从.csv文件使用Pandas访问JSON子属性

Question

I have this nested JSON data set which I have converted to .csv using pandas :

[{
        "attribute1": "One",
        "attribute2": "Two",
        "attribute3": [{
            "attribute4": "Four",
            "attribute5": "Five"
        }, {
            "attribute4": "Four",
            "attribute5": "Five"
        }]
    }]

df = pd.DataFrame(data, columns=["attribute1", "attribute2", "attribute3"])
df.to_csv('example.csv')

The data in the column attribute3 is still JSON. How can I access the values of subattributes of attribute3 ie attribute4 and attribute5 using indexing? For instance something like this: data[0][2:0] for getting data at zeroth row, second column and its sub attribute zero.

I would appreciate some help regarding how to access nested values. Should I flatten the one single column that contains nested values? How can I do that?

Answer 1

It would be easier to parse your original JSON ( data ) using json_normalize() :

In [5]: pd.io.json.json_normalize(data, ['attribute3'], ['attribute1','attribute2'])
Out[5]:
  attribute4 attribute5 attribute1 attribute2
0       Four       Five        One        Two
1       Four       Five        One        Two