# NumPy - Array Creation using Ones and Zeros

NumPy Tutorials
Introduction
Environment Setup
Array Creation using Ones and Zeros
Array Creation using Numerical Range
Array Creation using Existing Data
Data Types
Basic Indexing & Slicing
Advanced Indexing
Fancy Indexing
Arithmetic Operations
Mathematical Functions
Statistical Function
Array Comparison and Logical Operators
Copy, Views and Sort
Broadcasting
Array Manipulation

In this chapter, we will see how to create an array using One's and Zero's

## 1. numpy.empty

Return a new array of given shape and type, without initializing entries.

Note: It requires the user to manually set all the values in the array, and should be used with caution.

Example 1:

#Code to create empty array import numpy as np np.empty([2, 2]) Output: #uninitialized [[3.81391429e+180 4.53580024e+217] [5.16174075e-109 4.00979049e+087]]

## 2. numpy.zeros

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

Example 1:

# Array of three zeros. Default dtype is float import numpy as np a = np.zeros(3) print(a) Output: [0. 0. 0.]

Example 2:

# Array of zeros in 3*3 shape. Default dtype is float import numpy as np b = np.zeros((3, 3)) print(b) Output: [[0. 0. 0.] [0. 0. 0.] [0. 0. 0.]]

## 3. numpy.ones

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

Example 1:

#Code to create array with ones as per shape import numpy as np a = np.ones(3) print(a) Output: [1. 1. 1.]

Example 2:

#Code to create array with ones as per 3*3 shape import numpy as np b = np.ones((3, 3)) print(b) Output: [[1. 1. 1.] [1. 1. 1.] [1. 1. 1.]]

## 4. numpy.eye

Return a 2-D array with ones on the diagonal and zeros elsewhere. It is also called as Diagonal matrix.

Example 1:

import numpy as np a = np.eye(2) print(a) Output: [[1. 0.] [0. 1.]]

Example 2:

import numpy as np b = np.eye(3) print(b) Output: [[1. 0. 0.] [0. 1. 0.] [0. 0. 1.]]

## 5. numpy.full

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

Example 1:

#Code to create array as per mentioned shape and value import numpy as np a = np.full((2, 4), 5) print(a) Output: [[5 5 5 5] [5 5 5 5]]

Example 2:

#Code to create array as per mentioned shape and value import numpy as np b = np.full((3, 2), 10) print(b) Output: [[10 10] [10 10] [10 10]]

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