I'm trying to break down a program line by line. Y is a matrix of data but I can't find any concrete data on what .shape[0] does exactly.
for i in range(Y.shape[0]): if Y[i] == -1: This program uses numpy, scipy, matplotlib.pyplot, and cvxopt.
The shape attribute for numpy arrays returns the dimensions of the array. If Y has n rows and m columns, then Y.shape is (n,m). So Y.shape[0] is n.
In [46]: Y = np.arange(12).reshape(3,4) In [47]: Y Out[47]: array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) In [48]: Y.shape Out[48]: (3, 4) In [49]: Y.shape[0] Out[49]: 3 shape is a tuple that gives dimensions of the array..
>>> c = arange(20).reshape(5,4) >>> c array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11], [12, 13, 14, 15], [16, 17, 18, 19]]) c.shape[0] 5 Gives the number of rows
c.shape[1] 4 Gives number of columns
shape is a tuple that gives you an indication of the number of dimensions in the array. So in your case, since the index value of Y.shape[0] is 0, your are working along the first dimension of your array.
From http://www.scipy.org/Tentative_NumPy_Tutorial#head-62ef2d3c0a5b4b7d6fdc48e4a60fe48b1ffe5006
An array has a shape given by the number of elements along each axis: >>> a = floor(10*random.random((3,4))) >>> a array([[ 7., 5., 9., 3.], [ 7., 2., 7., 8.], [ 6., 8., 3., 2.]]) >>> a.shape (3, 4) and http://www.scipy.org/Numpy_Example_List#shape has some more examples.
In Python shape() is use in pandas to give number of row/column:
Number of rows is given by:
train = pd.read_csv('fine_name') //load the data train.shape[0] Number of columns is given by
train.shape[1]