Data Types in Python

Python has several built-in data types that can be used to classify and categorize data items. These data types determine what operations can be performed on a particular piece of data.

Python supports various built-in and user-defined data types.

Built-in Data Types

Numeric Types:

• int: Represents whole numbers
  (e.g., 1, 2, 3, -1, 0).


• float:Represents real numbers with decimal points
  (e.g., 1.2, 3.14, -0.5).


• complex:Represents complex numbers with a real and imaginary part
  (e.g., 1 + 2j).

Sequence Types:

• str:Represents text data
  (e.g., "hello", "world").


• list: An ordered, mutable sequence of items
  (e.g., \[1, 2, "apple"]).


• tuple:An ordered, immutable sequence of items
  (e.g., (1, 2, "apple")).


• range:Represents a sequence of numbers.

Mapping Type:

• dict:Represents a collection of key-value pairs
  (e.g., {"name": "John", "age": 30}).

Set Types:

• set:An unordered collection of unique items
  (e.g., {1, 2, 3}).


• frozenset:An immutable set.

Boolean Type:

• bool: Represents either True or False.

Binary Types:

• bytes: Represents a sequence of single bytes.
• bytearray: A mutable sequence of bytes.
• memoryview: Provides a view of memory without copying.

Python also provides the ability to cast data types from one to another, such as converting an integer to a float. The type() function can be used to determine the data type of a variable. Additionally, Python has specialized data types such as dates, times, and arrays.

User-defined Data Types

Created using classes, arrays, and modules.

Type Checking:

Use type() function to check the type of a variable.

Operators in Python

Operators are special symbols in Python that carry out specific operations on values and variables, referred to as operands. These operators are essential for performing various tasks, including arithmetic calculations, comparisons, logical evaluations, and bitwise manipulations.

Types of Operators

Arithmetic Operators:

The operators which are used to perform arithmetic operations like addition, subtraction, division etc.

• ( + ) Addition
• ( - ) Subtraction
• ( * ) Multiplication
• ( / ) Division
• ( % ) Modulo - remainder of a division
• ( // ) Floor division - integer part of the division
• ( ** ) Exponentiation

Assignment Operators:

The operators which are used for assigning values to variables. "=" is the assignment operator.

• ( = ) assign
• ( += ) add and assign
• ( -= ) subtract and assign
• ( *= ) multiply and assign
• ( /= ) divide and assign
• ( %= ) modulo and assign
• ( //=) floor divide and assign
• ( **=) exponentiate and assign

Comparison Operators:

These compare values.

• ( == ) equal
• ( != ) not equal
• ( > ) greater than
• ( < ) less than
• ( >= ) greater than or equal to
• ( <= ) less than or equal to

Logical Operators:

These perform logical operations.

• ( and ) logical AND
• ( or ) logical OR
• ( not ) logical NOT

Bitwise Operators:

These operate on individual bits.

• ( & ) bitwise AND
• ( | ) bitwise OR
• ( ^ ) bitwise XOR
• ( ~ ) bitwise NOT
• ( << ) left shift
• ( >> ) right shift

Identity Operators:

These check if two operands refer to the same object in memory.

• ( is ) is the same object
• ( is not ) is not the same object

Membership Operators:

These test if a sequence is present in an object.

• ( in ) is present
• ( not in ) is not present

Input and Output in Python

Methods :

• Convert from String to type into other types
• eval() function
• Command-line arguments
• IndexError
• Len() function

Some important codes

1. Input Method in Python

2. Checking return type of input() method in python

3. Checking return type of input() method in python

4. Converting string type to int() in Python

5. Converting string type to float() in Python

6. Taking int value at run time in Python

7. Taking int value and print their sum in Python

Control flow Statement

Types Of Control Flow Statement

• Sequential flow
• Conditional flow
• Looping flow

Control flow Statement Graph

SEQUENTIAL STATEMENTS IN PYTHON:

In this type of execution flow, the statements are executed one after the other sequentially. By using sequential statements, we can develop simple programs.sequential statements are executed line by line.

Sequential statements (demo1.py)

CONDITIONAL STATEMENTS IN PYTHON

Conditional: Statements are executed based on the condition. As shown above in the flow graph, if the condition is true then one set of statements are executed, and if false then the other set. Conditional statements are used much in complex programs.

There are three types of conditional statements in python. They are as follows:

• if statement
• if-else statement
• if elif else statement

if statement in python:

The if statement contains an expression/condition. As per the syntax colon (:) is mandatory otherwise it throws a syntax error. The condition gives the result as a bool type, either True or False. If the condition result is True, then if block statements will be executed. If the condition result is False, then if block statements won‟t execute.

