[Python] Python Pandas: Passing Multiple Functions to agg() with Arguments

I'm struggling to figure out how to combine two different syntaxes for pandas' dataframe.agg() function. Take this simple data frame:

df = pd.DataFrame({'A': ['group1', 'group1', 'group2', 'group2', 'group3', 'group3'],
'B': [10, 12, 10, 25, 10, 12],
'C': [100, 102, 100, 250, 100, 102]})

>>> df
[output]
A B C
0 group1 10 100
1 group1 12 102
2 group2 10 100
3 group2 25 250
4 group3 10 100
5 group3 12 102


I know you can send two functions to agg() and get a new data frame where each function is applied to each column:

df.groupby('A').agg([np.mean, np.std])

[output]
B C
mean std mean std
A
group1 11.0 1.414214 101 1.414214
group2 17.5 10.606602 175 106.066017
group3 11.0 1.414214 101 1.414214


And I know you can pass arguments to a single function:

df.groupby('A').agg(np.std, ddof=0)

[output]
B C
A
group1 1.0 1
group2 7.5 75
group3 1.0 1


But is there a way to pass multiple functions along with arguments for one or both of them? I was hoping to find something like df.groupby('A').agg([np.mean, (np.std, ddof=0)]) in the docs, but so far no luck. Any ideas?

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