Basic Syntax and First Program in NumPy

Introduction

To run the Numpy program error-free and correctly, the code should be written in a proper format. The methods for writing and creating NumPy arrays in Python using basic syntax are discussed in the below article.

Numpy Basic Syntax

The syntax is a set of pre-defined instructions that should be followed to run an error-free code.

Numpy should be installed before running any Numpy program.

The steps to install Numpy are as follows :

1. Download python from www.python.org according to the operating system.
2. After installing python go to the command prompt and type python to create a python environment.
3. Install Numpy by using a python library called pip by using the command :

Basic Syntax of NumPy as follows :

• Need to import NumPy library from python by using the following command :

• np is the attribute that can be used in place of NumPy whenever creating a NumPy program in python.

Let's see some examples below to understand the Syntax for creating the Numpy Program in python :

1. Creating a numpy program in python using python list :

   Syntax :

   Code :

   Output :

   Explanation :
   While creating an array arr through the list, elements should be in [] braces, and array [ 2 4 6 8] will be printed as output.

2. Creating a numpy program using a tuple :

   Syntax :

   Code :

   Output :

   Explanation :
   Creating an array arr by using the tuple elements should be in () braces, and array [ 2 4 6 8] will be printed as output.

3. Numpy program for creating arrays of zeros :

   Syntax :

   Code :

   Output :

   Explanation :
   zeros function is used to create the numpy array in python arr of zero values. The print statement will execute the array of zero values of shape(2,3) of datatype float.

   • Shape :
     is for defining the shape of the array
   • dtype :
     is the datatype of the array
   • order :
     is whether multi-dimensional data should be stored in memory in row-major or column-major order.

4. Numpy program for creating arrays of ones :

   Syntax :

   Code :

   Output :

   Explanation :
   The ones function is used to create the array arr of ones. The print statement will execute the array of one value of shape (2,3) of the data type integer.

   • Shape :
     is for defining the shape of the array.
   • dtype :
     is the datatype of the array.
   • order :
     is whether multi-dimensional data should be stored in memory in row-major or column-major order.

5. Creating an array of random values :

   Syntax :

   Code :

   Output :

   Explanation :
   The random function generates arrays of random elements of shape(2,3) i.e 2 rows and 3 columns.

6. Creating array in range 0 to 3 of sequence 5 :

   Syntax :

   Code :

   Output :

   Explanation :
   The linspace is a built-in function of the python numpy library which is used to create a linearly spaced array by giving the start value, end value, and the total number of elements inside the linspace function.

   In the above example, an array of 5 elements between 0 to 3 is generated.

7. Creating a sequence of integers with interval :

   Syntax :

   Code :

   Output :

   Explanation :
   Inside the arange function, specify the start, end, and the difference between elements. An integer array of elements between 0 to 20 with a given difference of 4 between the elements is executed as output.

NumPy First Program

Simple Numpy programs in python :

Code :

Output :

Explanation :
Creating two arrays, arr1 using arange function of elements between 0 to 20 with difference 4 and arr2 of 4 elements using simple numpy.

2-D Numpy program

Where is the NumPy Codebase ?

The collection of source code of an application or software program is called a codebase.

Numpy Codebase is a community-driven open-source project where the source code of NumPy is developed by a diverse group of developers.

NumPy's source code can be found in this GitHub repository.