从数据框创建嵌套字典答案

【问题标题】：Create a nested dictionary from a dataframe从数据框创建嵌套字典
【发布时间】：2021-11-16 04:40:14
【问题描述】：

我正在尝试从数据框创建嵌套字典，但不包含列名（即“描述”）作为另一个级别。

这是我的开始：

d = {"field_name": ["foo", "foo", "foo", "bar", "bar"],
  "values": ["key1", "key2", "key3", "key1", "key5"],
 "description": ["value1", "value2", "value3", "value4", "value6"]}
df = pd.DataFrame(data=d)
df.head()

field_name	values	description
foo	key1	value1
foo	key2	value2
foo	key3	value3
bar	key1	value4
bar	key5	value6

这是我目前拥有的：

df.groupby("field_name")[["values","description"]].apply(lambda x: x.set_index("values").to_dict(orient="dict")).to_dict()

{'bar': {'description': {'key1': 'value4', 'key5': 'value6'}},
 'foo': {'description': {'key1': 'value1', 'key2': 'value2', 'key3': 'value3'}}}

这就是我想要的：

{'bar': {'key1': 'value4', 'key5': 'value6'},
     'foo': {'key1': 'value1', 'key2': 'value2', 'key3': 'value3'}}

【问题讨论】：

标签： python dictionary

【解决方案1】：

以下python代码是您问题的解决方案

import pandas as pd

d = {"field_name": ["foo", "foo", "foo", "bar", "bar"],
     "values": ["key1", "key2", "key3", "key1", "key5"],
     "description": ["value1", "value2", "value3", "value4", "value6"]}
df = pd.DataFrame(data=d)
print(df.values)

resultant_dict = {}
"""
df.values is like
[['foo' 'key1' 'value1']
 ['foo' 'key2' 'value2']
 ['foo' 'key3' 'value3']
 ['bar' 'key1' 'value4']
 ['bar' 'key5' 'value6']]
"""
for i in df.values:
    if i[0] in resultant_dict:
        resultant_dict[i[0]][i[1]] = i[2]
    else:
        resultant_dict[i[0]] = {i[1]: i[2]}

print(resultant_dict)

# Resultant Dict is {'foo': {'key1': 'value1', 'key2': 'value2', 'key3': 'value3'}, 'bar': {'key1': 'value4', 
# 'key5': 'value6'}}

【讨论】：