
np.r_:是按列连接两个矩阵,就是把两矩阵上下相加,要求列数相等,类似于pandas中的concat()。
np.c_:是按行连接两个矩阵,就是把两矩阵左右相加,要求行数相等,类似于pandas中的merge()。
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = np.c_[a,b] print(np.r_[a,b])
print('\n')
print(c)
print('\n')
print(np.c_[c,a])
################################
结果:
[1 2 3 4 5 6] [[1 4]
[2 5]
[3 6]] [[1 4 1]
[2 5 2]
[3 6 3]]
其它函数
a = np.arange( 10, 30, 5 )
print(a)
# [10 15 20 25] a = np.arange(15).reshape(3, 5)
print(a)
# [[ 0 1 2 3 4]
# [ 5 6 7 8 9]
# [10 11 12 13 14]] a = np.array([1,2,3,4,5,6,7,8,9]).reshape(3,3)
print(a)
# [[1 2 3]
# [4 5 6]
# [7 8 9]] a = np.zeros((3,4))
print(a)
# [[0. 0. 0. 0.]
# [0. 0. 0. 0.]
# [0. 0. 0. 0.]] a = np.linspace( 0, 2, 9 )
print(a)
# [0. 0.25 0.5 0.75 1. 1.25 1.5 1.75 2. ] a = np.ones(3, dtype=np.int32)
print(a)
# [1 1 1] a = np.ones((2,3), dtype=int)
print(a)
# [[1 1 1]
# [1 1 1]]