The function np.where just chooses elements from two arrays that are both
computed before np.where is even executed. See this StackOverflow answer
https://stackoverflow.com/a/29950752/4681187 if you want to suppress the
error.
On Thu, Apr 25, 2024 at 8:16 PM 840362492--- via NumPy-Discussion <
num
Ok, thanks package stand alone I did but how I advertise it?
Maybe you as expert can say some thing that is needed , something to
develop I want some new experience
чт, 25 апр. 2024 г., 23:30 Matti Picus :
> On 25/04/2024 23:16, Alexei Lisitsa wrote:
>
> > Waiting for answer
>
>
> What kind of an
On 25/04/2024 23:16, Alexei Lisitsa wrote:
Waiting for answer
What kind of answer would you like? I took a look at numpy_list[0] and
if it serves your needs, that is great, but I don't think such ndarray
generation routines should be added to NumPy until they become more
commonly known, us
Waiting for answer
___
NumPy-Discussion mailing list -- numpy-discussion@python.org
To unsubscribe send an email to numpy-discussion-le...@python.org
https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
Member address: arch...@mail-archive.
0
In my code, I use the following calculation for a column in the dataframe:
np.where(df_score['number'] ! = 0, 100 - ((100 * df_score[rank_column]
-50)/df_score['number']), None),I have used df_score['number']! = 0, but the
code is still wrong, ZeroDivisionError: float division by zero, even i
