我有 2 个 CSV 文件:“数据”和“映射”:

• “映射”文件有 4 列:Device_Name、GDN、Device_Type 和 Device_OS。所有四列均已填充。
• 'Data' 文件具有这些相同的列，其中 Device_Name 列已填充，其他三列为空白。
• 我希望我的 Python 代码打开这两个文件，并为数据文件中的每个 Device_Name 映射其 GDN、Device_Type 和 Device_OS 映射文件中的值。

我知道在只有 2 列时如何使用 dict(需要映射 1 列)，但是当需要映射 3 列时我不知道如何完成此操作。

以下是我尝试完成 Device_Type 映射的代码:

x = dict([])
with open("Pricing Mapping_2013-04-22.csv", "rb") as in_file1:
    file_map = csv.reader(in_file1, delimiter=',')
    for row in file_map:
       typemap = [row[0],row[2]]
       x.append(typemap)

with open("Pricing_Updated_Cleaned.csv", "rb") as in_file2, open("Data Scraper_GDN.csv", "wb") as out_file:
    writer = csv.writer(out_file, delimiter=',')
    for row in csv.reader(in_file2, delimiter=','):
         try:
              row[27] = x[row[11]]
         except KeyError:
              row[27] = ""
         writer.writerow(row)

返回属性错误。

经过一番研究，我认为我需要创建一个嵌套字典，但我不知道如何做到这一点。

最佳答案

嵌套字典是字典中的字典。很简单的事情。

>>> d = {}
>>> d['dict1'] = {}
>>> d['dict1']['innerkey'] = 'value'
>>> d['dict1']['innerkey2'] = 'value2'
>>> d
{'dict1': {'innerkey': 'value', 'innerkey2': 'value2'}}

您也可以使用 defaultdict来自 collections包以方便创建嵌套字典。

>>> import collections
>>> d = collections.defaultdict(dict)
>>> d['dict1']['innerkey'] = 'value'
>>> d  # currently a defaultdict type
defaultdict(<type 'dict'>, {'dict1': {'innerkey': 'value'}})
>>> dict(d)  # but is exactly like a normal dictionary.
{'dict1': {'innerkey': 'value'}}

您可以随意填充。

我会在你的代码中推荐一些类似的东西:

d = {}  # can use defaultdict(dict) instead

for row in file_map:
    # derive row key from something 
    # when using defaultdict, we can skip the next step creating a dictionary on row_key
    d[row_key] = {} 
    for idx, col in enumerate(row):
        d[row_key][idx] = col

根据您的comment :

may be above code is confusing the question. My problem in nutshell: I have 2 files a.csv b.csv, a.csv has 4 columns i j k l, b.csv also has these columns. i is kind of key columns for these csvs'. j k l column is empty in a.csv but populated in b.csv. I want to map values of j k l columns using 'i` as key column from b.csv to a.csv file

我的建议会是这样的(不使用默认字典):

a_file = "path/to/a.csv"
b_file = "path/to/b.csv"

# read from file a.csv
with open(a_file) as f:
    # skip headers
    f.next()
    # get first colum as keys
    keys = (line.split(',')[0] for line in f) 

# create empty dictionary:
d = {}

# read from file b.csv
with open(b_file) as f:
    # gather headers except first key header
    headers = f.next().split(',')[1:]
    # iterate lines
    for line in f:
        # gather the colums
        cols = line.strip().split(',')
        # check to make sure this key should be mapped.
        if cols[0] not in keys:
            continue
        # add key to dict
        d[cols[0]] = dict(
            # inner keys are the header names, values are columns
            (headers[idx], v) for idx, v in enumerate(cols[1:]))