Example :-

if-else statement in python:

The if statement contains an expression/condition.The condition gives the result as bool type, which means either True or False. If the condition result is True, then if block statements will be executed. If the condition result is False, then else block statements will be executed.

Example :-

if...elif...else statement:

The if statement contains an expression/condition.The condition gives the result as bool type, which means either True or False. The conditions are evaluated in the order written. If one condition becomes True then the set of statements associated with that particular condition are executed and the execution comes out without checking other conditions.

Example :-

LOOPING (Iterations) Statement in Python

If we want to execute a group of statements multiple times, then we should go for a looping kind of execution. There are two types of loops available in python.

while loop

for loop

For Loops

For loops are typically used to iterate over a sequence (such as a list, tuple, string, or range) or other iterable objects. The loop executes once for each item in the sequence.

Example :

While Loops

While loops repeatedly execute a block of code as long as a condition is true.

Example :

Loop Control Statements

break:Terminates the loop prematurely.

continue:Skips the rest of the code inside the loop for the current iteration and moves to the next iteration.

pass: Does nothing, often used as a placeholder.

Example :

Nested Loops

Loops can be nested inside other loops. The inner loop executes completely for each iteration of the outer loop.

Example :

Looping with else

Python for and while loops can have an else clause. The else block executes when the loop finishes normally (i.e., not terminated by a break statement).

Example :

Strings in Python

Introduction to Strings in Python :-

A string is a sequence of characters enclosed in single ('), double ("), or triple (''' or """) quotes.Triple quotes are used for multi-line strings.

String Creation & Examples

Strings can include single or double quotes within them.

An empty string is created using "".

Accessing String Characters

Characters in strings can be accessed using:

indexing:

• Positive (left to right, starting at 0)
• Negative (right to left, starting at -1)

slicing : Extracting a substring using string[start:end:step].

String Immutability

Strings in Python are immutable (cannot be modified after creation).

String Operations

Concatenation (+) : Combines strings.

Repetition (*) : Repeats a string multiple times.

Length (len()) : Returns number of characters in the string.

Membership Operators

in and not in are used to check if a substring exists within a string.

Comparison Operators

Strings can be compared using ==, !=, <, >, etc., based on dictionary order.

Whitespace Handling

strip(), lstrip(), rstrip() remove spaces from ends of a string.

Substring Operations

find() / index() –Find substring (returns index or error).

rfind() / rindex() – Same as above, but search from end.

count() – Counts number of occurrences.

replace() – Replaces part of a string with another (creates a new string).

Splitting and Joining Strings

split() – Splits a string into a list using a separator.

join() – Joins a list/tuple of strings into one string using a separator.

Changing String Case

upper(), lower(), swapcase(), title(), capitalize() – Modify case of characters.

String Formatting

format() with {} or numbered/named placeholders is used to insert variables into strings.

Character Data Type

No separate char type in Python; a single character is treated as a string of length 1.

| Some Importan Programs |

1. Creating and Printing Strings

2. Multi-line Strings

3. Quotes Inside Strings

4. Empty String

5. Accessing Characters (Indexing)

6. Loop Through String

7. Slicing Strings

8. Immutability of Strings

9. String Concatenation and Repetition

10. Length of String

11. Membership Operators

12. Comparing Strings

13. Removing Spaces

14. Finding Substrings

15. Counting Substrings

16. Replacing Strings

17. Splitting Strings

18. Joining Strings

19. Changing Case

20. Formatting Strings

21. Character Data Type

functions in Pythoon

A function is one that contains a group of statements or a block of code to perform a certain task. The advantages of using functions are:

Maintaining the code is an easy way.

Code re-usability.

Example : print() is a predefined function in python that prints output on the console.

Types of functions in python:

There are many categories based on which we can categorize the functions. This categorization is based on who created it.

1. Pre-defined or built-in functions
2. User-defined functions

Predefined or built-in functions:

The functions which come installed along with python software are called predefined or built-in functions. We have covered some inbuilt functions in examples of earlier chapters. Some of them are stroid(), type(), input(), print() etc.

User-defined functions:

The functions which are defined by the developer as per the requirement are called user-defined functions. In this chapter, we shall concentrate on these kinds of functions that are user-defined.

How to Create and call a function in Python?

From creating a function to using it, these are the two things that are done.

