1. Convert the given list into a numpy array and replace the odd elements with -2.
Lst =[[1,2,3],
[4,5,6],
[7,8,9]]
2. In the numpy array given below print all the elements ranging from 8 to 15.
arr = [1,2,3,4,5,8,9,10,12,22,32,54,99,6,7]
3. Create a 3*3 narray that includes numbers from 1 to 9 and swap columns 1 and 2.
4. In the given numpy array replace the NaN values with the average of columns
arr = np.array([[1.3, 2.5, 3.6, np.nan],
[2.6, 3.3, np.nan, 5.5],
[2.1, 3.2, 5.4, 6.5]])
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