What if the lists were made of heterogeneous elements, such as integers, floats, and strings? This gets trickier. A quick example can describe the situation to you:
In: import numpy as np complex_list = [1,2,3] + [1.,2.,3.] + ['a','b','c'] # at first the input list is just ints Array_2 = np.array(complex_list[:3]) print ('complex_list[:3]', Array_2.dtype) # then it is ints and floats Array_2 = np.array(complex_list[:6]) print ('complex_list[:6]', Array_2.dtype) # finally we add strings print Array_2 = np.array(complex_list) ('complex_list[:] ',Array_2.dtype) Out: complex_list[:3] int64 complex_list[:6] float64 complex_list[:] <U32
As explicated by our output, it seems that float types prevail over int types, and ...
