Python Flatten Deep Nested JSON

Question

I have the following JSON structure:

{
  "comments_v2": [
    {
      "timestamp": 1196272984,
      "data": [
        {
          "comment": {
            "timestamp": 1196272984,
            "comment": "OSI Beach Party Weekend, CA",
            "author": "xxxx"
          }
        }
      ],
      "title": "xxxx commented on his own photo."
    },
    {
      "timestamp": 1232918783,
      "data": [
        {
          "comment": {
            "timestamp": 1232918783,
            "comment": "We'll see about that.",
            "author": "xxxx"
          }
        }
      ]
    }
  ]
}

I'm trying to flatten this JSON into a pandas dataframe and here is my solution:

# Read file
df = pd.read_json(codecs.open(infile, "r", "utf-8-sig"))

# Normalize
df = pd.json_normalize(df["comments_v2"])
child_column = pd.json_normalize(df["data"])
child_column = pd.concat([child_column.drop([0], axis=1), child_column[0].apply(pd.Series)], axis=1)
df_merge = df.join(child_column)
df_merge.drop(["data"], axis=1, inplace=True)

The resulting dataframe is as follows:

timestamp	title	comment.timestamp	comment.comment	comment.author	comment.group
1196272984	xxxx commented on his own photo	1196272984	OSI Beach Party Weekend, CA	XXXXX	NaN

Is there a simpler way to flat the JSON to obtain the result shown above?

Thank you!

Corralien · Accepted Answer · 2021-11-07 19:06:34Z

1

Use record_path='data' as argument of pd.json_normalize:

import json
import codecs

with codecs.open(infile, 'r', 'utf-8-sig') as jsonfile:
    data = json.load(jsonfile)
    df = pd.json_normalize(data['comments_v2'], 'data')

Output:

>>> df
   comment.timestamp              comment.comment comment.author
0         1196272984  OSI Beach Party Weekend, CA           xxxx
1         1232918783        We'll see about that.           xxxx

answered Nov 7, 2021 at 19:06

Corralien

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Jonathan Leon · Accepted Answer · 2021-11-07 19:30:47Z

1

try flatten_json (set json to js in this example)

from flatten_json import flatten^M
dic_flattened = (flatten(d, '.') for d in list(js['comments_v2']))^M
df = pd.DataFrame(dic_flattened)^M
df


    timestamp  data.0.comment.timestamp       data.0.comment.comment data.0.comment.author                             title
0  1196272984                1196272984  OSI Beach Party Weekend, CA                  xxxx  xxxx commented on his own photo.
1  1232918783                1232918783        We'll see about that.                  xxxx                               NaN

answered Nov 7, 2021 at 19:30

Jonathan Leon

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