title: Nested JSON and Pandas Normalise
body: <p>I have some JSON data returned as below: (I cannot change the structure)</p>
  
  <pre><code>[
    {
      "id": "d6aca8ac",
      "owner": "test",
      "sections": {
        "summary": {
          "id": "d417cd0e",
          "notes": "",
          "created_at": "2018-11-26T19:02:06Z"
        },
        "weather": {
          "id": "7ef34660",
          "notes": ""
        },
        "task": {
          "id": "255d86dc",
          "tasks": [
            {
              "id": "t1",
              "total_hours": 176.0,
              "updated_at": "2018-11-26T19:02:06Z",
              "created_at": "2018-11-26T19:02:06Z"
            },
            {
              "id": "t2",
              "total_hours": 176.0,
              "updated_at": "2018-11-26T19:02:06Z",
              "created_at": "2018-11-26T19:02:06Z"
            }
          ]
        }
      }
    }
  ]
  </code></pre>
  
  <p>I am trying to use json_normalise from pandas to get the tasks into a dataframe like this:</p>
  
  <pre><code>+----+-------------+----------------------+----------------------+
  | id | total_hours |      updated_at      |      created_at      |
  +----+-------------+----------------------+----------------------+
  | t1 |         176 | 2018-11-26T19:02:06Z | 2018-11-26T19:02:06Z |
  | t2 |         176 | 2018-11-26T19:02:06Z | 2018-11-26T19:02:06Z |
  +----+-------------+----------------------+----------------------+
  </code></pre>
  
  <p>I have a script that iterates over hundreds of JSON files in a folder applying a different record path depending on the filename and this works for them all except this one structure so I would really like to see if I can get this result using something similar (this doesn't work obviously):</p>
  
  <pre><code>normalised_data = json_normalize(data=json_data, record_path=['sections', 'task', 'tasks'], meta=['id'], meta_prefix='parent_' , errors='ignore')
  </code></pre>
  
  <p>If that style of command cant be used then what would be my best option? So I'll have to think about separating out this particular file.</p>
  
  <p>Thanks,</p>