将JSON数据从Request转换为Pandas DataFrame

Question

我正在尝试从网页中抓取一些数据并将其放入pandas数据框。我尝试并阅读了许多东西，但我无法获得想要的东西。我想要一个数据框，其中所有数据都位于单独的列和行中。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)似乎没有任何作用。有人可以尝试一下吗？

感谢您提前提供的所有帮助。

最好的问候，大卫

Answer 1

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)

Answer 2

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']])

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]

Answer 3

并且比 Justin 的（已经很有帮助）响应简单一步……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)