Actually I'll rephrase the question - I am trying to do something like you can see in the picture - does anyone know how I can do that?

Homework question? are you confused about the code, or how Hamilton fits into the picture?

Not homework! Just trying to understand the best way to approach the issue assuming I was using Hamilton. I ended up using something like this:

def _nest_series(**series:pd.Series) -> pd.Series:
    df = pd.DataFrame(series)
    return df.apply(pd.Series.to_dict, axis=1)

Reason I needed to do this is because saving 'nested' data structures from Pandas into GCP is supported by the google cloud libraries

Oh yep. You're missing returning

df

in the

_nest_series

function. But yeah that's one way to do it. I was asking in relation to Hamilton because you'd need to name the function arguments rather than them being in **kwargs.

(homework would be OK btw 🙂 )

@James Marvin e.g. :

def my_dataframe(col_a: pd.Series, col_b: pd.Series) -> pd.DataFrame:
    return pd.DataFrame({'col_a': col_a, 'col_b': col_b})