# 8. Assignment Using Boolean Arrays Continued-nympy.zeros

My Code: <’

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# create a new column filled with `0`.

print(taxi.shape[0])
zeros = np.zeros([taxi.shape[0], 1])
print(zeros)
taxi_modified = np.concatenate([taxi, zeros], axis=1)
#print(taxi_modified)
What I expected to happen:

` numpy.zeros has following definition. numpy.` `zeros` ( shape , dtype=float , order=‘C’ )

Return a new array of given shape and type, filled with zeros.

Parameters: shape : int or tuple of ints

Shape of the new array, e.g., `(2, 3)` or `2` .

dtype : data-type, optional

The desired data-type for the array, e.g., `numpy.int8` . Default is `numpy.float64` .

order : {‘C’, ‘F’}, optional, default: ‘C’

Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.
Returns: out : ndarray

Array of zeros with the given shape, dtype, and order.
What actually happened:

I am not sure what second parameter “1” means in below code

zeros = np.zeros([taxi.shape[0], 1])

Which parameter does it represent?

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1 Like

hey @gulabs_rawat
you may refer to this documentation (you have printed part of it here) for a detailed explanation

1 - take it as the number of columns. taxi.shape[0] - will give number of rows.

hope this helps.