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🍎 Python Basics Topic 39 / 100

⏳ 7 min read

map() and filter()

Two powerful built-ins — map() applies a function to every item, filter() keeps only items that pass a test.

"map() is a conveyor belt — every item goes through a machine and comes out transformed. filter() is a sieve — only items that fit the holes pass through."

— ShurAI

The Big Picture

⚙️

map(func, list)

Applies func to every item.
Returns a new collection of the same length with each item transformed.

🧹

filter(func, list)

Keeps items where func returns True.
Returns a smaller collection — items that failed the test are gone.

map() — Transform Every Item

Pass a function and a list. Python applies the function to each item and gives back the results. Wrap in list() to see the output:

python

nums = [1, 2, 3, 4, 5]

# Square every number
squared = list(map(lambda x: x**2, nums))
print(squared)     # [1, 4, 9, 16, 25]

# Convert strings to integers
raw    = ["10", "20", "30"]
ints   = list(map(int, raw))
print(ints)        # [10, 20, 30]

# Uppercase every name
names  = ["riya", "arjun", "sneha"]
upper  = list(map(str.upper, names))
print(upper)       # ['RIYA', 'ARJUN', 'SNEHA']

map(lambda x: x**2, [1, 2, 3, 4, 5])

1

↓

1

2

↓

4

3

↓

9

4

↓

16

5

↓

25

Every item goes in → every item comes out transformed. Same length, different values.

filter() — Keep Only Matching Items

Pass a function that returns True or False. Python keeps only the items where it returned True:

python

nums = [1, 2, 3, 4, 5, 6, 7, 8]

# Keep only even numbers
evens = list(filter(lambda x: x % 2 == 0, nums))
print(evens)      # [2, 4, 6, 8]

# Keep only passing scores (>= 70)
scores  = [45, 82, 61, 90, 55, 77]
passing = list(filter(lambda s: s >= 70, scores))
print(passing)    # [82, 90, 77]

# Keep only non-empty strings
data   = ["Riya", "", "Arjun", "", "Sneha"]
clean  = list(filter(None, data))   # None keeps all truthy items
print(clean)     # ['Riya', 'Arjun', 'Sneha']

filter(lambda x: x % 2 == 0, [1,2,3,4,5,6,7,8])

1 ✗

2 ✓

3 ✗

4 ✓

5 ✗

6 ✓

7 ✗

8 ✓

Greyed items were removed. Green items passed the test and were kept.

Chaining map() and filter()

You can chain them — filter first, then map the result:

python

scores = [45, 82, 61, 90, 55, 77]

# Step 1: keep only passing scores
# Step 2: add 5 bonus points to each
boosted = list(
    map(lambda s: s + 5,
        filter(lambda s: s >= 70, scores))
)
print(boosted)   # [87, 95, 82]

map() vs filter() vs List Comprehension

Tool	Use for	Example
map()	Transform every item	map(int, ["1","2"])
filter()	Keep matching items only	filter(lambda x: x>0, nums)
[ ... ]	Transform + filter together, most readable	[x*2 for x in nums if x>0]

Real Example — Process a Shopping List

python

items = [
    ("Rice",   280, True),    # (name, price, in_stock)
    ("Dal",    120, False),
    ("Milk",   60,  True),
    ("Eggs",   96,  True),
    ("Oil",    210, False),
]

# Keep only in-stock items
available = list(filter(lambda x: x[2], items))

# Apply 5% discount to prices
discounted = list(map(
    lambda x: (x[0], round(x[1] * 0.95), x[2]),
    available
))

print("In-stock with 5% discount:")
for name, price, _ in discounted:
    print(f"  {name:8} Rs.{price}")

output

In-stock with 5% discount:
  Rice     Rs.266
  Milk     Rs.57
  Eggs     Rs.91

"map() and filter() are elegant when paired with lambda. For anything more complex, a list comprehension is usually clearer."

— ShurAI

🧠 Quiz — Q1

What does list(map(lambda x: x*2, [1,2,3])) return?

🧠 Quiz — Q2

What does filter() do to items where the function returns False?

🧠 Quiz — Q3

Why do you wrap map() and filter() in list()?

🧠 Quiz — Q4

Which is the best tool when you need to BOTH filter AND transform items in one readable line?