Extract a block of rows from 2D numpy

Question

I know this question might be trivial but I am in the learning process. Given numpy 2D array, I want to take a block of rows using slicing approach. For instance, from the following matrix, I want to extract only the first three rows, so from:

[[  1   2   3   4]
 [  5   6   7   8]
 [  9  10  11  12]
 [ 28   9 203 102]
 [577 902  11 101]]

I want:

[[  1   2   3   4]
 [  5   6   7   8]
 [  9  10  11  12]]

My code here actually still missing something. I appreciate any hint.

X = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [28, 9, 203, 102], [577, 902, 11, 101]]
X = np.array(X)
X_sliced = X[3,:]
print(X_sliced)

@user3483203 I knew it is simple but I couldn't do it. Thank you so much — Ahmad
– Ahmad, Commented Jul 16, 2018 at 21:45

AmphotericLewisAcid · Accepted Answer · 2018-07-16 22:10:15Z

1

Numpy matrices can be thought of as nested lists of lists. Element 1 is list 1, element 2 is list 2, and so on.

You can pull out a single row with x[n], where n is the row number you want.

You can pull out a range of rows with x[n:m], where n is the first row and m is the final row.

If you leave out n or m and do x[n:] or x[:m], Python will fill in the blank with either the start or beginning of the list. For example, x[n:] will return all rows from n to the end, and x[:m] will return all rows from the start to m.

You can accomplish what you want by doing x[:3], which is equivalent to asking for x[0:3].

answered Jul 16, 2018 at 22:10

AmphotericLewisAcid

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