how to add columns and values in a dataframe in python

Question

In the below JSON array

{
  "data": [
    {
      "name": "page_call_phone_clicks_logged_in_unique",
      "period": "lifetime",
      "values": [
        {
          "value": 0
        }
      ],
      "title": null,
      "description": "Number of people who logged in to Facebook and clicked the Call Now button.",
      "id": "2342/insights/page_call_phone_clicks_logged_in_unique/lifetime"
    },
    {
      "name": "page_actions_post_reactions_total",
      "period": "lifetime",
      "values": [
        {
          "value": {}
        }
      ],
      "title": null,
      "description": "Daily total post reactions of a page by type.",
      "id": "2324/insights/page_actions_post_reactions_total/lifetime"
    },
    {
      "name": "page_consumptions_by_consumption_type",
      "period": "day",
      "values": [
        {
          "value": {},
          "end_time": "2020-11-02T08:00:00+0000"
        }
      ],
      "title": "Daily Page Consumptions By Type",
      "description": "Daily: The number of clicks on any of your content, by type. Stories generated without clicks on page content (e.g., liking the page in Timeline) are not included. (Total Count)",
      "id": "432234/insights/page_consumptions_by_consumption_type/day"
    }
  ]

}

I want the value of name as column name and the value of values as a column value , for example :
Expected Output that is a single row, but I'm getting the frame as shown in the picture below Actual Output

I have tried the below code:

for data_obj in data['data']:
               column_name = data_obj['name']
               column_value = data_obj['values']
               df_results= df_results.append({column_name:column_value}, ignore_index=True)

but it's not working properly, can anyone help me out on this

Answer 1

.append appends a dataframe by a row. This is why you are getting a new row for every iteration.To set columns you can simply use df[column_name] = value. So for your use case it should look something like this.

df_results = pd.DataFrame()
for data_obj in data['data']:
               column_name = data_obj['name']
               column_value = data_obj['values']
               df_results[column_name] = column_value