Again, this can be solved in pure Python:
>>> map(str, [0,33,4444522])['0', '33', '4444522']
Or if you need to convert back and forth:
>>> a = np.array([0,33,4444522])>>> np.array(map(str, a))array(['0', '33', '4444522'], dtype='|S7')
You can stay in numpy, doing
np.char.mod('%d', a)
This is twice faster than map or list comprehensions for 10 elements, four times faster for 100. This and other string operations are documented here.
map
Use arr.astype(str), as int to str conversion is now supported by numpy with the desired outcome:
arr.astype(str)
int
str
numpy
import numpy as npa = np.array([0,33,4444522])res = a.astype(str)print(res)array(['0', '33', '4444522'], dtype='<U11')