1. Defining function
2. Calling function

Defining a function in Python :-

In the function-related terminologies above, it was clearly explained what is what and how are they used. All the points together define the function. To summarize the definition contains – def keyword, name for the function, parentheses, parameters(optional), colon (:), body, return(optional).

Syntax to define a function in Python :-

Example:Define a function that has no parameters

def display():
        print("welcome to function")

Calling a function in Python:

After defining a function, we need to call to execute the function. While calling the function, we have to call with the same name of the function which we used while defining it, otherwise we will get an error.

Example: Define a function and call it

def display():
        print("welcome to function")
display()
display()
display()

Parameters/Arguments in function :-

Based on the parameters, functions can be categorized into two types. They are:

1. Function without parameters
2. Function with parameters

Function without Parameters in Python :-

A function that has no parameters in the function definition is called a function without parameters. The syntax is given below.

def name_of_the_function();
   //body of the function to perform 
     operations

Example :- Function performing addition operation

Example :- Check a number is even or odd by using a function.

Function without Parameters in Python :-

The return statement is included in the function body, and it returns some results after doing the operations. Some point about the return statement

Syntax ;-

def name_of_function(par1,par2,..);
   //body of function to perform 
     operations
     return result

Example :- Define a function that can return multiple values

Output :-

sum of a and b: 15

subtraction of a and b: 5

How to Return multiple values from a function in Python?

Syntax :-

Modules and Packages in Python

In python a module means a saved python file. This file can contain a group of classes, methods, functions and variables. Every file with .py or .python extension is called a python file, in turn a module.

Module :-

Make a python file (.py). Example :-addmultiplication.py

Now addmultiplication.py file is a module. addmultiplication.py module contains one variable and two functions.

If we want to use other members(variable, function, etc) of a module in your program, then you should import that module by using the import keyword. After importing you can access members by using the name of that module.

This imports the entire module, making its functions, classes, and variables accessible using the module name as a namespace. For example:

Importing Specific Items :-

You can import specific functions, classes, or variables from a module using the from keyword:

This imports only the specified items, allowing you to use them directly without the module name.

For example:

Importing with an Alias:

You can use the as keyword to give an imported module or item a different name:

This can be useful for shortening long module names or avoiding name conflicts.

For example:

Importing All Items:

You can import all items from a module using the * wildcard:

Lists in Python

In Python, a list is a versatile and commonly used data structure that allows you to store a collection of items. Lists are ordered, mutable, allow duplicates, and can store heterogeneous data types. Lists are part of the core Python data structures and provide a wide range of operations to manipulate stored elements effectively.

Lists are enclosed in square brackets [] and elements are separated by commas.

They are ideal when you need a container to hold multiple related values and need to modify the contents later.

Lists can be used to store strings, numbers, booleans, objects, or even other lists (nested lists).

Creating a list in Python :-

We can create a list in python by using square brackets ‘[ ]'. The elements in the list should be comma-separated.

Example: Creating an empty list

Example: Creating a list with elements

Creating a List:

Using list() function: l = list(range(0, 10))

Using square brackets: names = ["Mohan", 10, True]

The list() function is often used to convert other iterable data types like tuples, strings, or ranges into lists.

Accessing Elements:

Indexing: Access elements using positive or negative indices. Example: names[0] or names[-1]

Slicing: Retrieve sublists using syntax list[start:stop:step]. Example: n[2:5:2]

Looping: Traverse list using for or while loops.

Mutability of Lists:

List items can be changed after creation, which makes them mutable. This is one of the key differences between lists and tuples.

Important Methods:

Aliasing vs Cloning:

Aliasing: Both variables refer to same list object. y = x

Cloning: Create a copy using x[:] or x.copy()

Aliasing causes any change in one reference to reflect in the other. Cloning avoids this by creating a new object.

Operators on Lists:

Concatenation (+): Combine two lists. a + b

Repetition (*): Repeat list elements. a * 2

These operators allow you to build and modify lists in flexible ways.

Comparison and Membership:

Comparison: [1,2,3] < [2,2,3] compares element-wise until difference is found.

Membership: 20 in x or 90 not in x returns True/False.

Membership checks are useful for conditionals, filtering, and validation tasks.

Nested Lists:

Lists within lists. Useful for representing matrices or structured data.

List Comprehension:

Create lists in one line using expressions. It provides a concise way to create and transform lists.

With condition:

List comprehensions are not only cleaner but also more efficient in performance than traditional loops in many cases.

Rough Notebook