你如何在 Python 中创建嵌套的 dict? [英] How do you create nested dict in Python?

问题描述

我有 2 个 CSV 文件:数据"和映射":

• 'Mapping' 文件有 4 列:Device_Name、GDN、Device_Type 和 Device_OS.所有四列都已填充.
• 'Data' 文件具有这些相同的列，其中填充了 Device_Name 列，而其他三列为空.
• 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 <映射文件中的 code>Device_OS 值.

当只有 2 列(需要映射 1 列)时，我知道如何使用 dict，但是当需要映射 3 列时，我不知道如何实现这一点.

以下是我尝试完成Device_Type映射的代码:

x = dict([])使用 open("Pricing Mapping_2013-04-22.csv", "rb") 作为 in_file1:file_map = csv.reader(in_file1, delimiter=',')对于 file_map 中的行:typemap = [row[0],row[2]]x.append(typemap)将 open("Pricing_Updated_Cleaned.csv", "rb") 作为 in_file2，将 open("Data Scraper_GDN.csv", "wb") 作为 out_file:writer = csv.writer(out_file, delimiter=',')对于 csv.reader(in_file2, delimiter=',') 中的行:尝试:行[27] = x[行[11]]除了 KeyError:行[27] = ""writer.writerow(行)

返回属性错误.

经过一番研究，我想我需要创建一个嵌套的字典，但我不知道如何做到这一点.

解决方案

嵌套字典是字典中的字典.很简单的事情.

<预><代码>>>>d = {}>>>d['dict1'] = {}>>>d['dict1']['innerkey'] = '值'>>>d['dict1']['innerkey2'] = 'value2'>>>d{'dict1': {'innerkey': 'value', 'innerkey2': 'value2'}}

您还可以使用 defaultdict 来自 collections 包以方便创建嵌套字典.

<预><代码>>>>进口藏品>>>d = collections.defaultdict(dict)>>>d['dict1']['innerkey'] = '值'>>>d # 当前是 defaultdict 类型defaultdict(<type 'dict'>, {'dict1': {'innerkey': 'value'}})>>>dict(d) # 但与普通字典完全一样.{'dict1': {'innerkey': 'value'}}

---

您可以随意填充.

我会在您的代码中推荐类似以下内容:

d = {} # 可以使用 defaultdict(dict) 代替对于 file_map 中的行:# 从某事派生行键# 使用defaultdict时，我们可以跳过下一步在row_key上创建字典d[row_key] = {}对于 idx，enumerate(row) 中的 col:d[row_key][idx] = col

---

根据您的评论:

<块引用>

可能是上面的代码混淆了问题.我的问题简而言之:我有 2 个文件 a.csv b.csv，a.csv 有 4 列 i j k l，b.csv 也有这些列.i 是这些 csvs 的关键列.j k l 列在 a.csv 中为空，但在 b.csv 中填充.我想映射 j k 的值l 列使用 'i' 作为从 b.csv 到 a.csv 文件的关键列

我的建议是像这样的(不使用 defaultdict):

a_file = "path/to/a.csv";b_file = "path/to/b.csv";# 从文件 a.csv 中读取使用 open(a_file) 作为 f:# 跳过标题f.next()# 获取第一列作为键键 = (line.split(',')[0] for line in f)# 创建空字典:d = {}# 从文件 b.csv 读取使用 open(b_file) 作为 f:# 收集除第一个键标头以外的标头headers = f.next().split(',')[1:]# 迭代行对于 f 中的行:# 收集列cols = line.strip().split(',')# 检查以确保应该映射此键.如果 cols[0] 不在键中:继续# 给字典添加键d[cols[0]] = dict(# 内部键是标题名称，值是列(headers[idx], v) for idx, v in enumerate(cols[1:]))

请注意，解析 csv 文件有一个 csv 模块.

I have 2 CSV files: 'Data' and 'Mapping':

• 'Mapping' file has 4 columns: Device_Name, GDN, Device_Type, and Device_OS. All four columns are populated.
• 'Data' file has these same columns, with Device_Name column populated and the other three columns blank.
• I want my Python code to open both files and for each Device_Name in the Data file, map its GDN, Device_Type, and Device_OS value from the Mapping file.

I know how to use dict when only 2 columns are present (1 is needed to be mapped) but I don't know how to accomplish this when 3 columns need to be mapped.

Following is the code using which I tried to accomplish mapping of Device_Type:

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)

It returns Attribute Error.

After some researching, I think I need to create a nested dict, but I don't have any idea how to do this.

解决方案

A nested dict is a dictionary within a dictionary. A very simple thing.

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

You can also use a defaultdict from the collections package to facilitate creating nested dictionaries.

>>> 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'}}

---

You can populate that however you want.

I would recommend in your code something like the following:

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

---

According to your 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

My suggestion would be something like this (without using 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:]))

Please note though, that for parsing csv files there is a csv module.

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