Python中numpy模块常见用法demo实例小结

2023-08-25 20:57:04 213

本文实例总结了Python中numpy模块常见用法。分享给大家供大家参考，具体如下：

importnumpyasnp

arr=np.array([[1,2,3],[2,3,4]])
print(arr)
print(type(arr))
print('numberofdim:',arr.ndim)
print('shape:',arr.shape)
print('size:',arr.size)

[[123]
[234]]
numberofdim:2
shape:(2,3)
size:6

a32=np.array([1,23,456],dtype=np.int)
print(a32.dtype)
a64=np.array([1,23,456],dtype=np.int64)
print(a64.dtype)
f64=np.array([1,23,456],dtype=np.float)
print(f64.dtype)

int32
int64
float64

z=np.zeros((3,4))
print(z)
print(z.dtype)
print()
one=np.ones((3,4),dtype=int)
print(one)
print(one.dtype)
print()
emt=np.empty((3,4),dtype=int)
print(emt)
print(emt.dtype)
print()
ran=np.arange(12).reshape((3,4))
print(ran)
print(ran.dtype)
print()
li=np.linspace(1,10,6).reshape(2,3)
print(li)
print(li.dtype)

[[0.0.0.0.]
[0.0.0.0.]
[0.0.0.0.]]
float64
[[1111]
[1111]
[1111]]
int32
[[ 0 1072693248 1717986918 1074161254]
[1717986918 1074947686-1717986918 1075419545]
[1717986918 1075865190 0 1076101120]]
int32
[[0 1 2 3]
[4 5 6 7]
[8 91011]]
int32
[[1. 2.8 4.6]
[6.4 8.210.]]
float64

a=np.array([10,20,30,40])
b=np.arange(4)
print(a)
print(b)
print()
print(a+b)
print(a-b)
print(a*b)
print()
print(a**b)
print()
print(10*np.sin(a))
print()
print(b<3)
print()

[10203040]
[0123]
[10213243]
[10192837]
[ 0 20 60120]
[ 1 20 90064000]
[-5.44021111 9.12945251-9.88031624 7.4511316]
[True True TrueFalse]

a=np.array([[1,2],[3,4]])
b=np.arange(4).reshape(2,2)
print(a)
print(b)
print()
print(a*b)
print(np.dot(a,b))#矩阵乘法，或下面：
print(a.dot(b))
print()

[[12]
[34]]
[[01]
[23]]
[[0 2]
[612]]
[[4 7]
[815]]
[[4 7]
[815]]

a=np.random.random((2,4))
print(a)
print(np.sum(a))
print(np.min(a))
print(np.max(a))
print()
print(np.sum(a,axis=1))#返回每一行的和。axis=1代表行
print(np.min(a,axis=0))#返回每一列的最小值。axis=0代表列
print(np.mean(a,axis=1))#返回每一行的平均值

[[0.044567040.994816790.965995610.48590905]
[0.565128520.628877140.788291150.32759434]]
4.8011796551183945
0.04456704487406293
0.9948167913629338
[2.4912885 2.30989116]
[0.044567040.628877140.788291150.32759434]
[0.622822120.57747279]

A=np.arange(2,14).reshape(3,4)
print(A)
print(np.argmin(A))#最小索引
print(np.argmax(A))#最大索引
print()
print(A.mean())
print(np.median(A))#中位数
print(A.cumsum())#累加值
print(np.diff(A))#相邻差值
print()

[[2 3 4 5]
[6 7 8 9]
[10111213]]
0
11
7.5
7.5
[2 5 9142027354454657790]
[[111]
[111]
[111]]
(array([0,0,0,0,1,1,1,1,2,2,2,2],dtype=int32),array([0,1,2,3,0,1,2,3,0,1,2,3],dtype=int32))

A=np.array([[1,0],[0,3]])
print(A)
print(A.nonzero())#分别输出非零元素的行和列值
print(np.sort(A))#逐行排序后的矩阵
print(np.sort(A,axis=0))#逐列排序的矩阵
print(np.sort(A).nonzero())
print()
B=np.arange(14,2,-1).reshape(3,4)
print(B)
print(B.transpose())#转置
print((B.T).dot(B))#转置
print()
print(np.clip(B,5,9))#B中将范围限定，大于9的数都为9，小于5的都为5，之间的数不变
print()

[[10]
[03]]
(array([0,1],dtype=int32),array([0,1],dtype=int32))
[[01]
[03]]
[[00]
[13]]
(array([0,1],dtype=int32),array([1,1],dtype=int32))
[[14131211]
[10 9 8 7]
[6 5 4 3]]
[[1410 6]
[13 9 5]
[12 8 4]
[11 7 3]]
[[332302272242]
[302275248221]
[272248224200]
[242221200179]]
[[9999]
[9987]
[6555]]

A=np.arange(3,7)
print(A)
print(A[2])
print()
B=np.arange(3,15).reshape(3,4)
print(B)
print(B[2])
print(B[2][1])
print(B[2,1])
print()
print(B[2,2:])
print(B[1:,2:])
print()
forrowinB:
print(row)
print()
forcolinB.T:
print(col)
print()
print(B.flatten())
forelminB.flat:
print(elm)

[3456]
5
[[3 4 5 6]
[7 8 910]
[11121314]]
[11121314]
12
12
[1314]
[[910]
[1314]]
[3456]
[7 8 910]
[11121314]
[3 711]
[4 812]
[5 913]
[61014]
[3 4 5 6 7 8 91011121314]
3
4
5
6
7
8
9
10
11
12
13
14

#矩阵合并
A=np.array([1,1,1])
B=np.array([2,2,2])
C=np.vstack((A,B,A,B))
print(C)
print(A.shape,(A.T).shape)
print(C.shape)
print()
D=np.hstack((A,B))
print(D)
print()
print(A[np.newaxis,:])
print(A[:,np.newaxis])
print(np.hstack((A[:,np.newaxis],B[:,np.newaxis])))
print()
print(np.stack((A,B),axis=0))
print(np.stack((A,B),axis=1))
#print(np.concatenate((A,B,B,A),axis=0))
#print(np.concatenate((A,B,B,A),axis=1))

[[111]
[222]
[111]
[222]]
(3,)(3,)
(4,3)
[111222]
[[111]]
[[1]
[1]
[1]]
[[12]
[12]
[12]]
[[111]
[222]]
[[12]
[12]
[12]]

A=np.arange(12).reshape(3,4)
print(A)
print(np.split(A,2,axis=1))
print(np.split(A,3,axis=0))
print()
print(np.array_split(A,3,axis=1))#不等分割
print()
print(np.hsplit(A,2))
print(np.vsplit(A,1))

[[0 1 2 3]
[4 5 6 7]
[8 91011]]
[array([[0,1],
[4,5],
[8,9]]),array([[2, 3],
[6, 7],
[10,11]])]
[array([[0,1,2,3]]),array([[4,5,6,7]]),array([[8, 9,10,11]])]
[array([[0,1],
[4,5],
[8,9]]),array([[2],
[6],
[10]]),array([[3],
[7],
[11]])]
[array([[0,1],
[4,5],
[8,9]]),array([[2, 3],
[6, 7],
[10,11]])]
[array([[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9,10,11]])]

A=np.arange(4)
B=A
C=B
D=A.copy()
print(A,B,C,D)
A[0]=5
print(A,B,C,D)
print(id(A),id(B),id(C),id(D))#id返回指针的值（内存地址）
print()

[0123][0123][0123][0123]
[5123][5123][5123][0123]
172730832172730832172730832172730792

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Python中numpy模块常见用法demo实例小结

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