如何在for循环中每次循环时遍历不同的字典

def getDicts(aFile): voteFile = open(aFile) listDicts = [{},{},{},{},{},{},{},{},{},{},{}] i = 0 for line in voteFile: lineSplit = line.split(':') if len(lineSplit) > 1: key = lineSplit[0].strip() value = lineSplit[1].strip() listDicts[i][key] = value else: i += 1 return listDicts

_Constituency:East Midlands _Seats:5 Brexit Party:452321 Liberal Democrats:203989 Labour:164682 Conservative:126138 Green:124630 UKIP:58198 Change UK:41117 Independent Network:7641 Simon Rood (Independent):4511 _Constituency:East of England _Seats:7 Brexit Party:604715 Liberal Democrats:361563 Green:202460 Conservative:163830 Labour:139490 Change UK:58274 UKIP:54676 English Democrat:10217 Attila Csordas (Independent):3230 _Constituency:London _Seats:8 Liberal Democrats:608725 Labour:536810 Brexit Party:400257 Green:278957 Conservative:177964 Change UK:117635 UKIP:46497 Animal Welfare:25232 Women's Equality:23766 UK EU:18806 Claudia Mcdowell (Independent):1036 Daze Aghaji (Independent):1018 Roger Hallam (Independent):924 Kofi Klu (Independent):869 Andrea Venzon (Independent):731 Mike Shad (Independent):707 Zoe Lafferty (Independent):436 Andrew Medhurst (Independent):430 Alan Kirkby (Independent):401 Ian Sowden (Independent):254 Henry Muss (Independent):226 _Constituency:North East England _Seats:3 Brexit Party:240056 Labour:119931 Liberal Democrats:104330 Green:49905 Conservative:42395 UKIP:38269 Change UK:24968 _Constituency:North West England _Seats:8 Brexit Party:541843 Labour:380193 Liberal Democrats:297507 Green:216581 Conservative:131002 UKIP:62464 Change UK:47237 Tommy Robinson (Independent):38908 English Democrat:10045 UK EU:7125 Mohammad Aslam (Independent):2002 _Constituency:South East England _Seats:10 Brexit Party:915686 Liberal Democrats:653743 Green:343249 Conservative:260277 Labour:184678 Change UK:105832 UKIP:56487 UK EU:7645 Jason Guy Spencer McMahon (Independent):3650 Socialist (GB):3505 David Victor Round (Independent):2606 Michael Jeffrey Turberville (Independent):1587 _Constituency:South West England _Seats:6 Brexit Party:611742 Liberal Democrats:385095 Green:302364 Conservative:144674 Labour:108100 UKIP:53739 Change UK:46612 English Democrat:8393 Larch Maxey (Independent):1772 Mothiur Rahman (Independent):755 Neville Seed (Independent):3383 _Constituency:West Midlands _Seats:7 Brexit Party:507152 Labour:228298 Liberal Democrats:219982 Green:143520 Conservative:135279 UKIP:66934 Change UK:45673 _Constituency:Yorkshire and the Humber _Seats:6 Brexit Party:470351 Labour:210516 Liberal Democrats:200180 Green:166980 Conservative:92863 UKIP:56100 Yorkshire Party:50842 Change UK:30162 English Democrat:11283 _Constituency:Scotland _Seats:6 SNP:594553 Brexit Party:233006 Liberal Democrats:218285 Conservative:182476 Labour:146724 Scottish Green:129603 Change UK:30004 UKIP:28418 Gordon Edgar (Independent):6128 Ken Parke (Independent):2049 _Constituency:Wales _Seats:4 Brexit Party:271404 Plaid Cymru:163928 Labour:127833 Liberal Democrats:113885 Conservative:54587 Green:52660 UKIP:27566 Change UK:24332

2条回答

网友

1楼 · 编辑于 2024-10-01 00:22:27

作为一名计算机科学家，我个人喜欢保持从0开始而不是从1开始的惯例。例如，dict1到dict11现在是dict0到dict10。你知道吗

我不知道为什么在代码中使用while循环，我认为if语句就足够了。你知道吗

不管怎样，这里有一些代码给你。它只使用较少数量的字典，但它应该符合您的要求（假设您总是有11行数据后跟一个空行）。你知道吗

顺便说一下，%是一个模除运算符。它返回剩余的股息。因此5%4=1和4%3=1

测试.txt

key1:val1
key2:val2
key3:val3

key4:val4
key5:val5
key6:val6

脚本

voteFile = open('test.txt')

dict_0 = {}
dict_1 = {}
dict_2 = {}
listDicts = [dict_0, dict_1, dict_2]

lineCount = 0
for line in voteFile:
    lineSplit = line.split(":")
    if len(lineSplit) == 2:
        #Retrieves the dictionary you need by index
        listDictIndex = lineCount%len(listDicts)
        currentDict = listDicts[listDictIndex]

        key = lineSplit[0].strip()
        value = lineSplit[1].strip()
        currentDict[key] = value

        lineCount += 1
voteFile.close()

import pprint
pprint.pprint(listDicts)

编辑此算法没有嵌套循环，因此运行时为O（n），其中n是输入文档中的每一行。你知道吗

网友

2楼 · 编辑于 2024-10-01 00:22:27

以下是我的建议：

def getConstituencies(aFile):

    all_data = {}
    constituency_keys = []
    constituency_idx = []

    # Store all of the information in the text file
    with open(aFile, 'rb') as f:
        lines = f.readlines()

    # Go through the stored info and find all of the constituencies and corresponding indexes
    for idx, line in enumerate(lines):
        if line.split(':')[0] = '_Constituency':
            constituency_keys.append(line.split(':')[1])
            constituency_idx.append(idx)

    # Now go through the stored lines and from the specified index until a blank line, store all the related info into a dictionary. 
    # Then, nest that dictionary into the all_data dictionary
    for idx, c in zip(constituency_idx, constituency_keys):
        temp_dict = {}
        for line in lines[idx+1:]:
            if line == "":
                break
            temp_dict[line.split(':')[0]] = line.split(':')[1]
        all_data[c] = temp_dict

访问信息就是查询选区的问题：

all_data['East Midlands']['Green']

我还建议您从Pandas开始将数据排序为数据帧—这将使您的数据处理变得更加轻松

欢迎其他用户提出建议和反馈。你知道吗

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