## NumPy empty array

Python provides different functions to the users. To work with arrays, the python library provides a numpy empty array function. It is used to create a new empty array as per user instruction means given data type and shape of array without initializing elements. An array plays a major role in data science where speed matters. numpy is an acronym for numerical python. Basically, numpy is an open source project. numpy performs logical and mathematical operations of arrays. Unlike list data structure, numpy arrays are designed to use in various ways. Therefore, processing and manipulating can be done efficiently.

## Syntax and Parameters

Syntax and Parameters of NumPy empty array are given below:

## Syntax:

array = np.empty (shape, dtype(data type), order=’c’)

## Explanation:

As shown above syntax it will give a new array with the shape and data type. As shown in syntax where array is array variable name and we define numpy empty array functions such as np.empty with shape of array and data types. The values returned by array are random and by default order of array is c it is used to define whether array is multidimensional or not.

• ## shape:

It is used to determine the shape of the empty array. It can be int or tuple of int. Ex: (3, 5) or 2.

• ## dtype:

It is used to define the data type of an empty array and it is an optional parameter. The default dtype of numpy is float64.

• ## order:

It is used to determine that in which order we store multi dimensional data means C style (row style) or F style (column style).

## How does empty array Work in NumPy

• We must install Python on your system.
• We must install numpy using the pip command.
• We required basic knowledge about Python.
• We required basic knowledge about arrays.
• We can perform different operations using a numpy empty function.

## Examples to Implement NumPy empty array

Let’s see how we can implement a numpy empty array.

Basically there are two ways to implement a numpy array as follows. But both are slightly different.

1. ## Using Numpy Empty Array Function

In this method we implement a numpy empty array function. Let’s see an example for better understanding.

## Example #1

importnumpy as np

sample_array = np. empty ((3,3))

print(sample_array)

## Explanation:

We import numpy functions and use them as np. We declared variable sample_array and assigned values. We try to print the value of the variable

In the above example we implement a simple numpy empty array and it returns uninitialized values with shape and data type. Illustrate the end result of the above declaration by using the use of the following snapshot.

2. ## Using NumPy Zeros Array Function

In this method we implement a numpy array function in an efficient way and after that we are able to insert data row by row. Let’s see an example for better understanding.

## Example #1

importnumpy as np

A = np.zeros([3, 4])

print(A)

## Explanation:

We import numpy functions and use them as . We declared variable A and assigned values with zeros numpy function. Finally we try to print the value of variable

In the above method we implemented numpy zero function and it returns all zeros. Illustrate the end result of the above declaration by using the use of the following snapshot.

## Example #2

importnumpy as np

A = np.empty([4, 4], dtype=float)

print(A)

## Explanation:

In the above example we follow the same syntax but the only difference is that here we define shape and data type of empty array means we can declare shape and data type in the first example we only declared shape. Illustrate the end result of the above declaration by using the use of the following snapshot.

## Example #3 – For Order C

importnumpy as np

A = np.empty([3, 3], dtype=float, order=’C’)

print(A)

## Explanation:

We import numpy functions and use them as.We declared variable A and assigned values with an empty numpy function. Here we passed shape, data type and order in the function. Finally we try to print the value of variable

In this example we passed order in function. Illustrate the end result of the above declaration by using the use of the following snapshot.

## Example #4 – For Order F

importnumpy as np

A = np.empty([2, 2], dtype=float, order=’F’)

print(A)

## Explanation:

In the above example we have only changed the order of the array. Illustrate the end result of the above declaration by using the use of the following snapshot.

## Example #5 – For 1- Dimensional Empty Numpy Array

importnumpy as np

A = np.empty(shape= 2)

print(A)

## Explanation:

In the above example we create a 1- dimensional empty array. Here only we use a single parameter shape. Illustrate the end result of the above declaration by using the use of the following snapshot.

Same example we can execute without parameters.

importnumpy as np

A = np.empty(3)

print(A)

## Explanation:

In this example we only pass shape size without any parameter, still the result is empty that means python allows us to do this. Illustrate the end result of the above declaration by using the use of the following snapshot.

##### Example #6 – For 2- Dimensional empty numpy array

importnumpy as np

B = np.empty(shape= [3,4],dtype=int)

print(B)

## Explanation:

We import numpy functions and use them as. We declared variable B and assigned values with an empty numpy function. Here we passed shape, data type in the function. Finally we try to print the value of variable.

## Example #7 – To obtain exact data type of empty numpy array

importnumpy as np

X=np.empty(shape = [4,3], dtype = int)

print(X)

### Explanation:

In this example, we passed shape size and specific data type of empty numpy array in the function. Illustrate the end result of the above declaration by using the use of the following snapshot.

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