{"id":1038649,"date":"2024-12-31T12:25:51","date_gmt":"2024-12-31T04:25:51","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1038649.html"},"modified":"2024-12-31T12:25:53","modified_gmt":"2024-12-31T04:25:53","slug":"python%e5%a6%82%e4%bd%95%e7%bb%99%e4%b8%80%e7%bb%84%e6%95%b0%e6%8d%ae%e5%88%86%e7%bb%84","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1038649.html","title":{"rendered":"python\u5982\u4f55\u7ed9\u4e00\u7ec4\u6570\u636e\u5206\u7ec4"},"content":{"rendered":"

\"python\u5982\u4f55\u7ed9\u4e00\u7ec4\u6570\u636e\u5206\u7ec4\"<\/p>\n

Python\u7ed9\u4e00\u7ec4\u6570\u636e\u5206\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u4f7f\u7528pandas\u5e93\u3001itertools\u6a21\u5757\u548c\u81ea\u5b9a\u4e49\u51fd\u6570\u7b49\u3002\u5177\u4f53\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528pandas\u5e93\u7684groupby\u65b9\u6cd5\u3001\u4f7f\u7528itertools\u6a21\u5757\u7684groupby\u51fd\u6570\u3001\u4f7f\u7528for\u5faa\u73af\u548c\u6761\u4ef6\u5224\u65ad\u81ea\u5b9a\u4e49\u5206\u7ec4\u3002<\/strong> \u5176\u4e2d\u6700\u5e38\u7528\u7684\u662f\u4f7f\u7528pandas\u5e93\u7684groupby\u65b9\u6cd5\uff0c\u5b83\u4e0d\u4ec5\u529f\u80fd\u5f3a\u5927\uff0c\u800c\u4e14\u64cd\u4f5c\u7b80\u4fbf\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u5bf9\u8fd9\u51e0\u79cd\u65b9\u6cd5\u8fdb\u884c\u8be6\u7ec6\u4ecb\u7ecd\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pandas\u5e93\u7684GroupBy\u65b9\u6cd5<\/h3>\n<\/p>\n

Pandas\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u5904\u7406\u5e93\u4e4b\u4e00\uff0c\u5176groupby\u65b9\u6cd5\u975e\u5e38\u5f3a\u5927\uff0c\u9002\u7528\u4e8e\u5927\u591a\u6570\u5206\u7ec4\u9700\u6c42\u3002<\/p>\n<\/p>\n

