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using function in np.where - glidecode - Feb-17-2022
I'm using np.where and trying to reference a function call instead of putting in a static value, something like:
np.where(condition,function(arg1,arg2),0) | so if conditions returns true: call function, else set value to 0
My problem is that I can't just pass the current row and I don't know how to deal with an entire array in the function.
Without serialization it would be something like:
for x in array/series:
if y > z:
x = SET VALUE
else:
x= 0does anyone know what to do here?
RE: using function in np.where - Gribouillis - Feb-17-2022
Where do arg1 and arg2 come from? I mean what are y and z?
RE: using function in np.where - glidecode - Feb-17-2022
Each row in my dataframe is for a certain date and I'm looking to only call the function on dates where it's relevant, to save computation power.
So I need to pass the date (different for each row) and a more static variable (string)
usually with np.where I just do it like: np.where(condition,sales_column/average_price,0)
But I don't know if it's even possible with np.where to reference a function.
Could be that I would need to map a function. But I like the conditional element in the np.where function.
RE: using function in np.where - Gribouillis - Feb-17-2022
You could do
np.where(condition, func(sales_column, average_price), 0)but func would be called before the
np.where() is executed, like in any function composition.
RE: using function in np.where - glidecode - Feb-18-2022
But I would then be passing an array to the function and the function would have to work on the entire array and return a modified array -> np.where would then have to handle that this gets passed into the right rows.
Maybe that's doable, I don't know. Its been surprisingly hard to find anyone describe this use-case.
RE: using function in np.where - Gribouillis - Feb-18-2022
When you write
np.where(condition,sales_column/average_price,0), the situation is similar: the result of sales_column/average_price is computed before np.where() is called. I think it works because the length of the resulting array is the same as the number of rows.
RE: using function in np.where - perfringo - Feb-18-2022
(Feb-17-2022, 07:14 PM)glidecode Wrote: I'm looking to only call the function on dates where it's relevant, to save computation power.
Is computation power (really) a bottleneck?
Maybe straightforward approach will work: create mask, new column with zeros, apply function to rows matching mask. Something like:
mask = (df[some_column] some_condition) df[new_column] = 0 df.loc[mask, new_column] = some_calculated_value