What does .shape[] do in "for i in range(Y.shape[0])"?

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.

6 Answers

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

 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 has some more examples.

In python, Suppose you have loaded up the data in some variable train:

train = pandas.read_csv('file_name') >>> train train([[ 1., 2., 3.], [ 5., 1., 2.]],) 

I want to check what are the dimensions of the 'file_name'. I have stored the file in train

>>>train.shape (2,3) >>>train.shape[0] # will display number of rows 2 >>>train.shape[1] # will display number of columns 3 

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] 

shape() consists of array having two arguments rows and columns.

if you search shape[0] then it will gave you the number of rows. shape[1] will gave you number of columns.