ENH: `json_normalize` flatten lists as well
#### Problem

Right now `json_normalize` will leave lists encountered within dictionaries intact:

```
import pandas as pd
df = pd.json_normalize([{"a": [1, 1]}, {"a": [1, 2]}])
print(df)
```
output:
```
        a
0  [1, 1]
1  [1, 2]
```

Each entry is a `list` object in this case. I am not really sure how this is of any use really. If I for example like to do anything with the first element of each row I would have to convert this first into yet another `DataFrame` with something like:

```
df2 = pd.DataFrame({f"a.{k}": [i[k] for i in df['a']] for k in range(len(df['a'][0]))})
print(df2)
```
output
```
   a.0  a.1
0    1    1
1    1    2
```

#### Solution

It would be really useful I think, if there is a flag or something that would enable to directly flatten lists as well. Something like `json_normalize(data, flatten_list=True)`. The list index is then used as a string in the record name, e.g. `"a.0.b", "a.1.b"` etc.

#### API breaking implications

Don't think this would break any API.

#### Alternatives

There are a few packages that already have some of this ability, but require additional dependencies and intermediate products, so are slowing down conversion:

* https://github.com/amirziai/flatten
* https://github.com/metinsenturk/flat_table
