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How to Create an Array in Python?

How to Create an Array in Python

In the previous article, we have discussed how to declare an array in Python.

So, let's have a quick revision of that, and then we will see how we can create an array in Python.

Arrays are a great way of storing our numeric values into a variable in continuous locations. For declaring an array in C language, we used to specify the size of the array and then specify the elements it will hold.

The difference between an array and a list is that a list can hold multiple values of different data types whereas an array holds multiple values of the same data type.

Here we will discuss the following methods of creating an array in Python-

  1. Using numpy.
  2. Using range().
  3. Using arange().
  4. Using typecodes and initializers.

USING NUMPY-

The following program illustrates a simple way of declaring an array in python.

INPUT-

 import numpy as np   #importing the package
 x=np.array([1,2,3,4])  #array declaration
 print(x) #printing the array
 print(type(x))     #type of x
 print(x.ndim)     #dimension of array 

OUTPUT-

On executing the program, we can observe that the output displays the elements of an array, the data type of our object 'x', and its dimension(it's 1 since it's linear).

USING RANGE():

The next method that we will use here to declare an array is a range().

Here we will use the range function and for loop for declaring our array.

The first step is to initialize it and then use for loop and range together to add elements into it.

The following code illustrates how we can implement it-

INPUT-

 #array creation
 arr1=[ ]              #initialization
 for i in range(6):
     arr1.append(i)
 print(arr1)
 print(type(arr1)) 

OUTPUT-

USING ARANGE():

The next method of array declaration in Python that we will discuss is using the arange() function.

The syntax for arange() is:

 np.arange(start = ,stop= ,step= ,dtype= )
 start indicates the starting element of our array
 stop indicates the last element of our array
 step indicates the sequence or common difference between two consecutive elements.
 dtype shows the type of elements we want to insert in our array. 

Let us understand its working with the help of an example-

INPUT-

 import numpy as np
 arr=np.arange(1,10,1)  #array creation
 print(arr)             #displaying the array
 print(type(arr))       #displaying the type of array 

OUTPUT-

USING TYPECODES & INITIALIZERS-

In this approach of declaring the array we will specify a typecode and initialize the values of our array.

In this program, we will import the module array and use it for array creation-

INPUT-

 from array import *        #importing array module
 arr=('i',[1,2,3,4])        #array declaration
 for i in arr:
     print(i)               #printing the elements
 print(type(arr)) 

OUTPUT-

ACCESSING ELEMENTS OF AN ARRAY IN PYTHON:

The elements of an array can be accessed using its index-

For example-

INPUT-

 import numpy as np   #importing the package
 x=np.array([[1,2,3,4],[5,6,7,8]])  #array declaration
 print(x[0][1]) #printing the array
 print(x[0][3])
 print(x[1][2])
 print(x[1][3]) 

OUTPUT-

Let’s discuss some array operations in detail here-

The different operations that can be performed on an array in python are-

  1. Inserting an element in an array that can be done using arr.insert(position,value).

INPUT-

 import numpy as np
 x=np.array([1,2,3,4,5,6])
 print("The type of x is {}".format(type(x)))
 print("The array created is {}".format(x))
 print("The dimension of array is {}".format(x.ndim))
 #insertion of element
 y=np.insert(x,2,7,axis=0)
 print(y) 

OUTPUT-

In the output, we can observe the following things-

  • It returns the data type of x.
  • It displays the array.
  • It displays the dimension of the array.
  • It displays the array after the insertion of the new element.
  1. Deletion operation that can be performed using np.delete(array_name,index).

INPUT-

 import numpy as np
 x=np.array([1,2,3,4,5,6])
 print("The type of x is {}".format(type(x)))
 print("The array created is {}".format(x))
 print("The dimension of array is {}".format(x.ndim))
 #deletion of an element
 index=3
 x=np.delete(x,index)
 print(x) 

OUTPUT-

In the output, we can observe the following things-

  • It returns the data type of x.
  • It displays the array
  • It displays the dimension of the array.
  • It displays the array after the deletion of the specified element.
  1. We can search an element in an array using where().

INPUT-

 import numpy as np
 x=np.array([1,2,3,4,5,6])
 print("The type of x is {}".format(type(x)))
 print("The array created is {}".format(x))
 print("The dimension of array is {}".format(x.ndim))
 #searching an element
 y=np.where(x==5)
 print(y) 

OUTPUT-

In the output, we can observe the following things-

  • It returns the data type of x.
  • It displays the array.
  • It displays the dimension of the array.
  • It displays the index of the element which we have searched.
  1. Values in an array can be updated using arr[index]=new value.

INPUT-

 import numpy as np
 x=np.array([1,2,3,4,5,6])
 print("The type of x is {}".format(type(x)))
 print("The array created is {}".format(x))
 print("The dimension of array is {}".format(x.ndim))
 #updating an element
 x[1]=10
 print(x) 

OUTPUT-

In the output, we can observe the following things-

  • It returns the data type of x.
  • It displays the array.
  • It displays the dimension of the array.
  • It displays the updated array.
  1. If we want to add a number to all the elements of an array we can simply write-

INPUT-

 import numpy as np
 x=np.array([1,2,3,4,5,6])
 print("The type of x is {}".format(type(x)))
 print("The array created is {}".format(x))
 print("The dimension of array is {}".format(x.ndim))
 #adding one to every element
 print(x+1) 

OUTPUT-

In the output, we can observe the following things-

  • It returns the data type of x.
  • It displays the array.
  • It displays the dimension of the array.
  • It displays the array after1 is added to every element.
  1. We can declare two arrays and perform all kind of arithmetic operations on them-

INPUT-

 import numpy as np
 x=np.array([1,2,3,4,5])
 y=np.array([6,7,8,9,10])
 print("The type of x is {}".format(type(x)))
 print("The array created is {}".format(x))
 print("The dimension of array is {}".format(x.ndim))
 #performing basic arithmetic operations
 print(x+y)
 print(x-y)
 print(x*2)
 print(y*4) 

OUTPUT-

In the output, we can observe the following things-

  • It returns the data type of x.
  • It displays the array.
  • It displays the dimension of the array.
  • It displays the resultant arrays when x & y are added, x & y are subtracted, elements of array x are multiplied by 2, and elements of array x are multiplied by 4.

So, in this article, we discussed the different ways of creating an array in Python and performing operations on them.



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