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Python Tutorial

1 What is Data Type ?

A data type is like a label that tells the computer what kind of information you’re working with. When you create a variable in programming, you’re essentially telling the computer, “Hey, this is going to hold a certain kind of data.”

Data types define what kind of values the variable can hold (like numbers, text, etc.), what you can do with that data (like adding, subtracting, or joining), and how the computer should store it. Think of it like sorting things into categories: numbers go in one box, words go in another, and so on. This way, the computer knows exactly how to handle and work with the data you’re giving it.

In simpler terms, data types help the computer understand and process the information you’re dealing with, ensuring everything runs smoothly and without errors.

2 Get the type:

We can also print the type of variable used:

a = 6

b = “superman” c = False

print(type(a)) #integer print(type(b)) #string print(type(c)) #boolean

<class ‘int’>

<class ‘str’>

<class ‘bool’>

We can see that when we mention the variable in the type() we get the data type of the variable. For now we saw three data type

Integer – Number datatype String – categorical datatype boolean – True/False(0/1)

Python is dynamically typed, the data type of a variable is determined at runtime based on the assigned value.

For example – In any other programming language suppose java we mention the data type before the variable.

string name – “Shweta”

3 Types of data in data types:

For now we will just know the types of data that are available, Don’t worry if you don’t understand some things. We will dive deep into each one of them in detail later. ## 1. Numeric Data Types Integers and floating points are separated by the presence or absence of a decimal point. For instance,

  • is an integer
  • is a floating-point * Int – for Integer Number Example :-

#Integer Variable

num1 = 5

Float – for Decimal Number

Example:

#Float Variable

num2 = 5.5

Complex – for Complex Number

Example:

 num3 = 3 + 4j    

3.1 2. String Data Types

In Python, a string is simply a collection of characters that represent text. You can think of it as a piece of text that can include anything from letters and numbers to symbols and spaces. Strings are one of the most commonly used data types in programming because they let you work with text in all sorts of ways. We will learn more about string later in detail.

Example :-

 company_name =”Meritshot”                                                                            

3.2 3. Sequence Data Types

In Python, a sequence is a way to store an ordered collection of elements, where the order really matters. You can access each element by its position, or index, in the sequence. Python provides several built-in sequence types that help you organize and work with collections of data easily and efficiently. * List

Example :-

fruits = [‘apple’,’banana’,’pomegranate’]

Tuple

Example :-

roll_no = (121,122,123,124,125,126,127,128,129,130)

Range

Example :-

for i in range(5):

print(i)

0

1

2

3

4

3.3 4. Binary Data Types

In Python, a binary data type represents information using a series of 0s and 1s—just like how computers handle data at a fundamental level. Think of it as the special “language” that computers use to efficiently store and process information. This binary data format is particularly useful when working with files, images, or any data that can be broken down into just two possible values. Instead of using regular numbers or letters, binary data uses combinations of 0s and 1s to represent everything from simple text to complex images. * bytes

Example :-

b1 = bytes([65, 66, 67, 68, 69])

print(b1)

b’ABCDE’

bytearray

Example :-

value = bytearray([72, 101, 108, 108, 111]) print(value)

bytearray(b’Hello’)

Now you might be wondering that bytes and bytearray have same example then where is the difference. Well you’re right they both are almost same except one thing that bytearray is mutable whereas bytes is not !!!

memoryview

Example :-

data = bytearray(b’Hello, world!’)

view = memoryview(data)

print(view)

<memory at 0x000001D9B6204880>

3.4 5. Dictionary Data Type

Python dictionaries are like special storage containers that use a hash table to organize data. You can think of them as a collection of key-value pairs.Python dictionaries are like special storage containers that use a hash table to organize data. You can think of them as a collection of key- value pairs

Example :-

dict = {121:’Moon’, 122:’Sia’, 123:’Diya’} print(dict)

{121: ‘Moon’, 122: ‘Sia’, 123: ‘Diya’}

3.5 6. Set Data Type

Set is a Python implementation of set as defined in Mathematics. A set in Python is a collection, but is not an indexed or ordered collection as string, list or tuple. An object cannot appear more than once in a set, whereas in List and Tuple, same object can appear more than once. Comma separated items in a set are put inside curly brackets or braces {}. Items in the set collection can be of different data types. * Set

