将请求中的 JSON 数据转换为 Pandas DataFrame
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Convert JSON data from Request into Pandas DataFrame
提问by DavidV
I'm trying to scrape some data from a web page and put it into a pandas dataframe. I tried and read many things but I just cannot get what I want. And I want a dataframe with all the data in separate columns and rows. Below is my code.
我正在尝试从网页中抓取一些数据并将其放入Pandas数据框中。我尝试并阅读了很多东西，但我就是无法得到我想要的东西。我想要一个数据框，其中所有数据都在单独的列和行中。下面是我的代码。
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)doesn't seem to work in any way. Could someone give it a try?
pd.read_json(a)似乎没有任何作用。有人可以试试吗？
Thanks for all the help in advance.
感谢您提前提供的所有帮助。
Best regards, David
最好的问候，大卫
采纳答案by MaxU
you can do it this way:
你可以这样做：
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']])
Result:
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]
回答by Justin Eyster
Or, more simply:
或者，更简单地说：
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.from_dict(j)
回答by Jason
And one step simpler than Justin's (already helpful) response...by putting .json() at the end of the r = requests.getline
并且比 Justin 的（已经很有帮助）响应更简单一步……将 .json() 放在r = requests.get行尾
import requests
import pandas as pd
r = requests.get('http://www.starcapital.de/test/Res_Stockmarketvaluation_FundamentalKZ_Tbl.php').json()
df = pd.DataFrame.from_dict(r)