1.1 \u5b89\u88c5\u548c\u5bfc\u5165Pandas<\/h4>\n<\/p>\n

\u5728\u4f7f\u7528pandas\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5\u8be5\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
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165pandas\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.2 \u521b\u5efa\u6570\u636e\u96c6<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u6570\u636e\u96c6\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b\u6570\u636e\u96c6\uff1a<\/p>\n<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Edward'],<\/p>\n
    'Age': [24, 27, 22, 32, 29],<\/p>\n
    'City': ['New York', 'Los Angeles', 'New York', 'Chicago', 'Chicago']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.3 \u6309\u5355\u5217\u5206\u7ec4<\/h4>\n<\/p>\n
\u4f7f\u7528pandas\u7684groupby\u65b9\u6cd5\u53ef\u4ee5\u8f7b\u677e\u5730\u6309\u5355\u5217\u5206\u7ec4\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u6309\u57ce\u5e02\uff08City\uff09\u5206\u7ec4\uff1a<\/p>\n<\/p>\n
grouped = df.groupby('City')<\/p>\n
for name, group in grouped:<\/p>\n
    print(name)<\/p>\n
    print(group)<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.4 \u6309\u591a\u5217\u5206\u7ec4<\/h4>\n<\/p>\n
pandas\u4e5f\u652f\u6301\u6309\u591a\u5217\u5206\u7ec4\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u6309\u57ce\u5e02\uff08City\uff09\u548c\u5e74\u9f84\uff08Age\uff09\u5206\u7ec4\uff1a<\/p>\n<\/p>\n
grouped = df.groupby(['City', 'Age'])<\/p>\n
for name, group in grouped:<\/p>\n
    print(name)<\/p>\n
    print(group)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528itertools\u6a21\u5757\u7684groupby\u51fd\u6570<\/h3>\n<\/p>\n
itertools\u6a21\u5757\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u7528\u4e8e\u64cd\u4f5c\u8fed\u4ee3\u5bf9\u8c61\u7684\u51fd\u6570\uff0c\u5176\u4e2d\u7684groupby\u51fd\u6570\u53ef\u4ee5\u7528\u4e8e\u5206\u7ec4\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
2.1 \u5bfc\u5165itertools\u6a21\u5757<\/h4>\n<\/p>\n
import itertools<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.2 \u521b\u5efa\u6570\u636e\u96c6<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e0e\u4e0a\u9762\u76f8\u540c\u7684\u6570\u636e\u96c6\uff1a<\/p>\n<\/p>\n
data = [<\/p>\n
    {'Name': 'Alice', 'Age': 24, 'City': 'New York'},<\/p>\n
    {'Name': 'Bob', 'Age': 27, 'City': 'Los Angeles'},<\/p>\n
    {'Name': 'Charlie', 'Age': 22, 'City': 'New York'},<\/p>\n
    {'Name': 'David', 'Age': 32, 'City': 'Chicago'},<\/p>\n
    {'Name': 'Edward', 'Age': 29, 'City': 'Chicago'}<\/p>\n
]<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.3 \u6309\u5355\u5217\u5206\u7ec4<\/h4>\n<\/p>\n
\u4f7f\u7528itertools.groupby\u51fd\u6570\u6309\u57ce\u5e02\uff08City\uff09\u5206\u7ec4\uff1a<\/p>\n<\/p>\n
data_sorted = sorted(data, key=lambda x: x['City'])<\/p>\n
grouped = itertools.groupby(data_sorted, key=lambda x: x['City'])<\/p>\n
for key, group in grouped:<\/p>\n
    print(key)<\/p>\n
    for item in group:<\/p>\n
        print(item)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u8fdb\u884c\u5206\u7ec4<\/h3>\n<\/p>\n
\u6709\u65f6\u5019\uff0c\u6211\u4eec\u9700\u8981\u6839\u636e\u7279\u5b9a\u7684\u89c4\u5219\u8fdb\u884c\u5206\u7ec4\uff0c\u6b64\u65f6\u53ef\u4ee5\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u3002<\/p>\n<\/p>\n
3.1 \u521b\u5efa\u6570\u636e\u96c6<\/h4>\n<\/p>\n
\u6211\u4eec\u7ee7\u7eed\u4f7f\u7528\u4e0a\u9762\u76f8\u540c\u7684\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n
3.2 \u81ea\u5b9a\u4e49\u5206\u7ec4\u51fd\u6570<\/h4>\n<\/p>\n
\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5e74\u9f84\u6bb5\uff0820-25\u5c81\uff0c26-30\u5c81\uff0c31-35\u5c81\uff09\u8fdb\u884c\u5206\u7ec4\uff1a<\/p>\n<\/p>\n
def group_by_age(data):<\/p>\n
    groups = {'20-25': [], '26-30': [], '31-35': []}<\/p>\n
    for item in data:<\/p>\n
        age = item['Age']<\/p>\n
        if 20 <= age <= 25:<\/p>\n
            groups['20-25'].append(item)<\/p>\n
        elif 26 <= age <= 30:<\/p>\n
            groups['26-30'].append(item)<\/p>\n
        elif 31 <= age <= 35:<\/p>\n
            groups['31-35'].append(item)<\/p>\n
    return groups<\/p>\n
grouped_data = group_by_age(data)<\/p>\n
for key, group in grouped_data.items():<\/p>\n
    print(key)<\/p>\n
    for item in group:<\/p>\n
