Hi, thank you for all the good work here, I like this the best of the dplyr clones.</p

Mutate with boolean expressions about dfply HOT 3 OPEN

kieferk commented on July 28, 2024

Mutate with boolean expressions

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Comments (3)

grst commented on July 28, 2024

I believe this is part of a larger problem: any kind of standard python functions that have not specifically been adapted for dfply do not work. Take for example joining multiple str columns together:

df >> mutate(new_col = "_".join([col1, col2, col3]))

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-12-4cac91689aba> in <module>
----> 1 ap_raw >> mutate(cell_name = "_".join([X.patient, X.cellid]))

TypeError: sequence item 0: expected str instance, Intention found

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jwdink commented on July 28, 2024

I think the problem is just that in python the order of operations is different. If you wrapped your conditions with parentheses I believe it would work.

E.g. this works:

from dfply import *

@make_symbolic
def np_where(bools, val_if_true, val_if_false):
    return np.where(bools, val_if_true, val_if_false)

df = pd.DataFrame({'cond1' : [0,1], 'cond2' : [1,0]})
df >> mutate(result = np_where((X.cond1 == 1) & (X.cond2 == 1), 5, 2))

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jwdink commented on July 28, 2024

Also note that the package seems to have an if_else function built in. See https://github.com/kieferk/dfply/blob/master/dfply/vector.py. Although it seems to use a list-comprehension instead of np.where, so could potentially be slower than needed.

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