BASIC PYTHON

Python Basics

Introduction

• Writing and Dissecting our First Program
• String Data Type
• Numeric Data Type

This chapter covers Python data types and variables' numerous aspects in other words it is a Python beginner tutorial. Python has variables and data types. They improve code understanding, making software writing easier and faster. Python's concise nature makes basic jobs easy to learn and understand. In other words, we can say that learning Python for beginners in programming is also easy and Python coding for beginners is also easy.

The interactive programming environment, standard library functions, and grammar structures of Python are extensive. Many structures and functions are available, but few are used. Thus, we will examine the most popular Python libraries, features, and traits. This section includes simple Python code snippets to help you learn therefore here we learn Python basics and we call it a basic Python course. Here we learn the basics of Python coding. It is a free Python beginner course blog. We learn Python because by default it is most common language for machine learning and deep learning.

Basic Python operations

In Python, if we want to add 2 numbers, we just need to open the Python IDLE and type the numbers and between these numbers, we introduce the “+” symbol. Below we can see the simple Python code for addition.

Addition

The preceding code sample shows Python adding basics. Python shows that adding two integers does not need a datatype definition. The Python interpreter recognizes that we want to add two integers. Python handles all other basic mathematical procedures. 

In the above code, we can see the basic mathematical operations which we can do in Python easily. Let us look at some more advanced mathematical operations we can do easily in Python but in other languages it takes some effort.

One such operation is the Floor division. In floor division, it returns the highest integer which is less than or equal to the result of the division. Its result is always rounded to the nearest integer. 

Any integer may be exponentiated easily in Python. We'll examine both ways. One uses pow() and another uses double asterisks.

The double asterisk operator exponentiates. The right operand's power raises the left operand.

Double asterisk operator exponentiation

The pow() function is a built-in function of Python that is used for exponentiation. To use this we need to use two arguments the arguments are base and exponent.

pow() function

Modulo is a popular Python math function. Modulo is performed with the '%' operator. When two numbers are split, the modulus operator mostly returns the remainder. It finds the residual and determines if two numbers are divisible in a division.

Modulo

Variables

Programmers use variables to store and handle data. The values assigned to variables reflect data. Program execution can use these values for various actions and activities. Variables are symbolic names for data storage memory regions. Programmers can store data in variables and alter them throughout the code. Python does not need variable type definition, unlike other programming languages.

Let’s look at an example of using variables in Python:

'x' in the preceding case is '5'. The value in 'x' is doubled and assigned to 'y,' which is '10'. Variables store and change data, making code more flexible and understandable.

Writing and Dissecting our First program

The code begins with a comment. Typing '#' at the beginning of a line and putting something after it tells Python to disregard it and move to the next line if we want to write something Python shouldn't execute. The code snippet above ignores the first line.

Python's print() function displays data as strings or text. It prints the parenthesis-enclosed string to the console. Input(), another built-in function, requests users to type into text fields. This function waits for the user to press ENTER before executing the program after entering. The input() function returns the user-entered string. If the user types "Kumar", the input variable evaluates it.

Python variables follow a few rules:

• Variable names are case-sensitive (‘count’ and ‘Count’ would be different variables).
• Any letter (a-z, A-Z) or an underscore “_” must come before a variable name.
• Subsequent characters in the variable name can be letters, numbers, or underscores.
• Python has some reserved keywords (e.g., ‘if’, ‘else’, ‘while’) that cannot be used as variable names.
• We cannot use Spaces on variable names, but we can use the underscore ‘_’ to separate words in variable names.

Programmers utilize variables to dynamically store and manage data, making their code more flexible and responsive to changing conditions and demands. Python variables can be updated at any moment and accurately remembered. This flexibility helps programmers alter variable values while running, ensuring the latest values are always available.

The Integer, Floating-Point, and String Data Types

Most programming languages define and gather some sort of data, and then do something useful from it, therefore it is helpful to classify them into different types of data. 

Data Type	Examples
Integers	-2,-1,0,1,2,3,4
Floating-point numbers	-1.25, -1.0, -0.5, 0.0, 0.5, 1.0
Strings	‘a’, ‘aa’, ‘b’, ‘bb’, ‘hello’, ’11 cats’

The first data type we’ll look at in this chapter is called ‘string’. They are very simple and can be used in many different ways.

