What are Numeric Data Types ?

Numeric Data Types are the first basic and easy to understand data type of Python . ΰ€œΰ€¬ bhi hum programming mein kisi bhi tarah ke numbers ke sath kaam karte hainβ€”chahe wo kisi product ki price ho, temperature ho, bank account ka balance ho, ya koi bada scientific calculation hoβ€”toh Python wahan par Numeric Data Type ka istemal karta hai.
Python mein numbers ko unke naye roop aur kaam ke mutabik teen alag-alag bhaagon (sub-types) mein baanta gaya hai:

1. Integer

Integer ka matlab hota hai bina point wali poore numbers (whole numbers). Yeh positive (plus wale), negative (minus wale) ya zero ho sakte hain. Python mein iski koi fix limit nahi hoti, aap jitna chahein utna bada number isme store kar sakte hain jab tak aapke computer ki memory (RAM) full na ho jaye. Below is the code to store a Integer value in a variable.

main.py 
user_age = 24
bank_debts = -1500
total_items = 0

print(user_age)
print(bank_debts)
Code Output 
24
-1500

2. Float

Float ka matlab hota hai point wale numbers (decimal numbers). Agar kisi number mein ek single point (.) bhi lag jaye, toh Python use integer nahi balki float maanta hai. Integer ki tarah float bhi positive ya negative dono ho sakte hain.

Ek aur zaroori baat: Float numbers ko likhne ke liye Python scientific notation (e ya E) ka bhi support karta hai, jiska matlab hota hai "10 ki power". Jaise 3.2e3 ka matlab hai 3.2 * 10^3 (yaani 3200.0).
1. Kisi product ki exact price store karne ke liye (jaise: 99.99) , 2. Percentage nikalne ke liye (jaise: 85.5%) , 3. GPS coordinates ya weight store karne ke liye (jaise: 65.45 kg) etc. kaam karne ke liye float data type kaa upyog kiya jaata hai.
Below is the code to store Float value in some variables.

main.py 
# Float variables ke examples
product_price = 499.50
pi_value = 3.14159
scientific_num = 2.5e3  # Iska matlab hai 2500.0

print(product_price)
print(scientific_num)
Code Output 
499.5
2500.0

3. Complex Numbers

Complex numbers ka istemal aam programming mein bohot kam hota hai, lekin high-level mathematics, physics simulations, electrical engineering aur data science mein yeh bohot zaroori hain.

Ek complex number ke do bhaag hote hain: Real part aur Imaginary part. Python mein imaginary part ko darshane ke liye hum maths ke 'i' ki jagah 'j' ΰ€―ΰ€Ύ 'J' ka istemal karte hain. Jaise: 2 + 3j (yahan 2 real number hai aur 3j imaginary).

main.py 
# Complex variables ke examples
num1 = 3 + 4j
num2 = 5j  # Agar real part nahi likhenge toh wo 0 mana jayega

print(num1)
print(num1.real)  # Sirf real part dekhne ke liye
print(num1.imag)  # Sirf imaginary part dekhne ke liye
Code Output 
(3+4j)
3.0
4.0

Useful Built-in Functions for Numbers

Python mein numbers (integers aur floats) ke sath kaam karte waqt hume aksar unhe round-off karne, unki absolute (positive) value nikalne, ya kisi list mein se sabse bada/chhota number dhoodhne ki zaroorat padti hai.

Iske liye Python mein kuch Built-in Functions (pehle se bane banaye functions) milte hain, jinke liye aapko koi alag se library ya module import nahi karna padta. Niche in sabhi zaroori functions ko detail mein samjhaya gaya hai:

1. abs() β€” Absolute Value

abs() function ka kaam hota hai kisi bhi number ki absolute value batana. Iska matlab yeh hai ki agar aap isme koi negative (minus wala) number dalenge, toh yeh use positive (plus wale) number mein badal dega. Agar number pehle se positive hai, toh wo vaisa hi rahega.

Jab aapko sirf do cheezon ke beech ka antar (difference) nikalna ho aur aap nahi chahte ki answer minus mein aaye (jaise distance ya age ka difference). aisi jagaho per abs() function kaa upyog kiya jaa sakta hai . niche abs() function kaa ek python code diya gaya hai.

main.py 
distance_1 = -45
distance_2 = 120

print(abs(distance_1))
print(abs(distance_2))
Code Output 
45
120

2. round() β€” Rounding Off

round() function kisi bhi decimal (float) number ko uske sabse paas wale poore number (integer) mein badal deta hai.

Rule 1 : Agar point ke baad ka number .5 se chhota hai (jaise .4, .3), toh yeh niche wale number par round-off karega.
Rule 2 : Agar point ke baad ka number .5 ya usse bada hai (jaise .5, .7), toh yeh upar wale number par round-off karega.
Aap isme yeh bhi bata sakte hain ki aapko point ke baad kitne digits tak ka number chahiye (iske liye second argument diya jata hai). niche round() β€” Rounding Off Function kaa ek python code diya gaya hai.

main.py 
num1 = 4.3
num2 = 4.7
num3 = 5.5

# Point ke baad kitne digit chahiye uske liye example:
pi_value = 3.14159265

print(round(num1))
print(round(num2))
print(round(num3))
print(round(pi_value, 2))  # Point ke baad sirf 2 digits rakhega
Code Output 
4
5
6
3.14

3. sum() Total Sum

sum() function ka istemal kisi list ya tuple ke andar diye gaye sabhi numbers ka kul jod (total sum) nikalne ke liye kiya jata hai. Iske andar aapko numbers ka ek group bhejna padta hai. niche sum() function kaa ek python code diya gaya hai .

main.py 
monthly_expenses = [200, 500, 150, 1200]

total_spend = sum(monthly_expenses)
print(total_spend)
Code Output 
2050

Numeric Data Type ke sath Arithmetic Operations

Kyunki yeh saare numbers hain, isliye aap inpar maths ke saare basic operations asaani se chala sakte hain. Python alag-alag numeric types ko aukas ke mutabik khud hi convert (Implicit Typecasting) kar leta hai. Udaharan ke liye, agar aap ek integer aur ek float ko jodenge, toh result hamesha float aayega.

main.py 
# Alag-alag numbers par math operations
a = 10     # int
b = 3.5    # float

addition = a + b        # Jod
subtraction = a - b     # Ghatana
multiplication = a * b  # Guna
division = a / b        # Bhag (Division ka result hamesha float aata hai)

print(addition)
print(division)
Code Output 
13.5
2.857142857142857

Advantages Of Numeric Data Types

1. Unlimited Integer Precision : Python mein integer numbers store karne ki koi fix limit nahi hoti hai.Aap memory ke anusar jitna chahein utna bada number store kar sakte hain.
2. Underline for Readability : Bade numbers ko aasaani se padhne ke liye aap beech mein underscore (_) laga sakte hain.Python ka interpreter in underscores ko calculation karte waqt apne aap ignore kar deta hai.
3. Automatic Float Division : Jab aap do integers ko normal division (/) operator se bhag karte hain toh result hamesha float aata hai.Jaise 10 / 2 ka output hamesha integer 5 ke bajay decimal 5.0 aayega.
4. Immutable Nature : Python ke saare numeric data types poori tarah se immutable hote hain.Iska matlab hai ki ek baar memory mein number banne ke baad use badla nahi ja sakta.
5. Multiple Number Systems Support : Python mein aap normal numbers ke alawa Binary, Octal, aur Hexadecimal numbers bhi likh sakte hain.Iske liye aapko number ke aage 0b, 0o, ya 0x jaise prefixes lagane padte hain.