Example :-

set1 = {‘pink’,’blue’,’red’,’yellow’,’green’}

set2 = {1,2,3,4,5}

print(set1)

print(set2)

{‘yellow’, ‘pink’, ‘red’, ‘green’, ‘blue’}

{1, 2, 3, 4, 5}

3.6 7. Boolean Data Type

The Boolean type in Python is a built-in data type that represents one of two values: True or False. It’s like a simple on/off switch in programming. The bool() function in Python lets you check the truth value of any expression, returning True or False based on the outcome. A Boolean value can only be True or False, which are actually just special versions of the numbers 1 and 0 in the background.

Example :-

a = True

print(a)

True

3.7 8. None Data Type

In Python, the None type is represented by the special type NoneType. It’s a unique object that signifies the absence of a value or a null value. When you see None in your code, it’s like Python’s way of saying, “There’s nothing here.”

Example :-

x = None

print(x)

None

4 Implicit Conversion (Coercion):

When Python automatically changes the type of your data during an operation, that’s called implicit conversion. It happens without you telling it to, making sure everything works smoothly without losing important information. For example, if you’re adding an integer to a float, Python will automatically turn the integer into a float so the math adds up correctly.

x = 5 # This  is  an  integer  variable

y = 5.5 # This  is  a  float  variable

result = x + y # Adding  integer  and  float  values

print(result) # Final  Value  converted  to  Float

10.5

So the above example is Implicit conversion, here Python converts the Integer variable to Float variable on its own without doing it explicitly.

x = 5 # Integer  variable

y = “Ashish” # String  Variable

result = x+y # Adding Integer and String Variable

print(result) # error generated

TypeError

Input In  [17], in <cell line: 3>()

1 x = 5 # Integer variable

2 y = “Ashish” # String Variable

—-> 3 result = x+y # Adding Integer and String Variable

4 print(result)

TypeError: unsupported operand type(s) for +: ‘int’ and ‘str’

We got a TypeError in the above example because it was not implicit conversion. The above example comes under Explicit conversion which we will learn next.

Some of the coomon Implicit conversions are :

* Integer to Float * Integer to complex * Float to complex * Boolean to Integer

result = True + 1 #Adding boolean value and Integer Value

print(result)

As discussed above there are two types of boolean values, True/False, where ‘True’ stands for ‘1’ and ‘False’ standa for ‘0’

5 Type Casting (Type Conversion in Python)

We can easily convert from one type to another type as int(), float(), and complex() methods. Type casting is simply the process of converting one type of data into another. It’s like changing the form of a value so it can be used in a different way. For example, turning a number into a string so you can combine it with text.

num1 = 10

num_str = str(num1) num2 = 20

res = num_str + num2 print(res)

TypeError

Input In  [19], in <cell line: 4>()

2 num_str = str(num1) 3 num2 = 20

—-> 4 res = num_str + num2

5 print(res)

TypeError: can only concatenate str (not “int”) to str

6 Obtaining User Input

6.1 input() function:

Takes a prompt as an optional argument and returns the user’s input as a string.

name = input(“Enter your name: “) print(“Hello, ” + name + “!”)

Enter your name: Aisha Hello, Aisha!

6.2 Converting Input Data Types:

int() function:

Converts a string to an integer.

age = int(input(“Enter your age: “))

print(“You will be”, age + 1, “next year.”)

Enter your age: 17

You will be 18 next year.

  • float() function:

Converts a string to a floating-point number.

height = float(input(“Enter your height in centimeters: “))

print(“Your height in meters is:”, height / 100)

Enter your height in centimeters: 152.5 Your height in meters is: 1.525

Combining the three examples above we get:

name = input(“Enter your name: “) age = int(input(“Enter your age: “))

height = float(input(“Enter your height in centimeters: “))

print(f”Hello, {name}!”)

print(f”You will be {age + 1} next year.”) print(f”Your height in meters is: {height / 100}“)

Enter your name: Aisha

Enter your age: 17

Enter your height in centimeters:

152.5 Hello, Aisha!

You will be 18 next year.

Your height in meters is: 1.525

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