n
]<\/p>\n
console = Console()<\/p>\n
table = Table(title="User Data")<\/p>\n
table.add_column("Name", justify="right", style="cyan", no_wrap=True)<\/p>\n
table.add_column("Age", style="magenta")<\/p>\n
table.add_column("Skills", style="green")<\/p>\n
for item in data:<\/p>\n
    table.add_row(item["name"], str(item["age"]), ", ".join(item["skills"]))<\/p>\n
console.print(table)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u4ee5\u7f8e\u89c2\u7684\u8868\u683c\u5f62\u5f0f\u5728\u7ec8\u7aef\u5c55\u793a\u6570\u636e\uff0c\u9002\u5408\u7528\u4e8e\u7ec8\u7aef\u5c55\u793a\u548c\u8c03\u8bd5\u3002<\/p>\n<\/p>\n
\u516b\u3001\u4f7f\u7528Jupyter Notebook<\/h3>\n<\/p>\n
Jupyter Notebook\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5c55\u793a\u548c\u4ea4\u4e92\u529f\u80fd<\/strong>\uff0c\u9002\u5408\u7528\u4e8e\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u9886\u57df\u3002\u5176\u4f18\u70b9\u662f\u652f\u6301\u4ee3\u7801\u3001\u6587\u672c\u548c\u56fe\u8868\u7684\u6df7\u5408\u5c55\u793a\uff0c\u9002\u5408\u7528\u4e8e\u6570\u636e\u5206\u6790\u548c\u62a5\u544a\u3002\u5177\u4f53\u5b9e\u73b0\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25},<\/p>\n
    {"name": "Bob", "age": 30},<\/p>\n
    {"name": "Charlie", "age": 35}<\/p>\n
]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
df<\/p>\n
<\/code><\/pre>\n<\/p>\n
Jupyter Notebook\u7684\u4ea4\u4e92\u5f0f\u73af\u5883\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5c55\u793a<\/strong>\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u9879\u76ee\u3002<\/p>\n<\/p>\n
\u5177\u4f53\u5b9e\u73b0\u4e0e\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u9700\u8981\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5c55\u793a\u65f6\uff0cJupyter Notebook\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u5de5\u5177\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
data = [<\/p>\n
    {"name": "Alice", "age": 25, "skills": ["Python", "Data Analysis"]},<\/p>\n
    {"name": "Bob", "age": 30, "skills": ["Java", "Project Management"]},<\/p>\n
    {"name": "Charlie", "age": 35, "skills": ["C++", "System Architecture"]}<\/p>\n
]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
df<\/p>\n
\u7ed8\u5236\u5e74\u9f84\u5206\u5e03\u56fe<\/strong><\/h2>\n
df['age'].plot(kind='bar')<\/p>\n
plt.title('Age Distribution')<\/p>\n
plt.xlabel('Name')<\/p>\n
plt.ylabel('Age')<\/p>\n
plt.xticks(ticks=range(len(df)), labels=df['name'])<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u5728Jupyter Notebook\u4e2d\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5c55\u793a\uff0c\u9002\u5408\u7528\u4e8e\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u9879\u76ee\u3002<\/p>\n<\/p>\n
\u4e5d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u663e\u793a\u4e00\u4e2a\u5217\u8868\u4e2d\u7684\u5b57\u5178\u6709\u591a\u79cd\u65b9\u6cd5\uff0c\u5305\u62ecfor\u5faa\u73af\u904d\u5386\u3001\u5217\u8868\u751f\u6210\u5f0f\u3001pprint\u6a21\u5757\u3001json\u6a21\u5757\u3001pandas\u6a21\u5757\u3001tabulate\u6a21\u5757\u3001rich\u6a21\u5757\u3001Jupyter