Python：DictReader返回字典列表？

Question

我正在使用csv.DictReader（）来读取文件。它实际上返回一个字典列表，而不是单个字典。我如何强制它返回单个字典，或者如何合并它返回的字典列表？

def agilent_e8361c_pna_read(file_loc): 
    ''' 
    Load the '.s2p' file in to a dictionary. 
    ''' 

    with open(file_loc) as f: 
     # define the fields in the Agilent '.s2p' file 
     col_names = ["f","s11","arg_s11","s21","arg_s21","s12","arg_s12","s22","arg_s22"] 

     # read the data into a dictionary 
     s2p_dicts = csv.DictReader(itertools.ifilter(n_input.is_comment, f), fieldnames=col_names, delimiter=' ') 

    return s2p_dict 

理想情况下，数据将被最初读成一个单一的字典，从来没有需要合并。它是一组数据。这些列属于一起，没有完整集合或连贯的子集是无意义的。如果DictReader不是“pythonically”能够完成这个壮举，我将决定合并词典列表。这不应该是科学家和程序员都想要用数据集所做的不常见的事情。

Answer 1

如果你想的key:listOfValues一个字典，你可以做这样的事情：

def transposeDict(listOfDicts): 
    """Turn a list of dicts into a dict of lists. Assumes all dicts in the list have the exact same keys.""" 

    keys = listOfDicts[0].iterkeys() 
    return dict((key, [d[key] for d in listOfDicts]) for key in keys) 

或者，在python2.7或更高版本：

def transposeDict(listOfDicts): 
    """Turn a list of dicts into a dict of lists. Assumes all dicts in the list have the exact same keys.""" 

    keys = listOfDicts[0].iterkeys() 
    return {key: [d[key] for d in listOfDicts] for key in keys} 

当然，这个假设中的所有类型的字典该列表具有完全相同的密钥 - 它们将来自DictReader。

一般情况下，如果不是的话，你需要如果你想占位符缺失值做类似的东西

from collections import defaultdict 

def transposeListOfDicts(listOfDicts): 
    """Turn a list of dict into a dict of lists""" 

    result = defaultdict(list) 

    for d in listofDicts: 
     for key, value in d.iteritems(): 
      result[key].append(item) 

    return result 

，那么它看起来像这样：

def transposeListOfDicts(listOfDicts): 
    keys = {} 
    for d in listOfDicts: 
     keys.update(d.iterkeys()) 

    return {key: [d.get(key, None) for d in listOfDicts] for key in keys} 

Answer 2

DictReader将每行都定期csv.reader()返回并根据您传入或从第一行读取的字段名将其转换为字典。这是设计。

如果您输入的文件只包含一个行，通过读取器调用next()返回：

def agilent_e8361c_pna_read(file_loc): 
    with open(file_loc) as f: 
     col_names = ["f","s11","arg_s11","s21","arg_s21","s12","arg_s12","s22","arg_s22"] 

     reader = csv.DictReader(itertools.ifilter(n_input.is_comment, f), fieldnames=col_names, delimiter=' ') 
     return next(reader) 

请注意，next()调用应该是while块内，否则文件将被关闭然后才能读取它。

如果您需要将行合并到一个字典中，则需要声明您希望如何查看合并的数据。您可以轻松地将合并入行每列出重点：

import csv 

def agilent_e8361c_pna_read(file_loc): 
    with open(file_loc) as f: 
     col_names = ["f","s11","arg_s11","s21","arg_s21","s12","arg_s12","s22","arg_s22"] 
     result = {k: [] for k in col_names} 

     reader = csv.reader(itertools.ifilter(n_input.is_comment, f), fieldnames=col_names, delimiter=' ') 
     for row in reader: 
      for k, v in zip(col_names, row): 
       result[k].append(v) 

     return result 

我们并不需要一个DictReader了在这一点上，因为我们没有建立每行一本字典在这里。

Answer 3

好，这是最优雅的解决方案，任何人都有这个问题。

def agilent_e8361c_pna_read(file_loc): 
    ''' 
    Load the '.s2p file in to a dictionary. 
    ''' 

    with open(file_loc) as f: 
     # read the data into a dictionary 
     rows = csv.reader(itertools.ifilter(n_input.is_comment, f), delimiter=' ') 

     # transpose data 
     cols = transpose(rows) 

     # create a dictionary with intuitive key names 
     col_names = ["f","s11","arg_s11","s21","arg_s21","s12","arg_s12","s22","arg_s22"] 
     s2p_dict = dict(zip(col_names,cols)) 

    return s2p_dict 

def transpose(l): 
    return map(list, zip(*l))