yea I know what you mean. The main use I have found is something like. Say you have a price per company_id and per transaction_id. Now you have some function, w

yea I know what you mean. The main use I have found is something like. Say you have a price per company_id and per transaction_id. Now you have some function, which for the sake of it, takes it to an exponent. i used to write a lot of functions which went like this: def convert_price(price_frame:pd.DataFrame) -> pd.DataFrame: price_frame["new_price"] = np.exp(price_frame) return price_frame and i came back to these functions, and i was always like. hmm what needs to be in the price frame. which columns etc. Also it mutates the state of the data frame while i now write functions like def convert_price(price:pd.Series) -> pd.Series: return np.exp(price) However what is good as well you can treat the series as a single dimensional array and do operations on it. Its not a perfect example since im not using the ids haha but you might see what i mean :D