Why Coin Change Minimum Coins in DSA Python?

The Big Idea

What if you could instantly know the fewest coins needed for any payment without guessing?

The Scenario

Imagine you have a handful of coins of different values, and you need to pay a certain amount using the fewest coins possible. You try to pick coins one by one, guessing which ones to use, but it takes forever and you often end up with too many coins.

The Problem

Manually trying every combination of coins is slow and confusing. You might miss better combinations or waste time checking the same sets again and again. This makes paying the exact amount with the least coins very hard and error-prone.

The Solution

The Coin Change Minimum Coins method uses a smart way to remember the best solutions for smaller amounts and builds up to the target amount. This saves time and finds the fewest coins needed quickly and correctly.

Before vs After

✗ Before

def min_coins(coins, amount):
    # Try all combinations manually
    # Very slow and complicated
    pass

✓ After

def min_coins(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0
    for i in range(1, amount + 1):
        for coin in coins:
            if coin <= i:
                dp[i] = min(dp[i], dp[i - coin] + 1)
    return dp[amount] if dp[amount] != float('inf') else -1

What It Enables

This method makes it easy to find the smallest number of coins needed for any amount, even when the coin values are tricky.

Real Life Example

When you pay at a store and want to give exact change using the fewest coins, this method helps cashiers quickly figure out the best coins to hand over.

Key Takeaways

Manual guessing is slow and error-prone.

Dynamic programming remembers smaller results to build the answer fast.

It finds the minimum coins needed for any amount efficiently.

Practice

1. What does the Coin Change Minimum Coins problem ask you to find?
coins = [1, 2, 5], amount = 11

easy

A. The minimum number of coins needed to make the amount

B. The maximum number of coins that can be used

C. The total sum of all coin values

D. The number of different coin types

Solution

1. Step 1: Understand the problem goal

   The problem asks for the fewest coins needed to sum up to the given amount using the available coin denominations.

2. Step 2: Clarify what is asked

   It is not about maximum coins or total sum, but the minimum count of coins to reach the amount.

3. Final Answer:

   The minimum number of coins needed to make the amount -> Option A

4. Quick Check:

   Minimum coins = goal [OK]

Hint: Focus on minimum coins to reach amount, not max or sum [OK]

Common Mistakes:

• Confusing minimum with maximum coins
• Thinking total sum of coins is the answer
• Counting coin types instead of coin count

2. Which of the following is the correct Python syntax to initialize a list dp of size amount + 1 with all values set to amount + 1?

easy

A. dp = [amount + 1] * amount

B. dp = [amount + 1 for i in range(amount)]

C. dp = [amount] * (amount + 1)

D. dp = [amount + 1] * (amount + 1)

Solution

1. Step 1: Understand list initialization

   We want a list of length amount + 1, each element set to amount + 1.

2. Step 2: Check each option

   dp = [amount + 1] * (amount + 1) correctly creates a list of length amount + 1 with all values amount + 1. dp = [amount + 1 for i in range(amount)] creates length amount, not amount + 1. dp = [amount + 1] * amount length is amount, not amount + 1. dp = [amount] * (amount + 1) sets values to amount, not amount + 1.

3. Final Answer:

   dp = [amount + 1] * (amount + 1) -> Option D

4. Quick Check:

   Correct list size and values [OK]

Hint: Use * operator with correct length for list initialization [OK]

Common Mistakes:

• Off-by-one error in list size
• Wrong value assigned to list elements
• Using list comprehension with wrong range

3. What is the output of the following code?

coins = [1, 3, 4]
amount = 6
dp = [7] * (amount + 1)
dp[0] = 0
for i in range(1, amount + 1):
    for coin in coins:
        if coin <= i:
            dp[i] = min(dp[i], dp[i - coin] + 1)
print(dp[amount])

medium

A. 6

B. 2

C. 1

D. 3

Solution

1. Step 1: Trace dp array updates for amount=6

   Initialize dp = [0,7,7,7,7,7,7]. For i=1: dp[1]=min(7, dp[0]+1)=1. For i=2: dp[2]=min(7, dp[1]+1)=2. For i=3: dp[3]=min(7, dp[0]+1)=1. For i=4: dp[4]=min(7, dp[0]+1)=1. For i=5: dp[5]=min(7, dp[4]+1)=2. For i=6: dp[6]=min(7, dp[5]+1=3, dp[3]+1=2, dp[2]+1=3) so dp[6]=2.

2. Step 2: Final dp[6] value

   The minimum coins to make 6 is 2 (e.g., 3+3 or 4+1+1 but 2 coins is minimal).

