ndim维度(也称为秩,一维数组的秩为 1,二维数组的秩为 2)。shape行数和列数。size元素个数。dtype元素类型。itemsize以字节的形式返回数组中每一个元素的大小。
【例】
import numpy as npa = np.array([1, 2, 3, 4, 5])print(a.shape) # (5,)print(a.dtype) # int32print(a.size) # 5print(a.ndim) # 1print(a.itemsize) # 4b = np.array([[1, 2, 3], [4, 5, 6.0]])print(b.shape) # (2, 3)print(b.dtype) # float64print(b.size) # 6print(b.ndim) # 2print(b.itemsize) # 8
在ndarray中所有元素必须是同一类型,否则会自动向下转换,int->float->str。
【例】
import numpy as npa = np.array([1, 2, 3, 4, 5])print(a) # [1 2 3 4 5]b = np.array([1, 2, 3, 4, '5'])print(b) # ['1' '2' '3' '4' '5']c = np.array([1, 2, 3, 4, 5.0])print(c) # [1. 2. 3. 4. 5.]
