How to convert a JSON string with multiple columns and an index to a Pandas dataframe?

Question

I need to convert a JSON string with 2 columns and an index into a pandas dataframe but I'm facing an error I can't find a solution.

I have tried to encode the JSON with different orientations orient='columns and orient='index , I also normalized the JSON string and specified the columns name but there is still an error. It looks like it's a bit tricky, how can I do that?

This is the string I use:

> type(data)
<class 'str'>

> print(data)
{
"2020-04-02T00:00:00.000Z": {
    "A": 133.25,
    "B": 0.000155642
},
"2020-04-03T00:00:00.000Z": {
    "A": 136.45,
    "B": 0.0001498913
},
"2020-04-04T00:00:00.000Z": {
    "A": 141.55,
    "B": 0.0001471562
}
}

df = pd.DataFrame.from_dict(data)
df = pd.DataFrame.from_dict(json_normalize(data), orient='index', columns=['A', 'B'])

Python throws an error saying AttributeError: 'str' object has no attribute 'values' .

What I would like is a dataframe like this:

                                A         B
2020-04-02 00:00:00+00:00  133.25  0.000156
2020-04-03 00:00:00+00:00  136.45  0.000150
2020-04-04 00:00:00+00:00  141.55  0.000147

Thank you,

Answer 1

You can use pandas.read_json . From the doc you can specify orient = index which is an Indication of expected JSON string format in dict like {index -> {column -> value}}

>>> import pandas as pd
>>> data = """
... {
...     "2020-04-02T00:00:00.000Z": {
...         "A": 133.25,
...         "B": 0.000155642
...     },
...     "2020-04-03T00:00:00.000Z": {
...         "A": 136.45,
...         "B": 0.0001498913
...     },
...     "2020-04-04T00:00:00.000Z": {
...         "A": 141.55,
...         "B": 0.0001471562
...     }
... }"""
>>> 
>>> df = pd.read_json(data, orient='index')
>>> df
                                A         B
2020-04-02 00:00:00+00:00  133.25  0.000156
2020-04-03 00:00:00+00:00  136.45  0.000150
2020-04-04 00:00:00+00:00  141.55  0.000147

Answer 2

You can use T like this:

df = pd.DataFrame.from_dict(data).T

and result is this:

                          A         B
2020-04-02T00:00:00.000Z  133.25  0.000156
2020-04-03T00:00:00.000Z  136.45  0.000150
2020-04-04T00:00:00.000Z  141.55  0.000147

source: https://note.nkmk.me/en/python-pandas-t-transpose/