将请求中的JSON数据转换成熊猫数据框

Question

我试图从网页中抓取一些数据并将其放入熊猫数据框中。我尝试并阅读了很多东西，但我无法得到我想要的东西。我想要一个数据框，将所有数据放在不同的行和列中。以下是我的代码。

import requests 
import json 
import pandas as pd 
from pandas.io.json import json_normalize 

r = requests.get('http://www.starcapital.de/test/Res_Stockmarketvaluation_FundamentalKZ_Tbl.php') 

a = json.loads(r.text) 

res = json_normalize(a) 
##print(res) 

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

##df = pd.read_json(a) 
##print(df) 

pd.read_json(a)似乎没有任何工作。有人可以试一试吗？

感谢您提前提供的所有帮助。

最好的问候，大卫

Answer 1

你能做到这样：

import requests 
import pandas as pd 

r = requests.get('http://www.starcapital.de/test/Res_Stockmarketvaluation_FundamentalKZ_Tbl.php') 

j = r.json() 

df = pd.DataFrame([[d['v'] for d in x['c']] for x in j['rows']], 
        columns=[d['label'] for d in j['cols']]) 

结果：

In [217]: df 
Out[217]: 
        Country Weight CAPE PE PC PB PS DY RS 26W RS 52W Score 
0     Russia  1.1 5.9 9.1 5.1 1.0 0.9 3.7 1.22 1.35 1.0 
1     China  1.1 12.8 7.2 4.5 0.9 0.6 4.2 1.05 1.13 2.0 
2     Italy  1.0 12.7 31.5 5.7 1.2 0.6 3.3 1.13 1.11 3.0 
3     Austria  0.2 14.3 21.7 7.3 1.1 0.7 2.5 1.10 1.15 4.0 
4     Norway  0.4 12.8 32.4 7.4 1.6 1.2 4.0 1.10 1.17 5.0 
5     Hungary  0.0 12.5 49.8 7.5 1.4 0.7 2.3 1.12 1.19 6.0 
6     Spain  1.2 11.7 24.7 7.0 1.4 1.2 3.7 1.08 1.11 7.0 
7     Czech  0.0 8.9 13.6 6.1 1.3 1.0 6.7 1.03 1.05 8.0 
8     Brazil  1.3 9.8 42.1 7.4 1.6 1.2 3.0 1.06 1.24 9.0 
9     Portugal  0.1 11.3 29.0 4.8 1.5 0.7 3.9 1.05 1.06 10.0 
..      ...  ... ... ... ... ... ... ...  ...  ... ... 
42  EMERGING MARKETS 13.5 14.0 16.0 8.8 1.6 1.3 2.9 1.04 1.11 NaN 
43  DEVELOPED EUROPE 22.4 16.6 26.5 9.9 1.8 1.1 3.2 1.06 1.08 NaN 
44   EMERGING EUROPE  1.7 8.6 10.9 5.8 1.1 0.8 3.4 1.13 1.20 NaN 
45  EMERGING AMERICA  3.0 15.2 30.1 9.4 1.9 1.2 2.4 1.03 1.11 NaN 
46 DEVELOPED ASIA-PACIFIC 17.7 NaN 17.7 8.8 1.3 0.9 2.5 1.03 1.09 NaN 
47 EMERGING ASIA-PACIFIC  6.9 14.9 15.1 9.1 1.8 1.4 2.7 1.01 1.08 NaN 
48   EMERGING AFRICA  0.8 NaN 16.5 10.6 2.0 1.4 3.8 1.06 1.12 NaN 
49    MIDDLE EAST  1.3 NaN 13.7 11.8 1.5 1.8 3.9 1.06 1.10 NaN 
50     BRIC  5.9 11.8 14.6 7.4 1.4 1.2 2.7 1.06 1.16 NaN 
51  OTHER EMERGING MKT.  2.5 NaN 17.7 12.9 1.8 1.5 3.1 1.16 1.20 NaN 

[52 rows x 11 columns]