如何将纯文本转换为数据帧

Question

我正在通过Google Trends的API提取常见查询列表：

!pip install pytrends
import pandas as pd                        
from pytrends.request import TrendReq
pytrend = TrendReq()
ytrend.build_payload(kw_list=['urban dictionary'],timeframe='2019-01-01 2019-12-31')
related_queries = pytrend.related_queries()
related_queries.values()

我的问题是related_queries.values()是一个只有一个值的字典，它是纯文本：

    dict_values([{'top':                       query  value
0      the urban dictionary    100
1                definition     50
2    urban dictionary words     12
3    urban dictionary names     10
4     word urban dictionary     10
5          urban outfitters      9
6     thot urban dictionary      8
7      dog urban dictionary      6
8      cap urban dictionary      6
9     urban dictionary yeet      6
10                     yeet      6
11     top urban dictionary      5
12    stan urban dictionary      4
13  urban dictionary boomer      4
14                   boomer      4
15    fomo urban dictionary      4
16    urban dictionary drip      4
17     smh urban dictionary      4
18                      smh      4
19                urban air      3
20     tea urban dictionary      3
21   green urban dictionary      3
22     bet urban dictionary      3
23                     vsco      3
24    goat urban dictionary      3

我想将该词典转换为一个包含三列的数据框架——索引、查询和流行度。你知道怎么做吗

干杯

Answer 1

您的字典related_queries有一个名为urban dictionary的键，其中包含两个额外的字典top和rising，我将遍历最后两个键并创建数据帧字典：

dataframes = dict()

for key, value in related_queries['urban dictionary'].items():
    dataframes[key] = pd.DataFrame(value)

dataframes['top'].head(4)

#    query                  value
# 0  the urban dictionary   100
# 1  definition             51
# 2  urban dictionary words 13
# 3  word urban dictionary  11