jvalhondo / flatten

Flatten JSON in Python

flatten

Flattens JSON objects in Python. flatten_json destroys the hierarchy in your object which can be useful if you want to force your objects into a table.

Installation

pip install flatten_json

Usage

Let's say you have the following object:

dic = {
    "a": 1,
    "b": 2,
    "c": [{"d": [2, 3, 4], "e": [{"f": 1, "g": 2}]}]
}

which you want to flatten. Just apply flatten_json:

from flatten_json import flatten_json
flatten_json(dic)

Results:

{'a': '1',
 'b': '2',
 'c_0_d_0': '2',
 'c_0_d_1': '3',
 'c_0_d_2': '4',
 'c_0_e_0_f': '1',
 'c_0_e_0_g': '2'}

Usage with Pandas

For the following object:

dic = [
    {"a": 1, "b": 2, "c": {"d": 3, "e": 4}},
    {"a": 0.5, "c": {"d": 3.2}},
    {"a": 0.8, "b": 1.8},
]

We can apply flatten_json to each element in the array and then use pandas to capture the output as a dataframe.

dic_flattened = [flatten_json(d) for d in dic]

which creates an array of flattened objects:

[{'a': '1', 'b': '2', 'c_d': '3', 'c_e': '4'},
 {'a': '0.5', 'c_d': '3.2'},
 {'a': '0.8', 'b': '1.8'}]

Finally you can use pd.DataFrame to capture the flattened array:

import pandas as pd
df = pd.DataFrame(dic_flattened)

The final result as a Pandas dataframe:

	a	b	c_d	c_e
0	1	2	3	4
1	0.5	NaN	3.2	NaN
2	0.8	1.8	NaN	NaN