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python - 从多个 csv 文件的多列创建字典中的字符偏移列表

问题描述

我有两个类似的 csv 文件，如下所示：

{http://www.omg.org/XMI}id,begin,end,Character
45440,34,45,Miss Parker
45455,137,147,Farrington
48976,295,298,Mr Alleyne
45533,890,900,Mr Alleyne
49020,2147,2154,Mr Alleyne
49020,2147,2154,Mr Alleyne
48606,2689,2696,Farrington
46858,3690,3693,Farrington
48680,5280,5291,clients
46880,5373,5376,Farrington
46728,5396,5407,clients
49057,5673,5683,clients
48734,6145,6155,Mr Alleyne
48734,6145,6155,Mr Alleyne
46699,6661,6664,Miss Delacour
49094,6969,6972,Farrington
48841,8451,8461,Mr Alleyne
48849,8466,8479,Miss Delacour

我希望能够创建一个唯一字符提及的字典作为键，并添加它们的偏移量'begin'和'end'，忽略列'{http://www.omg.org/XMI}id'相应唯一字符（即键）的列。

我想要的输出应该是这样的：

print(dict_of_mentions)

输出：

{'Farrington': [(137,147),(2689,2696) #etc...],
 'Mr Alleyne': [(295,298), (890,900) #etc...], #rest of characters... }

到目前为止，我的代码如下所示：

import tkinter
from tkinter import filedialog
def character_mentions():
    filenames = filedialog.askopenfilenames()
    for filename in filenames:
        reader = csv.DictReader(open(filename))
        dict_of_mentions = {}      
        for row in reader:
            key = row.pop('Character')
            if key in dict_of_mentions:
                #implement duplicate row handling here
                pass
            dict_of_mentions[key] = row
    print(dict_of_mentions)

输出如下所示：

{'Miss Parker': OrderedDict([('{http://www.omg.org/XMI}id', '45440'), ('begin', '34'), ('end', '45')]) 'Farrington': OrderedDict([('{http://www.omg.org/XMI}id', '46645'), ('begin', '22012'), ('end', '22014')]), 'Mr Alleyne': OrderedDict([('{http://www.omg.org/XMI}id', '47297'), ('begin', '13952'), ('end', '13962')]), 'clients': OrderedDict([('{http://www.omg.org/XMI}id', '49057'), ('begin', '5673'), ('end', '5683')]), 'Miss Delacour': OrderedDict([('{http://www.omg.org/XMI}id', '45867'), ('begin', '9101'), ('end', '9109')]), 'Everyone': OrderedDict([('{http://www.omg.org/XMI}id', '45836'), ('begin', '11896'), ('end', '11900')]), "Terry Kelly's clerk": OrderedDict([('{http://www.omg.org/XMI}id', '49278'), ('begin', '11971'), ('end', '11980')]), 'crowd': OrderedDict([('{http://www.omg.org/XMI}id', '49337'), ('begin', '12458'), ('end', '12471')]), 'office-girls': OrderedDict([('{http://www.omg.org/XMI}id', '49359'), ('begin', '12537'), ('end', '12549')]), 'Higgins': OrderedDict([('{http://www.omg.org/XMI}id', '45936'), ('begin', '13925'), ('end', '13927')]), 'friends': OrderedDict([('{http://www.omg.org/XMI}id', '49592'), ('begin', '17499'), ('end', '17506')]), 'boys': OrderedDict([('{http://www.omg.org/XMI}id', '47949'), ('begin', '17638'), ('end', '17649')]), 'one of the young women': OrderedDict([('{http://www.omg.org/XMI}id', '46257'), ('begin', '19945'), ('end', '19954')]), 'Weathers': OrderedDict([('{http://www.omg.org/XMI}id', '49643'), ('begin', '19881'), ('end', '19891')]), 'curate': OrderedDict([('{http://www.omg.org/XMI}id', '46142'), ('begin', '19094'), ('end', '19101')]), 'Ada': OrderedDict([('{http://www.omg.org/XMI}id', '46364'), ('begin', '20313'), ('end', '20316')]), 'Tom': OrderedDict([('{http://www.omg.org/XMI}id', '49804'), ('begin', '21852'), ('end', '21855')])}

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标签： pythonpython-3.xlistfilecsv

解决方案

您可以使用itertools.groupby

>>> import csv
>>> from itertools import groupby
>>> l = list(csv.reader(open('file.csv')))
>>> f = lambda x: x[-1]
>>> {k:[tuple(x[1:3]) for x in v] for k,v in groupby(sorted(l[1:], key=f), f)}
{'Farrington': [('137', '147'), ('2689', '2696'), ('3690', '3693'), ('5373', '5376'), ('6969', '6972')], 'Miss Delacour': [('6661', '6664'), ('8466', '8479')], 'Miss Parker': [('34', '45')], 'Mr Alleyne': [('295', '298'), ('890', '900'), ('2147', '2154'), ('2147', '2154'), ('6145', '6155'), ('6145', '6155'), ('8451', '8461')], 'clients': [('5280', '5291'), ('5396', '5407'), ('5673', '5683')]}

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