Argenis Leon
Argenis Leon
Thanks @SethMMorton that works. Will be possible to add this feature?
Do you mean that `allow_nan` will accept `None`, `False`, and `True`?
@SethMMorton sorry for the late response. Yes, the request still handles my needs. Thanks
I am using fastnumbers to detect the number of float in a Dask series. This series can have millions of element and it can have n `None` elements. Using try-except...
Yes, I am trying to convert a string pandas series to numbers. For the record in pandas 1.0.1 I tested `to_numeric` to convert string to float and fast numbers seems...
Are this tests working?
@luis11011 This is a POC on generating random numbers for every incremental calculation. ``` mylist = list(range(0,100)) import random random.shuffle(mylist) print(mylist) number_of_groups=10 chunks = len(mylist)/number_of_groups for n in range(0,number_of_groups): print(mylist[n::number_of_groups]...
After seeing this live it, could be good to the UX to highlight the columns that will be deleted.
@BrendaHali Any other feature do you think we need to show?
We could use intercom to handle this