empty arrays should keep their type, but they always come back as double from array import array from numpy import array as ndarray x = array('B',range(10)) print x.typecode # 'B' x = ndarray(x) print x.dtype.char # 'l' x = array('B',[])...
>>> import numpy as np >>> np.array(([1, 2], 3), dtype='(2,)i,i') array(([1, 2], 3), dtype=[('f0', '<i4', (2,)), ('f1', '<i4')]) >>> np.array(([1, 2],), dtype='(2,)i') TypeError: int() argument must be a string, a bytes-like object or a n...
We are now running simple tests with CuPy to gauge its ability to replace our NumPy-based pipeline. Unfortunately, it appears that initializing an array takes at least 10x longer with CuPy than with Numpy. For example: $ python3.9 -m tim...
Checklist I added a descriptive title. I searched through existing issues and couldn't find a solution or duplicate issue. I searched on the web (e.g. Google) and didn't find any helpful information. I searched the Anaconda documentation...
Code Sample, a copy-pastable example if possible data = pd.read_csv('ş/_Excel File.csv') Problem description If there is a ş in the folder name read csv gives an Initializing from file failed error. Expected Output file should have been ...