In this article, we will discuss how to create 1D or 2D numpy arrays filled with zeros (0s).
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')
- 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’.
- 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,
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.
It returns a 1D numpy array with five 0s,
- Convert a Pandas Series or Index to a NumPy array
- How to Remove Columns from NumPy Array
- Remove elements from Array Greater than a Value in Python
- Sort a NumPy Array in descending order in Python
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))
[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)
[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)
[[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)
[[[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).
In this article we learned how to create 1D or 2D numpy array of given shape and filled with zeros.