array = np.array([[1, 2, 3],
[2, 3, 4]])
print(array)
print(array.shape)
print(array.size)
a = np.array(([2, 3, 4], [1, 2, 3]), dtype=np.int)
print(a, a.dtype, sep=』\n』)
a = np.zeros((3, 4))
a1 = np.ones((3, 4))
a2 = np.empty((3, 4))
a3 = np.arange(10, 20, 2)
a4 = np.arange(12).reshape(3, 4)
a5 = np.linspace(1, 10, 4)
print(a, a1, a2, a3, a4, a5, sep=』\n』)
d = np.array([[1, 2, 3],
[2, 3, 4]])
e = np.arange(6).reshape(3, 2)
print(d, e, sep=』\n』)
c = d*e
f = np.dot(d, e) # – = a.dot(b)
print(f, sep=』\n』)
a = np.random.random((2, 4))
print(a, np.sum(a, axis=1), np.max(a))
a = np.arange(0, 12, 1).reshape(3, 4)
print(a, np.mean(a, axis=1), a.max(axis=1), a.cumsum(), np.diff(a), sep=』\n』)
print(np.nonzero(a))
print(np.sort(a))
print(np.transpose(a)) # 裝置
print((a.t).dot(a)) # a的轉置乘a
print(np.clip(a, 5, 9)) # 大於9的都是9,小於5的都是5
a = np.arange(3, 15).reshape(3, 4)
print(a)
print(a[1, 3])
print(a[1:3, 1:3])
print(a.flatten()) # --將a平鋪開來
for row in a: # --迭代行
print(row)
for column in a.t: # – 迭代列
print(column)
for item in a.flat: # --將a變為乙個迭代項
print(item)
a = np.array([1, 1, 1])
b = np.array([2, 2, 2])
c = np.vstack((a, b)) # --上下合併
d = np.hstack((a, b)) # --左右合併
print(c, d)
print(a[:, np.newaxis]) # 縱向的輸出
e = np.array([1, 1, 1])[:, np.newaxis]
f = np.array([2, 2, 2])[:, np.newaxis]
g = np.hstack((e,f))
print(g)
h = np.concatenate((e, f), axis=0)
print(h)
a = np.arange(12).reshape(3, 4)
print(a)
print(np.split(a, 2, axis=1))
print(np.array_split(a, 3, axis=1)) # --不等分割
print(np.vsplit(a, 3)) # --橫向分割,縱向分割
print(np.hsplit(a, 2))
a = np.arange(4).reshape((2, 2))
b = a.copy(a)
c = a
d = b
a[0] = 11
print(a, b, c, d)
print(b is a)
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