|
1 | | -importnumpyasnp |
2 | | - |
3 | | -ok=np.array([1,2,3]) |
4 | | -print(ok) |
5 | | -np.zeros((2,3))# 2x3 array of zeros |
6 | | -np.ones((2,3))# 2x3 array of ones |
7 | | -np.random.rand(2,3)# 2x3 array of random floats |
8 | | -np.arange(0,10,2)# Array with values from 0 to 9 with a step of 2 |
9 | | - |
10 | | -arr=np.array([[1,2,3], [4,5,6]]) |
11 | | -print(arr.shape)# Output: (2, 3) |
12 | | -print(arr.size)# Output: 6 |
13 | | -print(arr.dtype)# Output: int64 |
14 | | -print(arr.ndim)# Output: 2 |
15 | | - |
16 | | -arr=np.array([1,2,3,4,5]) |
17 | | -print(arr[1:3])# Output: [2 3] |
18 | | -arr2d=np.array([[1,2], [3,4], [5,6]]) |
19 | | -print(arr2d[1:, :])# Output: [[3 4] [5 6]] |
20 | | - |
21 | | -arr=np.array([1,2,3]) |
22 | | -print(arr+2)# Output: [3 4 5] |
23 | | -print(arr*3)# Output: [3 6 9] |
24 | | - |
25 | | -arr1=np.array([1,2,3]) |
26 | | -arr2=np.array([4,5,6]) |
27 | | -print(arr1+arr2)# Output: [5 7 9] |
28 | | - |
29 | | -arr=np.array([1,2,3]) |
30 | | -matrix=np.array([[10], [20], [30]]) |
31 | | -print(arr+matrix) |
32 | | -# Output: |
33 | | -# [[11 12 13] |
34 | | -# [21 22 23] |
35 | | -# [31 32 33]] |
36 | | -arr=np.array([1,2,3,4]) |
37 | | -print(np.sum(arr))# Output: 10 |
38 | | -print(np.mean(arr))# Output: 2.5 |
39 | | -print(np.std(arr))# Output: 1.11803 |
40 | | - |
41 | | -arr1=np.array([1,2]) |
42 | | -arr2=np.array([3,4]) |
43 | | -print(np.dot(arr1,arr2))# Output: 11 |
44 | | - |
45 | | -arr=np.array([1,2,3,4]) |
46 | | -print(np.sum(arr))# Output: 10 |
47 | | -print(np.mean(arr))# Output: 2.5 |
48 | | -print(np.std(arr))# Output: 1.11803 |
49 | | - |
50 | | -arr1=np.array([1,2]) |
51 | | -arr2=np.array([3,4]) |
52 | | -print(np.dot(arr1,arr2))# Output: 11 |
53 | | - |
54 | | -matrix=np.array([[1,2], [3,4]]) |
55 | | -print(np.linalg.inv(matrix))# Inverse of the matrix |
56 | | - |
57 | | -np.random.seed(42)# Set seed for reproducibility |
58 | | -print(np.random.rand(3,2))# 3x2 array of random floats |
| 1 | +importnumpyasnp |
| 2 | + |
| 3 | +ok=np.array([1,2,3]) |
| 4 | +print(ok) |
| 5 | +np.zeros((2,3))# 2x3 array of zeros |
| 6 | +np.ones((2,3))# 2x3 array of ones |
| 7 | +np.random.rand(2,3)# 2x3 array of random floats |
| 8 | +np.arange(0,10,2)# Array with values from 0 to 9 with a step of 2 |
| 9 | + |
| 10 | +arr=np.array([[1,2,3], [4,5,6]]) |
| 11 | +print(arr.shape)# Output: (2, 3) |
| 12 | +print(arr.size)# Output: 6 |
| 13 | +print(arr.dtype)# Output: int64 |
| 14 | +print(arr.ndim)# Output: 2 |
| 15 | + |
| 16 | +arr=np.array([1,2,3,4,5]) |
| 17 | +print(arr[1:3])# Output: [2 3] |
| 18 | +arr2d=np.array([[1,2], [3,4], [5,6]]) |
| 19 | +print(arr2d[1:, :])# Output: [[3 4] [5 6]] |
| 20 | + |
| 21 | +arr=np.array([1,2,3]) |
| 22 | +print(arr+2)# Output: [3 4 5] |
| 23 | +print(arr*3)# Output: [3 6 9] |
| 24 | + |
| 25 | +arr1=np.array([1,2,3]) |
| 26 | +arr2=np.array([4,5,6]) |
| 27 | +print(arr1+arr2)# Output: [5 7 9] |
| 28 | + |
| 29 | +arr=np.array([1,2,3]) |
| 30 | +matrix=np.array([[10], [20], [30]]) |
| 31 | +print(arr+matrix) |
| 32 | +# Output: |
| 33 | +# [[11 12 13] |
| 34 | +# [21 22 23] |
| 35 | +# [31 32 33]] |
| 36 | +arr=np.array([1,2,3,4]) |
| 37 | +print(np.sum(arr))# Output: 10 |
| 38 | +print(np.mean(arr))# Output: 2.5 |
| 39 | +print(np.std(arr))# Output: 1.11803 |
| 40 | + |
| 41 | +arr1=np.array([1,2]) |
| 42 | +arr2=np.array([3,4]) |
| 43 | +print(np.dot(arr1,arr2))# Output: 11 |
| 44 | + |
| 45 | +arr=np.array([1,2,3,4]) |
| 46 | +print(np.sum(arr))# Output: 10 |
| 47 | +print(np.mean(arr))# Output: 2.5 |
| 48 | +print(np.std(arr))# Output: 1.11803 |
| 49 | + |
| 50 | +arr1=np.array([1,2]) |
| 51 | +arr2=np.array([3,4]) |
| 52 | +print(np.dot(arr1,arr2))# Output: 11 |
| 53 | + |
| 54 | +matrix=np.array([[1,2], [3,4]]) |
| 55 | +print(np.linalg.inv(matrix))# Inverse of the matrix |
| 56 | + |
| 57 | +np.random.seed(42)# Set seed for reproducibility |
| 58 | +print(np.random.rand(3,2))# 3x2 array of random floats |