Python中遍历字典列表、提取值并填充至目标字典的方法

现有如下字典列表：

[
    {'name':['mallesh'],'email':['m@gmail.com']},
    {'name':['bhavik'],'ssn':['1000011']},
    {'name':['jagarini'],'email':['m@gmail.com'],'phone':['111111']},
    {'name':['mallesh'],'email':['m@gmail.com'],'phone':['1234556'],'ssn':['10000012']}
]

需要基于指定键提取信息，填充到目标字典：

xml_master_dict={'name':[],'email':[],'phone':[],'ssn':[]}

提取规则：

• 若单个字典中存在目标键，就把该键对应列表里的元素（取第一个，因原始数据中每个键对应值均为单元素列表）加入目标字典的对应列表
• 若不存在目标键，则向对应列表中添加None

预期填充后的字典：

{
    'name':['mallesh','bhavik','jagarini','mallesh'],
    'email':['m@gmail.com',None,'m@gmail.com','m@gmail.com'],
    'phone':[None,None,'111111','1234556'],
    'ssn':[None,'1000011',None,'10000012'],
}

同时需要支持将填充后的字典转换为pandas DataFrame形式：

import pandas as pd

pd.DataFrame({
    'name':['mallesh','bhavik','jagarini','mallesh'],
    'email':['m@gmail.com',None,'m@gmail.com','m@gmail.com'],
    'phone':[None,None,'111111','1234556'],
    'ssn':[None,'1000011',None,'10000012'],
})

1. 填充目标字典 #

# 原始数据
data_list = [
    {'name':['mallesh'],'email':['m@gmail.com']},
    {'name':['bhavik'],'ssn':['1000011']},
    {'name':['jagarini'],'email':['m@gmail.com'],'phone':['111111']},
    {'name':['mallesh'],'email':['m@gmail.com'],'phone':['1234556'],'ssn':['10000012']}
]

# 目标字典
xml_master_dict = {'name':[],'email':[],'phone':[],'ssn':[]}

# 遍历每个字典提取对应值
for item in data_list:
    for key in xml_master_dict.keys():
        xml_master_dict[key].append(item[key][0] if key in item else None)

print(xml_master_dict)

运行后输出的字典与预期完全一致。

2. 转换为pandas DataFrame #

直接将填充完成的字典传入pd.DataFrame即可：

import pandas as pd

df = pd.DataFrame(xml_master_dict)
print(df)

输出的DataFrame内容如下：

name         email    phone       ssn
0   mallesh  m@gmail.com     None      None
1    bhavik         None     None  1000011
2  jagarini  m@gmail.com  111111      None
3   mallesh  m@gmail.com  1234556  10000012

内容的提问来源于stack exchange，提问作者myamulla_ciencia