Passing argument in groupby.agg with multiple functions

Question

Anyone knows how to pass arguments in a groupby.agg() with multiple functions?

Bottom line, I would like to use it with a custom function, but I wi

Answer 1

df1 = df.groupby('lvl_1')['value'].agg(['min','max',("custom_quantile",lambda x: x.quantile(q))])

for q=0.22, the output is:

       min      max         custom_quantile
lvl_1           
di     0.275401 0.530000    0.294589
fi     0.054363 0.848818    0.136555

Answer 2

Use lambda function:

q = 0.22
df1 = df.groupby('lvl_1')['value'].agg(['min','max',lambda x: x.quantile(q)])
print (df1)
            min       max  <lambda>
lvl_1                              
di     0.275401  0.530000  0.294589
fi     0.054363  0.848818  0.136555

Or is possible create f function and set it name for custom column name:

q = 0.22
f = lambda x: x.quantile(q)
f.__name__ = 'custom_quantile'
df1 = df.groupby('lvl_1')['value'].agg(['min','max',f])
print (df1)
            min       max  custom_quantile
lvl_1                                     
di     0.275401  0.530000         0.294589
fi     0.054363  0.848818         0.136555