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machphymachphy
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sql update
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8 files changed

+682
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‎mere_dost.csv‎

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name,marks,city
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ajay,45,gorakhpur
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vijay,10,kushingar
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mohan,42,kasia
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jadish,45,lucknow
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krishna,36,odisha

‎numpy/__pycache__/numpy.cpython-312.pyc‎

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‎numpy/numpy.py‎

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import numpy as np
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ok= np.array([1, 2, 3])
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print(ok)
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np.zeros((2, 3)) # 2x3 array of zeros
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np.ones((2, 3)) # 2x3 array of ones
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np.random.rand(2, 3) # 2x3 array of random floats
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np.arange(0, 10, 2) # Array with values from 0 to 9 with a step of 2
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arr = np.array([[1, 2, 3], [4, 5, 6]])
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print(arr.shape) # Output: (2, 3)
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print(arr.size) # Output: 6
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print(arr.dtype) # Output: int64
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print(arr.ndim) # Output: 2
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arr = np.array([1, 2, 3, 4, 5])
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print(arr[1:3]) # Output: [2 3]
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arr2d = np.array([[1, 2], [3, 4], [5, 6]])
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print(arr2d[1:, :]) # Output: [[3 4] [5 6]]
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arr = np.array([1, 2, 3])
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print(arr + 2) # Output: [3 4 5]
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print(arr * 3) # Output: [3 6 9]
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arr1 = np.array([1, 2, 3])
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arr2 = np.array([4, 5, 6])
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print(arr1 + arr2) # Output: [5 7 9]
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arr = np.array([1, 2, 3])
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matrix = np.array([[10], [20], [30]])
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print(arr + matrix)
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# Output:
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# [[11 12 13]
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# [21 22 23]
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# [31 32 33]]
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arr = np.array([1, 2, 3, 4])
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print(np.sum(arr)) # Output: 10
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print(np.mean(arr)) # Output: 2.5
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print(np.std(arr)) # Output: 1.11803
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arr1 = np.array([1, 2])
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arr2 = np.array([3, 4])
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print(np.dot(arr1, arr2)) # Output: 11
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arr = np.array([1, 2, 3, 4])
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print(np.sum(arr)) # Output: 10
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print(np.mean(arr)) # Output: 2.5
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print(np.std(arr)) # Output: 1.11803
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arr1 = np.array([1, 2])
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arr2 = np.array([3, 4])
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print(np.dot(arr1, arr2)) # Output: 11
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matrix = np.array([[1, 2], [3, 4]])
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print(np.linalg.inv(matrix)) # Inverse of the matrix
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np.random.seed(42) # Set seed for reproducibility
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print(np.random.rand(3, 2)) # 3x2 array of random floats
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import numpy as np
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ok= np.array([1, 2, 3])
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print(ok)
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np.zeros((2, 3)) # 2x3 array of zeros
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np.ones((2, 3)) # 2x3 array of ones
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np.random.rand(2, 3) # 2x3 array of random floats
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np.arange(0, 10, 2) # Array with values from 0 to 9 with a step of 2
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arr = np.array([[1, 2, 3], [4, 5, 6]])
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print(arr.shape) # Output: (2, 3)
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print(arr.size) # Output: 6
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print(arr.dtype) # Output: int64
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print(arr.ndim) # Output: 2
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arr = np.array([1, 2, 3, 4, 5])
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print(arr[1:3]) # Output: [2 3]
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arr2d = np.array([[1, 2], [3, 4], [5, 6]])
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print(arr2d[1:, :]) # Output: [[3 4] [5 6]]
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arr = np.array([1, 2, 3])
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print(arr + 2) # Output: [3 4 5]
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print(arr * 3) # Output: [3 6 9]
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arr1 = np.array([1, 2, 3])
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arr2 = np.array([4, 5, 6])
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print(arr1 + arr2) # Output: [5 7 9]
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arr = np.array([1, 2, 3])
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matrix = np.array([[10], [20], [30]])
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print(arr + matrix)
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# Output:
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# [[11 12 13]
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# [21 22 23]
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# [31 32 33]]
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arr = np.array([1, 2, 3, 4])
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print(np.sum(arr)) # Output: 10
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print(np.mean(arr)) # Output: 2.5
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print(np.std(arr)) # Output: 1.11803
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arr1 = np.array([1, 2])
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arr2 = np.array([3, 4])
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print(np.dot(arr1, arr2)) # Output: 11
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arr = np.array([1, 2, 3, 4])
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print(np.sum(arr)) # Output: 10
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print(np.mean(arr)) # Output: 2.5
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print(np.std(arr)) # Output: 1.11803
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arr1 = np.array([1, 2])
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arr2 = np.array([3, 4])
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print(np.dot(arr1, arr2)) # Output: 11
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matrix = np.array([[1, 2], [3, 4]])
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print(np.linalg.inv(matrix)) # Inverse of the matrix
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np.random.seed(42) # Set seed for reproducibility
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print(np.random.rand(3, 2)) # 3x2 array of random floats

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