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Minimum coins for 6 = 2 [OK]

Hint: Trace dp array updates step-by-step for each amount [OK]

Common Mistakes:

• Not updating dp[i] correctly inside nested loops
• Confusing coin values with indices
• Forgetting to initialize dp[0] = 0

4. Find the error in the following code snippet for Coin Change Minimum Coins:

coins = [1, 2, 5]
amount = 11
dp = [amount + 1] * amount
dp[0] = 0
for i in range(1, amount + 1):
    for coin in coins:
        if coin <= i:
            dp[i] = min(dp[i], dp[i - coin] + 1)
print(dp[amount])

medium

A. The inner loop should start from coin = 0

B. dp[0] should be set to amount + 1

C. dp list size is incorrect, should be amount + 1

D. The print statement should print dp[amount - 1]

Solution

1. Step 1: Check dp list initialization size

   dp is initialized with size amount, but indices go up to amount (11), so dp[11] access causes error.

2. Step 2: Correct dp size and consequences

   dp should be size amount + 1 to include index amount. dp[0] = 0 is correct. Other parts are fine.

3. Final Answer:

   dp list size is incorrect, should be amount + 1 -> Option C

4. Quick Check:

   dp size = amount + 1 [OK]

Hint: dp size must cover all indices up to amount [OK]

Common Mistakes:

• Off-by-one error in dp list size
• Incorrect initialization of dp[0]
• Wrong index in print statement

5. Given coins = [2, 5] and amount = 7, which of the following code snippets correctly returns the minimum number of coins needed or -1 if not possible?

hard

A. def min_coins(coins, amount):
dp = [amount + 1] * (amount + 1)
dp[0] = 0
for i in range(1, amount + 1):
for coin in coins:
if coin <= i:
dp[i] = min(dp[i], dp[i - coin] + 1)
return dp[amount] if dp[amount] != amount + 1 else -1

B. def min_coins(coins, amount):
dp = [0] * (amount + 1)
for i in range(1, amount + 1):
dp[i] = min(dp[i - coin] + 1 for coin in coins if coin <= i)
return dp[amount]

C. def min_coins(coins, amount):
dp = [float('inf')] * amount
dp[0] = 0
for i in range(1, amount):
for coin in coins:
if coin <= i:
dp[i] = min(dp[i], dp[i - coin] + 1)
return dp[amount - 1]

D. def min_coins(coins, amount):
dp = [amount] * (amount + 1)
dp[0] = 1
for i in range(1, amount + 1):
for coin in coins:
if coin < i:
dp[i] = min(dp[i], dp[i - coin] + 1)
return dp[amount]

Solution

1. Step 1: Analyze each code snippet

   def min_coins(coins, amount): dp = [amount + 1] * (amount + 1) dp[0] = 0 for i in range(1, amount + 1): for coin in coins: if coin <= i: dp[i] = min(dp[i], dp[i - coin] + 1) return dp[amount] if dp[amount] != amount + 1 else -1 correctly initializes dp with amount + 1 size and value, sets dp[0]=0, updates dp[i] properly, and returns -1 if no solution. def min_coins(coins, amount): dp = [0] * (amount + 1) for i in range(1, amount + 1): dp[i] = min(dp[i - coin] + 1 for coin in coins if coin <= i) return dp[amount] lacks initialization for dp[0] and may cause error if no valid coins. def min_coins(coins, amount): dp = [float('inf')] * amount dp[0] = 0 for i in range(1, amount): for coin in coins: if coin <= i: dp[i] = min(dp[i], dp[i - coin] + 1) return dp[amount - 1] uses wrong dp size and indices, and returns dp[amount - 1] incorrectly. def min_coins(coins, amount): dp = [amount] * (amount + 1) dp[0] = 1 for i in range(1, amount + 1): for coin in coins: if coin < i: dp[i] = min(dp[i], dp[i - coin] + 1) return dp[amount] sets dp[0]=1 incorrectly and uses wrong coin comparison (coin < i instead of coin <= i).

2. Step 2: Confirm correctness of def min_coins(coins, amount): dp = [amount + 1] * (amount + 1) dp[0] = 0 for i in range(1, amount + 1): for coin in coins: if coin <= i: dp[i] = min(dp[i], dp[i - coin] + 1) return dp[amount] if dp[amount] != amount + 1 else -1

   def min_coins(coins, amount): dp = [amount + 1] * (amount + 1) dp[0] = 0 for i in range(1, amount + 1): for coin in coins: if coin <= i: dp[i] = min(dp[i], dp[i - coin] + 1) return dp[amount] if dp[amount] != amount + 1 else -1 matches the standard dynamic programming solution for minimum coins with proper edge case handling.

3. Final Answer:

   Option A code snippet -> Option A

4. Quick Check:

   Standard DP solution with correct initialization and return [OK]

Hint: Check dp size, dp[0], coin comparison, and return condition [OK]

Common Mistakes:

• Wrong dp list size or initialization
• Incorrect dp[0] value
• Using coin < i instead of coin <= i
• Not handling no solution case (-1)