Code With Python
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In Python, enhanced for loops with enumerate() provide both the index and value of items in an iterable, making it ideal for tasks needing positional awareness without manual counters. This is more Pythonic and efficient than using range(len()) for list traversals.

fruits = ['apple', 'banana', 'cherry']
for index, fruit in enumerate(fruits):
print(f"{index}: {fruit}")

# Output:
# 0: apple
# 1: banana
# 2: cherry

# With start offset:
for index, fruit in enumerate(fruits, start=1):
print(f"{index}: {fruit}")
# 1: apple
# 2: banana
# 3: cherry


#python #forloops #enumerate #bestpractices

✉️ @DataScience4
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In Python, for loops are versatile for iterating over iterables like lists, strings, or ranges, but advanced types include basic iteration, index-aware with enumerate(), parallel with zip(), nested for multi-level data, and comprehension-based—crucial for efficient data processing in interviews without overcomplicating.

# Basic for loop over iterable (list)
fruits = ["apple", "banana", "cherry"]
for fruit in fruits: # Iterates each element directly
print(fruit) # Output: apple \n banana \n cherry

# For loop with range() for numeric sequences
for i in range(3): # Generates 0, 1, 2 (start=0, stop=3, step=1)
print(i) # Output: 0 \n 1 \n 2

for i in range(1, 6, 2): # Start=1, stop=6, step=2
print(i) # Output: 1 \n 3 \n 5

# Index-aware with enumerate() (gets both index and value)
for index, fruit in enumerate(fruits, start=1): # start=1 for 1-based indexing
print(f"{index}: {fruit}") # Output: 1: apple \n 2: banana \n 3: cherry

# Parallel iteration with zip() (pairs multiple iterables)
names = ["Alice", "Bob", "Charlie"]
ages = [25, 30, 35]
for name, age in zip(names, ages): # Stops at shortest iterable
print(f"{name} is {age} years old") # Output: Alice is 25 years old \n Bob is 30 years old \n Charlie is 35 years old

# Nested for loops (outer for rows, inner for columns; e.g., matrix)
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
for row in matrix: # Outer: each sublist
for num in row: # Inner: each element in row
print(num, end=' ') # Output: 1 2 3 4 5 6 7 8 9 (space-separated)

# For loop in list comprehension (concise iteration with optional condition)
squares = [x**2 for x in range(5)] # Basic comprehension
print(squares) # Output: [0, 1, 4, 9, 16]

evens_squared = [x**2 for x in range(10) if x % 2 == 0] # With condition (if)
print(evens_squared) # Output: [0, 4, 16, 36, 64]

# Nested comprehension (flattens 2D list)
flattened = [num for row in matrix for num in row] # Equivalent to nested for
print(flattened) # Output: [1, 2, 3, 4, 5, 6, 7, 8, 9]


#python #forloops #range #enumerate #zip #nestedloops #listcomprehension #interviewtips #iteration

👉 @DataScience4
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