        print(item)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u51e0\u79cd\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0cPython\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u5f0f\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\u3002\u4f7f\u7528pandas\u5e93\u7684groupby\u65b9\u6cd5\u3001\u4f7f\u7528itertools\u6a21\u5757\u7684groupby\u51fd\u6570\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u8fdb\u884c\u5206\u7ec4<\/strong>\uff0c\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002pandas\u5e93\u7684groupby\u65b9\u6cd5\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u7528\u4e8e\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\uff1bitertools\u6a21\u5757\u7684groupby\u51fd\u6570\u7b80\u6d01\u9ad8\u6548\uff0c\u9002\u7528\u4e8e\u5904\u7406\u8fed\u4ee3\u5bf9\u8c61\uff1b\u81ea\u5b9a\u4e49\u51fd\u6570\u5219\u7075\u6d3b\u6027\u9ad8\uff0c\u9002\u7528\u4e8e\u7279\u6b8a\u7684\u5206\u7ec4\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u65e0\u8bba\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\uff0c\u90fd\u9700\u8981\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u8fdb\u884c\u9009\u62e9\uff0c\u786e\u4fdd\u4ee3\u7801\u7684\u7b80\u6d01\u6027\u548c\u53ef\u8bfb\u6027\u3002\u5e0c\u671b\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u80fd\u591f\u5e2e\u52a9\u5927\u5bb6\u66f4\u597d\u5730\u638c\u63e1Python\u6570\u636e\u5206\u7ec4\u7684\u65b9\u6cd5\u548c\u6280\u5de7\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u5206\u7ec4\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u8f7b\u677e\u5730\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5Pandas\u5e93\u3002\u4f7f\u7528pd.DataFrame<\/code>\u521b\u5efa\u4e00\u4e2a\u6570\u636e\u6846\uff0c\u7136\u540e\u5229\u7528groupby()<\/code>\u51fd\u6570\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u6839\u636e\u67d0\u4e00\u5217\u7684\u503c\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u4f7f\u7528agg()<\/code>\u51fd\u6570\u5bf9\u6bcf\u7ec4\u5e94\u7528\u805a\u5408\u64cd\u4f5c\uff0c\u5982\u6c42\u548c\u3001\u5747\u503c\u7b49\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
import pandas as pd\n\ndata = {'\u7c7b\u522b': ['A', 'B', 'A', 'B'], '\u503c': [10, 20, 30, 40]}\ndf = pd.DataFrame(data)\ngrouped = df.groupby('\u7c7b\u522b').agg('sum')\nprint(grouped)\n<\/code><\/pre>\n
\u5982\u4f55\u4f7f\u7528Python\u7684\u5185\u7f6e\u51fd\u6570\u5bf9\u6570\u636e\u5217\u8868\u8fdb\u884c\u5206\u7ec4\uff1f<\/strong>
Python\u7684\u5185\u7f6e\u6a21\u5757itertools<\/code>\u63d0\u4f9b\u4e86groupby()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5bf9\u5df2\u6392\u5e8f\u7684\u6570\u636e\u5217\u8868\u8fdb\u884c\u5206\u7ec4\u3002\u9996\u5148\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u6392\u5e8f\uff0c\u7136\u540e\u4f7f\u7528groupby()<\/code>\u51fd\u6570\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u5904\u7406\u4e00\u4e2a\u5305\u542b\u591a\u4e2a\u76f8\u540c\u5143\u7d20\u7684\u5217\u8868\u65f6\uff0c\u53ef\u4ee5\u5c06\u76f8\u540c\u5143\u7d20\u5206\u4e3a\u4e00\u7ec4\uff0c\u5e76\u8ba1\u7b97\u6bcf\u7ec4\u7684\u6570\u91cf\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
from itertools import groupby\n\ndata = [1, 1, 2, 2, 3]\ngrouped = {key: len(list(group)) for key, group in groupby(sorted(data))}\nprint(grouped)\n<\/code><\/pre>\n
\u5728Python\u4e2d\uff0c\u5982\u4f55\u5bf9\u5b57\u5178\u7684\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff1f<\/strong>
\u5982\u679c\u9700\u8981\u5bf9\u5b57\u5178\u4e2d\u7684\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff0c\u53ef\u4ee5\u4f7f\u7528defaultdict<\/code>\u6765\u7b80\u5316\u64cd\u4f5c\u3002\u901a\u8fc7\u904d\u5386\u5b57\u5178\u7684\u952e\u503c\u5bf9\uff0c\u5c06\u76f8\u540c\u7684\u952e\u503c\u805a\u96c6\u5230\u4e00\u8d77\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u6839\u636e\u67d0\u4e2a\u5c5e\u6027\u5bf9\u4e00\u7ec4\u5bf9\u8c61\u8fdb\u884c\u5206\u7ec4\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a  <\/p>\n
from collections import defaultdict\n\ndata = [{'\u7c7b\u522b': 'A', '\u503c': 10}, {'\u7c7b\u522b': 'B', '\u503c': 20}, {'\u7c7b\u522b': 'A', '\u503c': 30}]\ngrouped = defaultdict(list)\n\nfor item in data:\n    grouped[item['\u7c7b\u522b']].append(item['\u503c'])\n\nprint(dict(grouped))\n<\/code><\/pre>\n
\u8fd9\u4e9b\u65b9\u6cd5\u4e3a\u60a8\u63d0\u4f9b\u4e86\u4e0d\u540c\u7684\u5206\u7ec4\u65b9\u5f0f\uff0c\u60a8\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u6700\u5408\u9002\u7684\u65b9\u6848\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u7ed9\u4e00\u7ec4\u6570\u636e\u5206\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u4f7f\u7528pandas\u5e93\u3001itertools\u6a21\u5757\u548c\u81ea\u5b9a\u4e49\u51fd\u6570\u7b49\u3002\u5177\u4f53\u65b9\u6cd5 […]","protected":false},"author":3,"featured_media":1038659,"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\/1038649"}],"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=1038649"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1038649\/revisions"}],"predecessor-version":[{"id":1038663,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1038649\/revisions\/1038663"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1038659"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1038649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1038649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1038649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}