嵌套字典是字典中的字典。非常简单的事情。
>>> d = {}
>>> d['dict1'] = {}
>>> d['dict1']['innerkey'] = 'value'
>>> d
{'dict1': {'innerkey': 'value'}}
你也可以使用一个defaultdict从collections包装，以方便创建嵌套的字典。
>>> 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'}}
您可以根据需要填充。
我建议在你的代码的东西 像 下面：
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
根据您的评论：
可能是上面的代码使这个问题感到困惑。我的问题简而言之：我有2个文件a.csv b.csv，a.csv有4列ijkl，b.csv也有这些列。我是这些csv的关键列。jkl列在a.csv中为空，但在b.csv中填充。我想使用’i`作为键列将b.csv中的jk l列的值映射到a.csv文件
我的建议是什么 像 这样（不使用defaultdict）：
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:]))
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