PO Basic Data Types | Python Course

Python comes with several built-in data types. These are used to define the type of data that a variable holds.

Python automatically detects the type when you assign a value to a variable (thanks to dynamic typing).

Common Data Types

Type	Example	              Description
int	    10	                  Integer
float	10.5	              Decimal number
str	    "Hello"	              Text string
bool	True, False           Boolean (True/False)

int: Used to store whole numbers (positive, negative, or zero).
float: Used for numbers with decimal points.
str: A sequence of characters enclosed in quotes (single or double).
bool: Represents logical values — True or False.

Let's see some examples,

age = 25             # int
price = 19.99        # float
name = "Praveen"       # str
is_member = True     # bool

Type Checking

You can check the type of any variable using the type() function:

print(type(age))       # <class 'int'>
print(type(price))     # <class 'float'>
print(type(name))      # <class 'str'>
print(type(is_member)) # <class 'bool'>

Let's see an example for dynamic typing.

x = 10       # int
x = "Ten"    # str — Python allows this

Type Conversion

Used to convert from one data type to another.

int("10")          # Converts string to integer
float("3.14")      # Converts string to float
str(100)           # Converts integer to string

Let's see some examples.

print(int(14/3)) # It prints 4 and it just skips the decimal part
print(round(14/3)) # It prints 5 by rounding off
print(round(14/3,2)) # It prints 4.67 by rounding off to 2 decimals
print(int('100', 2))  # It prints 4 by converting binary '100' to decimal

print(10 // 3)  # It prints 3, which is integer division (floor division)
print(10 % 3)   # It prints 1, which is the remainder (modulus)
print(2 ** 3)   # It prints 8, which is 2 raised to the power 3
print(float(5)) # It prints 5.0 by converting integer to float

print(int("7"))      # It prints 7 by converting string to int
print(str(123))      # It prints "123" by converting int to string
print(type(3.14))    # It prints <class 'float'>
print(isinstance(5, int))  # It prints True because 5 is an integer

print("hello".capitalize())  # It prints "Hello" with first letter capitalized
print("python".upper())      # It prints "PYTHON" in uppercase
print("test"[1:3])           # It prints "es" (substring from index 1 to 2)
print("data" * 2)            # It prints "datadata" by repeating the string

print(True and False)  # It prints False because both are not True
print(True or False)   # It prints True because at least one is True
print(not True)        # It prints False because it's the opposite of True
print(5 > 3)           # It prints True since 5 is greater than 3

Decimal

When working with money or financial values in Python, it's best to use the Decimal type from the decimal module instead of float, to avoid rounding errors caused by floating-point precision issues.

Why Use Decimal for Money?

Floating-point numbers can lead to inaccurate results in financial calculations:

print(0.1 + 0.2)  # It prints 0.30000000000000004 – not good for money!

With Decimal, it's precise and accurate:

from decimal import Decimal
print(Decimal('0.1') + Decimal('0.2'))  # It prints 0.3 – perfect!

Let's see more examples.

from decimal import Decimal, ROUND_HALF_UP

# Define money amounts precisely
price = Decimal('19.99')
tax = Decimal('1.50')
total = price + tax
print(total)  # It prints 21.49 – accurate sum of money

# Rounding to 2 decimal places (like dollars and cents)
discounted = total.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)
print(discounted)  # It prints 21.49

# Applying a discount
discount = Decimal('5.00')
final_price = total - discount
print(final_price)  # It prints 16.49

# Multiplying (e.g., 3 items)
quantity = 3
subtotal = price * quantity
print(subtotal)  # It prints 59.97

Let's see getcontext() from Python's decimal module.

What is getcontext()?

The getcontext() function is part of the decimal module in Python. It retrieves the current context used by all Decimal operations.

This context includes:

Precision (how many digits to keep)
Rounding mode
Flags and traps for arithmetic conditions (e.g., division by zero)

It's like a global setting that controls how all Decimal math behaves.

Let's see an example.

from decimal import Decimal, getcontext, ROUND_HALF_UP

# Set global context for financial calculations
ctx = getcontext()
ctx.prec = 10  # total digits of precision
ctx.rounding = ROUND_HALF_UP  # standard rounding (0.5 rounds up)

# Prices of items in the cart
item_1 = Decimal('19.99')
item_2 = Decimal('5.75')
item_3 = Decimal('3.40')

# Calculate subtotal
subtotal = item_1 + item_2 + item_3
print("Subtotal:", subtotal)  # Exact subtotal

# Apply tax (e.g., 8.5%)
tax_rate = Decimal('0.085')
tax_amount = (subtotal * tax_rate).quantize(Decimal('0.01'))
print("Tax:", tax_amount)

# Apply discount (e.g., $5.00)
discount = Decimal('5.00')
final_total = (subtotal + tax_amount - discount).quantize(Decimal('0.01'))
print("Final Total:", final_total)

String

A string in Python is a sequence of characters enclosed in either single quotes ' or double quotes ".

name = "Praveen"
greeting = 'Hello'

Strings are used to represent:

Words and sentences
User input (names, emails, etc.)
File paths, URLs, commands
Anything text-based

Strings are immutable, which means once created, they cannot be changed — but we can create modified versions using string functions.

Basic String Characteristics

s = "Hello, World!"

print(type(s))         # <class 'str'>
print(len(s))          # 13 – total number of characters
print(s[0])            # 'H' – indexing (0-based)
print(s[-1])           # '!' – negative index (from end)
print(s[0:5])          # 'Hello' – slicing

Common String Functions

str.lower() / str.upper()

email = "UsEr@Example.COM"
print(email.lower())  # 'user@example.com' – normalize for comparison

str.strip() – Removes whitespace

name = "  Praveen  "
print(name.strip())  # 'Praveen' – clean input fields

str.replace(old, new) – Replace parts of string

text = "Price: $100"
print(text.replace("$", ""))  # 'Price: 100' – useful for currency cleaning

str.find() – Find position (returns -1 if not found)

email = "user@example.com"
if email.find("@") != -1:
    print("Looks like a valid email")

str.split() – Split a string into a list

data = "Praveen,Oruganti,39"
parts = data.split(",")
print(parts)  # ['Praveen', 'Oruganti', '39']

str.join() – Join list into a string

words = ["apple", "banana", "cherry"]
sentence = ", ".join(words)
print(sentence)  # 'apple, banana, cherry'

str.startswith() / str.endswith()

filename = "report.pdf"
print(filename.endswith(".pdf"))  # True – file type validation

str.isdigit() / str.isalpha() / str.isalnum()

age = "39"
print(age.isdigit())  # True – check if all characters are digits

str.capitalize() / str.title()

name = "praveen oruganti"
print(name.title())  # 'Praveen Oruganti' – used for display

str.zfill(width) – Pad numbers with zeros

invoice_id = "45"
print(invoice_id.zfill(6))  # '000045' – standardized invoice format