import numpy as np
array1D = [20, 2, 7, 1, 34]
print(np.mean(array1D))
array2D = [[14, 17, 12, 33, 44],
[15, 6, 27, 8, 19],
[23, 2, 54, 1, 4]]
print(np.mean(array2D))
print(np.mean(array2D, axis = 0))
print(np.mean(array2D, axis = 1))
>> import numpy as np
>> a=[1,2,3,4,5]
>> np.mean(a)
3.0
import numpy as np
import numpy as np
array1D = np.array([1,2,3,4,5])
print(f'Axis = -1 --> {array1D.mean(axis=-1)}')
print(f'Axis = 0 --> {array1D.mean(axis=0)}')
Axis = -1 --> 3.0
Axis = 0 --> 3.0
array2D = np.array([[14, 17, 12, 33, 44],
[15, 6, 27, 8, 19],
[23, 2, 54, 1, 4]] )
print(f'Axis = -1 {array2D.mean(axis=-1)}')
print(f'Axis = 0 {array2D.mean(axis=0)}')
print(f'Axis = 1 {array2D.mean(axis=1)}')
Axis = -1 [24. 15. 16.8]
Axis = 0 [17.33333333 8.33333333 31. 14. 22.33333333]
Axis = 1 [24. 15. 16.8]
import numpy as np
array3D = np.array([[[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5]],
[[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5]]])
print(f'Axis = -1 --> {array3D.mean(axis=-1)}')
print(f'Axis = 0 --> {array3D.mean(axis=0)}')
print(f'Axis = 1 --> {array3D.mean(axis=1)}')
print(f'Axis = 2 --> {array3D.mean(axis=2)}')
Axis = -1 --> [[3. 3. 3.]
[3. 3. 3.]]
Axis = 0 --> [[1. 2. 3. 4. 5.]
[1. 2. 3. 4. 5.]
[1. 2. 3. 4. 5.]]
Axis = 1 --> [[1. 2. 3. 4. 5.]
[1. 2. 3. 4. 5.]]
Axis = 2 --> [[3. 3. 3.]
[3. 3. 3.]]
import numpy as np
speed = [10, 20, 30, 40]
x = np.mean(speed)
print(x)
x = np.median(speed)
print(x)
x = np.std(speed)
print(x)
x = np.var(speed)
print(x)
x = np.percentile(speed, 20)
print(f"20 percent of speed is {x} or lower")
x = np.percentile(speed, 90)
print(f"90 percent of speed is {x} or lower")
x = np.random.normal(loc=5.0, scale=.2, size=100)
print(x)
arr = np.array([10, 20, 20, 30, 30, 20])
print("Original array:")
print(arr)
print("Mode: Most frequent value in the above array:")
print(np.bincount(arr).argmax())
x = np.lcm(3, 4)
print(x)
arr = np.array([3, 6, 9])
x = np.lcm.reduce(arr)
print(x)
x = np.gcd(3, 4)
print(x)
arr = np.array([20, 8, 32, 36, 16])
x = np.gcd.reduce(arr)
print(x)