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Supposing I have 20x100 numpy array. I want to select all columns except say 50th. So I was following this thread Extracting specific columns in numpy array but it didn't help. I tried using
x=Z[:,[:49,51:]]
but was giving error. In R it is easy to do this
x=Z[,c(1:49,51:100)]
But could not figure out in Python. Please help. Thanks
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We can use [][] operator to select an element from Numpy Array i.e. Example 1: Select the element at row index 1 and column index 2. Or we can pass the comma separated list of indices representing row index & column index too i.e.
NumPy arrays can be sorted by a single column, row, or by multiple columns or rows using the argsort() function. The argsort function returns a list of indices that will sort the values in an array in ascending value.
To select an element from Numpy Array , we can use [] operator i.e. It will return the element at given index only.
One way to get an R-like syntax here would be to use np.r_:
>>> Z = np.arange(2000).reshape(20, 100)
>>> Z.shape
(20, 100)
>>> x = Z[:,np.r_[:49,50:100]]
>>> x.shape
(20, 99)
>>> x[0,48:52]
array([48, 50, 51, 52])
and we see that the 50th column (with number 49) is missing from x.
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