我正在通过Google趋势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()
是一本只有一个值的字典,即纯文本:
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
我想将该字典转换为具有三列的数据框-索引,查询和流行度。知道怎么做吗?
干杯
答案 0 :(得分:1)
您的字典related_queries
有一个名为urban dictionary
的键,其中包含两个附加字典top
和rising
,我将遍历这最后两个键并创建一个数据帧字典:
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