numpy.zeros() & numpy.ones() | Create a numpy array of zeros or ones

In this article we will discuss how to create a Numpy array of different shapes and initialized with 0 & 1.

numpy.zeros()

Python’s Numpy module provides a function to create a numpy array of given shape & type and all values in it initialized with 0’s i.e.

Arguments:

• shape : Shape of the numpy array. Single int or sequence of int.
• dtype : (Optional) Data type of elements. Default is float64.
• order : (Optional) Order in which data is stored in multi-dimension array i.e. in row major(‘F’) or column major (‘C’). Default is ‘C’.

Let’s see some examples,

Create a flattened numpy array filled with all zeros

Output:

Here, in shape argument we passed 5. So, it returned a flattened numpy array of 5 zeros.

Create a 2D numpy array with 5 rows & 6 columns, filled with 0’s

Output:

Here we passed (5,6) as shape argument in numpy.zeros(), therefore it returned a 2D numpy array of 5 rows & 6 column with all zeros.
As default type was float64. Let’s see how to pass the data type int64 i.e.

Output:

It will create a 2D numpy array of ints filled with zeros.

numpy.ones()

Python’s Numpy module provides a function to create a numpy array of given shape & type and all values in it initialized with 1’s i.e.

Arguments:

• shape : Shape of the numpy array. Single int or sequence of int.
• dtype : (Optional) Data type of elements. Default is float64.
• order : (Optional) Order in which data is stored in multi-dimension array i.e. in row major(‘F’) or column major (‘C’). Default is ‘C’.

Let’s see some examples,

Create a flattened numpy array filled with all Ones

Output:

Here, in shape argument we passed 5. So, it returned a flattened numpy array of 5 zeros.

Create a 2D numpy array with 3 rows & 4 columns, filled with 1’s

Output:

Here we passed (3,4) as shape argument in numpy.ones(), therefore it returned a 2D numpy array of 3 rows & 4 column with all zeros.
As default type was float64. Let’s see how to pass the data type int64 i.e.

Output:

It will create a 2D numpy array of ints filled with ones.

Complete example is as follows,

Output

 

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