Converting data in a dictionary format into one in Pandas DataFrame

**Is your feature request related to a problem? Please describe.**
When obtaining the data via yahooquery, there seem to be Python dictionary and Pandas DataFrame formats. I would like to be able either to convert between those two formats OR to obtain data in whichever format.

```
aapl = Ticker('aapl')
aapl.institution_ownership

aapl = Ticker('aapl')
aapl.get_modules('institutionOwnership')
```

The advantage is that I can just call `all_modules` once and get every module (e.g., `institutionOwnership` and others) already. Saving requests and not reaching the rate limit.

Another advantage is that depending one when/why/how, I use one method or another. It'd be easier to compare two different data from the same ticker, etc.

**Describe the solution you'd like**
Is there a way to convert data in a dictionary format into one in Pandas DataFrame (vice verse).
For example, I can take `aapl.get_modules('institutionOwnership')` and turn it into the same DF format as `aapl.institution_ownership`

```
aapl = Ticker('aapl')
dict_to_dataframe(aapl.get_modules('institutionOwnership'))
```

or

```
aapl = Ticker('aapl')
data = aapl.all_modules
dict_to_dataframe(data['institutionOwnership'])
```

In fact, some of these seems to be already available via functions in `ticker` class, e.g., `to_dataframe`.

Or perhaps there's already a way to do this :)

**Describe alternatives you've considered**
Alternatively, I just call `aapl.institution_ownership` and other modules one-by-one. It's a bad since calling all_modules is just one call, so it would save everyone many requests.