String

Python uses strings or strs for text values. Python strings contain basic characters. Python treats single or double quotes as strings.

"This is a string"

'This is also a string'

Python code with single and double quotes is above. If Python prints an EOL error, we probably forgot to insert the last single quote character at the end of the string. 

Python displays an incomplete input error in the above code, and the last quote is missing. Thus, it implies a syntactic or incomplete input error.

Changing Case in a String with Methods

Changing string case is a basic Python procedure. For instance, changing a string's case from a lowercase to a title case is easy. This modification is seen in the code example below.

The 'title()' method is used to modify the case of a string in the 'name' variable. First, the Name saves "ada lovelace" in lowercase. By using 'title()' on 'name,' we may transform the string to title case, which capitalizes each word's first letter. Python methods are data-related actions. They are in parenthesis and have a dot ('.') after the variable name. Passing inputs to 'title()' in parentheses is unnecessary.

String cases can be handled in many ways. Change the string's case from lowercase to uppercase. This code is written here:

Upper() converts a string to uppercase. While lower() lowercase strings do the reverse. We commonly distrust user-provided capitalization, thus it's beneficial to lowercase the string when storing data. 

Combining or Concatenating Strings

Sometimes we need to combine strings to make things work, thus it's beneficial. String combinations and concatenations are examined in this chapter. Consider a website with a login form. Users should be allowed to submit their first and last names individually, but when they visit the site, they should see their entire name, which is merged. Example of string combining. The two strings are combined below.

Python joins strings with the '+' symbol, so read the following code: first_name and last_name are joined to make full_name.

Merging data types is not supported in Python. Python will fail if we mix "ada" with 42. Merging two data types in Python generates the following error message.

But if the number is in quotes, then Python treats it as a string and then we can combine them. 

Concatenation is another term for string joining. We can use concatenation to produce a complete message using the data we saved in the variable. Let's look at an example:

The len() Function

The len() function, which may be applied to string values or other variables containing strings, is generally used to verify the integer values of the string's character count. As an illustration, look at the code below:

In the above code, we can see that the “Rohit” string has 5 characters and when we print the length of the it using len() function it will print 5 as an output.

Numbers

Integers

Another crucial Python data type, integers can be positive, negative, or zero without decimals or fractions.  They help in counting, indexing, and other mathematical processes that need discrete, whole-number values. Python can represent very large and very small whole numbers, unlike other computer languages that limit integer size. Python allows adding, subtracting, multiplying, and dividing numbers. You can see all these actions, but we rephrase them using integer variables to make things clearer.

In the above code, we can see all the basic operations we can do in integers with their outputs.

Float

To store the decimal or fractional values in Python we use float datatype. Float data can store numbers with a decimal point. Unlike integers, floats can include fractional components, making them suitable for situations where more precision is needed in numerical values. Floats are versatile and can represent a wide range of real numbers, both positive and negative. They are commonly used in mathematical calculations, scientific computations, and any scenario where non-integer values are essential. Python provides flexibility in handling float, allowing for the expression of values in scientific notation and providing various methods for working with decimal numbers. In Float type numbers we can also do the same operations we do with integers like addition (+), subtraction (-), multiplication (*), and division (/). Below is the code for these operations in Float using the input() function and variable.

In the above code, we can see the various operations we did in float values and taking input from the user.

Summary

This Python basics tutorial chapter covered various Python variables and data types and how they improve code understanding and efficiency. Python's intuitive architecture and simple syntax make it suitable for beginners and pros. In other words, we learn the Python basic concepts and Python coding basics as well as Python basic operations.

Python math basics including addition, subtracting, multiplying, and dividing were taught. Python interprets data types correctly, so you don't need to define them.

They introduced exponentiation and floor division. Floor division returns the largest integer less than or equal to the division result, and exponentiation may be done with 'pow()' or the double asterisk operator ('**').

This chapter introduced variables, which store dynamic data. Participants studied the Python variable name standard, emphasizing case sensitivity and character exclusion.

The film presented Python's string data types and showed how to change cases, merge strings, and retrieve their length using the 'len()' function.

We examined integers and float numerical values. The focus was on how float data types handle decimal and fractional integers easily. Examples with user input demonstrated integer and float math procedures.