In this article, we will discuss how to create 1D or 2D numpy arrays filled with zeros (0s).
numpy.zeros()
Python’s Numpy module provides a function to create a numpy array of given shape & type and filled with 0’s i.e,
numpy.zeros(shape, dtype=float, order='C')
Arguments:
- shape: Shape of the numpy array. Single integer or sequence of integers.
- 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’.
Returns:
- It returns a numpy array of given shape but filled with zeros.
Let’s understand with some examples but first we need to import the numpy module,
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import numpy as np
Create 1D Numpy Array of given length and filled with zeros
Suppose we want to create a numpy array of five zeros (0s). For that we need to call the numpy.zeros() function with argument 5 i.e.
np.zeros(5)
It returns a 1D numpy array with five 0s,
array([0., 0., 0., 0., 0.])
We can assign the array returned by zeros() to a variable and print its type to confirm if it is a numpy array or not,
arr = np.zeros(5) print(arr) print(type(arr))
Output:
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[0. 0. 0. 0. 0.] <class 'numpy.ndarray'>
Create Numpy array of zeros of integer data type
By default numpy.zeros() returns a numpy array of float zeros. But if we want to create a numpy array of zeros as integers, then we can pass the data type too in the zeros() function. For example,
arr = np.zeros(5, dtype=np.int64) print(arr)
Output:
[0 0 0 0 0]
It returned a numpy array of zeros as integers because we pass the datatype as np.int64.
Create two dimensional (2D) Numpy Array of zeros
To create a multidimensional numpy array filled with zeros, we can pass a sequence of integers as the argument in zeros() function. For example, to create a 2D numpy array or matrix of 4 rows and 5 columns filled with zeros, pass (4, 5) as argument in the zeros function.
arr_2d = np.zeros( (4, 5) , dtype=np.int64) print(arr_2d)
Output:
[[0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0]]
It returned a matrix or 2D Numpy Array of 4 rows and 5 columns filled with 0s.
Create 3D Numpy Array filled with zeros
To create a 3D Numpy array filled with zeros, pass the dimensions as the argument in zeros() function. For example,
arr_3d = np.zeros( (2, 4, 5) , dtype=np.int64) print(arr_3d)
Output:
[[[0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0]] [[0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0]]]
It created a 3D Numpy array of shape (2, 4, 5).
Summary:
In this article we learned how to create 1D or 2D numpy array of given shape and filled with zeros.
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