I noticed that it’s possible to use df.rename(columns=str.lower), but not df.rename(columns=str.replace(" ", "_")).

1. Is this because it is allowed to use the variable which stores the method (str.lower), but it’s not allowed to actually call the method (str.lower())?
   There is a similar question, why the error message of df.rename(columns=str.replace(” “, “_”)) is rather confusing – without an answer on that.

2. Is it possible to use methods of the .str accessor (of pd.DataFrame().columns) inside of df.rename(columns=...)?
   The only solution I came up so far is

   df = df.rename(columns=dict(zip(df.columns, df.columns.str.replace(" ", "_"))))
   

   but maybe there is something more consistent and similar to style of df.rename(columns=str.lower)? I know df.rename(columns=lambda x: x.replace(" ", "_") works, but it doesn’t use the .str accessor of pandas columns, it uses the str.replace() of the standard library.
   The purpose of the question is explore the possibilities to use pandas str methods when renaming columns in method chaining, that’s why df.columns = df.columns.str.replace(' ', '_') is not suitable to me.

As an df example, assume:

df = pd.DataFrame([[0,1,2]], columns=["a pie", "an egg", "a nut"])