Comments (1)
Hello - sorry it's been a long time since I checked these issues!
The reason this doesn't work is that pd.to_datetime
will try to evaluate X.timestamp
immediately, causing an error due to the fact that it doesn't know what to do with X.timestamp
.
The error will be different now in v0.3.0, but the reason is the same. If you want to use a custom window function like that in the piping syntax, you need to make a version of it that can "delay itself" when it encounters symbolic arguments.
Luckily this is quite easy, you just need to decorate a function with the @make_symbolic
decorator like so:
@make_symbolic
def to_datetime(series):
return pd.to_datetime(series)
This version of the function can be used inside the pipe:
hub2 >> mutate(time=to_datetime(X.timestamp))
I actually used this a one of the examples in the new readme documentation, because it's perfect for explaining the use of @make_symbolic
for custom window functions. Thanks for that!
Hope this helps and clears up the issue for you. Cheers
from dfply.
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