Pandas how to apply multiple functions to dataframe

Question

Is there a way to apply a list of functions to each column in a DataFrame like the DataFrameGroupBy.agg function does? I found an ugly way to do it like this:

Answer 1

I am using pandas to analyze Chilean legislation drafts. In my dataframe, the list of authors are stored as a string. The answer above did not work for me (using pandas 0.20.3). So I used my own logic and came up with this:

df.authors.apply(eval).apply(len).sum()

Concatenated applies! A pipeline!! The first apply transforms

"['Barros Montero: Ramón', 'Bellolio Avaria: Jaime', 'Gahona Salazar: Sergio']"

into the obvious list, the second apply counts the number of lawmakers involved in the project. I want the size of every pair (lawmaker, project number) (so I can presize an array where I will study which parties work on what).

Interestingly, this works! Even more interestingly, that last call fails if one gets too ambitious and does this instead:

df.autores.apply(eval).apply(len).apply(sum)

with an error:

TypeError: 'int' object is not iterable

coming from deep within /site-packages/pandas/core/series.py in apply