打开csv文件在python中自定义字典 [英] open csv file in python to customize dictionary

问题描述

我想知道加载此csv文件：

 表位，ID，频率，测定
 
 AVNIVGYSNAQGVDY，123431,27.0，Tetramer 
 
 DIKYTWNVPKI，887473,50.0,3H 
 
 LRQMRTVTPIRMQGG，34234,11.9，Elispot 
 
 > 
 
 
 
 d = {'AVNIVGYSNAQGVDY'：[ID [123431]，Frequency [27.0]，Assay ['Tetramer']]，'DIKYTWNVPKI'：[ID [887473]，Frequency [50.0]，Assay ['3H']] LRQMRTVTPIRMQGG'：[ID [34234]，Frequency [11.9]，Assay ['Elispot']] 
  
我使用列表，因为我的实际文件是更大的，我会追加更多的值到这些列表。 
解决方案
首先，你知道  csv  模块？如果没有，阅读介绍和例子到你知道如何获得一个可迭代的行。打印每一个，他们将看起来像这样：
  ['AVNIVGYSNAQGVDY'，'123431'，'27 .0' ，'Tetramer'] 
  
或者，如果使用 DictReader ：
  {'Epitope'：'AVNIVGYSNAQGVDY'，'ID'：'123431'，
 'Frequency'：'27 .0'，'Assay'：'Tetramer'} 
  
想要列表的列表或字典的列表;你想要一个列表的字典，其中每个键是 Epitope 从一行，对应的值是其他三个值，对不对？所以...只需将每行插入字典：
  d = {} 
 with open（path， rb'）as f：
 with csv.DictReader（f）as reader：
 for row in reader：
d [row ['Epitope']] = [row ['ID' row ['Frequency']，row ['Assay']] 
  
一个普通的读取器而不是一个 DictReader ，但我认为它更可读这种方式，如果你回到代码a几个月后）。
 
 
 
您还需要转换这些值，并将它们用作另一个查找的键，但这应该是微不足道的。例如：
  row_id = ID [int（row ['ID']）] 
 row_frequency = Frequency [float （row ['Frequency']）] 
 row_assay = Assay [row ['Assay']] 
d [row ['Epitope']] = [row_id，row_frequency，row_assay] 
  
您可以通过将行转换写为函数，然后使用字典理解来清理：
 以open（path，'rb'）as f：
 with csv.DictReader（f）as reader：
d = {row ['Epitope']：process_row（row）for reader in reader} 
  
 
I would like to know to load this csv file:
Epitope,ID,Frequency,Assay

AVNIVGYSNAQGVDY,123431,27.0,Tetramer

DIKYTWNVPKI,887473,50.0,3H

LRQMRTVTPIRMQGG,34234,11.9,Elispot
into a python dictionary like this:
d = {'AVNIVGYSNAQGVDY': [ID[123431],Frequency[27.0],Assay['Tetramer']], 'DIKYTWNVPKI': [ID[887473],Frequency[50.0],Assay['3H']], 'LRQMRTVTPIRMQGG': [ID[34234],Frequency[11.9],Assay['Elispot']]}
I am working with lists since my actual file is bigger and I will append more values to those lists. 
解决方案
First, do you know about the csv module? If not, read the introduction and examples to the point where you know how to get an iterable of rows. Print each one out, and they'll look something like this:
['AVNIVGYSNAQGVDY', '123431', '27.0', 'Tetramer']
Or, if you use a DictReader:
{'Epitope': 'AVNIVGYSNAQGVDY', 'ID': '123431', 
 'Frequency': '27.0', 'Assay': 'Tetramer'}
But you don't want a list of lists, or a list of dictionaries; you want a dictionary of lists, where each key is the Epitope from a row, and the corresponding value is the other three values, right? So… just insert each row into a dictionary that way:
d = {}
with open(path, 'rb') as f:
    with csv.DictReader(f) as reader:
        for row in reader:
            d[row['Epitope']] = [row['ID'], row['Frequency'], row['Assay']]
(This would be more compact with a plain reader instead of a DictReader, but I think it's more readable this way if you come back to the code a few months from now.)


You also want to convert the values and use them as keys for another lookup, but that should be trivial. For example:
            row_id = ID[int(row['ID'])]
            row_frequency = Frequency[float(row['Frequency'])]
            row_assay = Assay[row['Assay']]
            d[row['Epitope']] = [row_id, row_frequency, row_assay]
You can clean this up a bit by writing the row transformation as a function, and then just using a dictionary comprehension:
with open(path, 'rb') as f:
    with csv.DictReader(f) as reader:
        d = {row['Epitope']: process_row(row) for row in reader}


                        
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