I'm receiving request from the API and try to process it in Python using `requests` library and `json_normalize()` function. Here are my steps:

```
import requests
from pandas.io.json import json_normalize 

url = "Some String"

headers = {

'Authorization':"Some Token"}

response = requests.request("GET", url, headers=headers)

data = response.json()

df = json_normalize(data)

```

It gives me output like that:

```
Col1                                                  Col2
[{'text': 'sometext', 'date':'1528322400000',...}]    [[1528322400000, 24], [1528322460000, 24]

```

I want to parse the nested structures inside the columns, make dataframes from them and merge on date.

The situation is that I can parse `Col1` like that: `df = json_normalize(data['Col1'])` It will give me nice dataframe with columns of from this nested json and all is fine. 

But it does not work with `Col2` because basically it's the list. While performing `df = json_normalize(data['Col2'])` I receive an error: `'list' object has no attribute 'values'`

My questions:

1. Can I parse the nested lists just like I did with `Col1` (using `json_normalize()` or smth other)?
2. Will it be easier if I will make some changes to API itself and all the column names in `Col2` just like it is in `Col1` for easier parsing?

Thanks!