将嵌套字典中的值拆分为 Pandas 数据帧

Question

I have a nested dictionary which returns multiple columns and rows as one value. It's being fetched from the unofficial Google Trends API and the following query returns a dictionary of pandas.DataFrames.

# Related Queries, returns a dictionary of dataframes
related_queries_dict = pytrends.related_queries()
print(related_queries_dict)

Result:

 {'jeans': {'top':                    query  value
0             mens jeans    100
1           skinny jeans     92
2            black jeans     84
3           womens jeans     62
4             blue jeans     58
5            white jeans     55
6           ripped jeans     54
7             best jeans     42
8            levis jeans     41
9                  levis     41
10           denim jeans     38
11        american eagle     37
12  american eagle jeans     36
13            levi jeans     33
14                  levi     33
15             mom jeans     30
16         jeans for men     28
17       jeans for women     28
18       hollister jeans     26
19             hollister     25
20    high waisted jeans     24
21        wrangler jeans     24
22              wrangler     23
23       plus size jeans     21
24       boyfriend jeans     20, 'rising':                              query  value
0                extreme cut jeans   6450
1            extreme cut out jeans   5800
2                 skinnygirl jeans   3000
3                      mugsy jeans    200
4                    cut out jeans    170
5                skinny girl jeans    160
6                   everlane jeans    160
7                   levi mom jeans    140
8                  judy blue jeans    120
9         not your daughters jeans    120
10                    kancan jeans    110
11                    my fit jeans    100
12              levis wedgie jeans    100
13                     amiri jeans     90
14             wrangler jeans mens     90
15                mike amiri jeans     80
16                  mom jeans band     80
17            wit and wisdom jeans     70
18               bell bottom jeans     60
19   how to get blood out of jeans     60
20              just my size jeans     60
21  how to get grease out of jeans     50
22                     ariat jeans     50
23                       ymi jeans     50
24                 mr. green jeans     50}}

I would like to split up the result into a pandas data frame so it looks something like this:

+--------+----------------------+-------+
| Index  |       query          | value |
+--------+----------------------+-------+
|      0 | mens jeans           |   100 |
|    1   | skinny jeans         |    92 |
|    2   | black jeans          |    84 |
|    3   | womens jeans         |    62 |
|    4   | blue jeans           |    58 |
|    5   | white jeans          |    55 |
|    6   | ripped jeans         |    54 |
|    7   | best jeans           |    42 |
|    8   | levis jeans          |    41 |
|    9   | levis                |    41 |
|    10  | denim jeans          |    38 |
|    11  | american eagle       |    37 |
|    12  | american eagle jeans |    36 |
|    13  | levi jeans           |    33 |
|    14  | levi                 |    33 |
|    15  | mom jeans            |    30 |
|    16  | jeans for men        |    28 |
|    17  | jeans for women      |    28 |
|    18  | hollister jeans      |    26 |
|    19  | hollister            |    25 |
|    20  | high waisted jeans   |    24 |
|    21  | wrangler jeans       |    24 |
|    22  | wrangler             |    23 |
|    23  | plus size jeans      |    21 |
+--------+----------------------+-------+

I have already searched for a similar answer on how to transform nested dictionaries into a pandas data frame but none of them takes into account splitting values.

I have no problem transforming it into a data frame using pd.DataFrame.from_dict which gives me the desired result although all values are in the same row:

df_new = pd.DataFrame.from_dict(related_queries_dict, orient='index')
df_new.head()

Result:

+-------+-------------------+-------------------+
|       |        top        |      rising       |
+-------+-------------------+-------------------+
| jeans | query value 0 ... | query value 0 ... |
+-------+-------------------+-------------------+

Answer 1

看起来 'top' 和 'rising' 已经是数据帧了，请尝试打印 call to type 以确认

print(type(related_queries_dict['jeans']['top']))