Using if else statements on lambda expressions on a pandas data frame based on column names

I have a data frame df that looks like the following:

import pandas as pd
df = pd.DataFrame({'a':[78.78, 77.26], 'b':[94.47,94.06], 'c':[0.72, 0.71], 'd':[0.19, 0.29]})

For the columns a, b and c I want to extract (into a list) the min values, while for column d I want to get the max value i.e. :

[77.26, 94.06, 0.71, 0.29]

I am mainly trying to get this done with lambda expressions

to get all the min values, for instance, I could:

df.apply(lambda x:x.min(), axis = 0)

I thought about something like (of course it is not working):

df_final.apply(lambda x:x.max() if x =='d' else x.min(), axis = 0)

I have found this question which is doing something similar, though the conditional statement is based on the values of each columns, while I want my if else statement based on the column names.The thing is that x i.e. the iterable object is not the column names. How can I then apply if else conditions with lambda functions based on column names?