Notebook\u7b49<\/strong>\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u4f18\u7f3a\u70b9\u548c\u9002\u7528\u573a\u666f\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u6267\u884c\u6548\u7387\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u5e0c\u671b\u60a8\u80fd\u591f\u638c\u63e1\u591a\u79cd\u65b9\u6cd5\uff0c\u5e76\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u8fdb\u884c\u6570\u636e\u5c55\u793a\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u683c\u5f0f\u5316\u663e\u793a\u5b57\u5178\u5217\u8868\u7684\u5185\u5bb9\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528pprint<\/code>\u6a21\u5757\u6765\u683c\u5f0f\u5316\u663e\u793a\u5b57\u5178\u5217\u8868\u3002pprint<\/code>\uff08\u5373\u201cpretty-print\u201d\uff09\u80fd\u591f\u8ba9\u8f93\u51fa\u66f4\u52a0\u7f8e\u89c2\u6613\u8bfb\u3002\u4f8b\u5982\uff0c\u4f7f\u7528pprint.pprint(your_list)<\/code>\u53ef\u4ee5\u6e05\u6670\u5730\u5c55\u793a\u5217\u8868\u4e2d\u7684\u6bcf\u4e2a\u5b57\u5178\u53ca\u5176\u952e\u503c\u5bf9\uff0c\u907f\u514d\u884c\u7684\u62e5\u6324\u548c\u6df7\u4e71\u3002<\/p>\n
\u5728\u6253\u5370\u5b57\u5178\u5217\u8868\u65f6\uff0c\u5982\u4f55\u63a7\u5236\u8f93\u51fa\u7684\u6df1\u5ea6\uff1f<\/strong>
\u4f7f\u7528pprint<\/code>\u6a21\u5757\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6edepth<\/code>\u53c2\u6570\u6765\u63a7\u5236\u8f93\u51fa\u7684\u6df1\u5ea6\u3002\u8fd9\u5bf9\u4e8e\u5d4c\u5957\u5b57\u5178\u7279\u522b\u6709\u7528\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
from pprint import pprint\npprint(your_list, depth=2)\n<\/code><\/pre>\n
\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u53ea\u663e\u793a\u5230\u6307\u5b9a\u7684\u6df1\u5ea6\uff0c\u4fbf\u4e8e\u67e5\u770b\u5173\u952e\u6570\u636e\u800c\u4e0d\u5fc5\u88ab\u5197\u4f59\u4fe1\u606f\u6df9\u6ca1\u3002<\/p>\n
\u5982\u4f55\u5728Jupyter Notebook\u4e2d\u663e\u793a\u5b57\u5178\u5217\u8868\uff0c\u4f7f\u5176\u66f4\u52a0\u7f8e\u89c2\uff1f<\/strong>
\u5728Jupyter Notebook\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u5c06\u5b57\u5178\u5217\u8868\u8f6c\u6362\u4e3aDataFrame\uff0c\u8fd9\u6837\u5c31\u80fd\u4ee5\u8868\u683c\u7684\u5f62\u5f0f\u663e\u793a\uff0c\u63d0\u5347\u53ef\u8bfb\u6027\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
import pandas as pd\ndf = pd.DataFrame(your_list)\ndf\n<\/code><\/pre>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u7528\u6237\u80fd\u591f\u66f4\u76f4\u89c2\u5730\u67e5\u770b\u548c\u5206\u6790\u5b57\u5178\u4e2d\u7684\u6570\u636e\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python \u663e\u793a\u4e00\u4e2a\u5217\u8868\u4e2d\u7684\u5b57\u5178\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u4f7f\u7528for\u5faa\u73af\u904d\u5386\u3001\u4f7f\u7528\u5217\u8868\u751f\u6210\u5f0f\u3001\u4f7f\u7528pprint\u6a21\u5757\u7b49\u3002\u672c […]","protected":false},"author":3,"featured_media":1130661,"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\/1130653"}],"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=1130653"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1130653\/revisions"}],"predecessor-version":[{"id":1130664,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1130653\/revisions\/1130664"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1130661"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1130653"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1130653"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1130653"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}