Sort according to another array
Detailed guide and Python implementation for the 'Sort according to another array' problem.
1. Concept Overview
The 'Sort according to another array' problem is a key challenge in the Arrays section.
This implementation focuses on easy-level logic in Python.
We prioritize technical accuracy and code readability in our provided solutions.
2. Real-World Applications
3. Visual Intuition
Visualizing the logic flow for Sort according to another array.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Sort according to another array carefully.
2. Formulate brute force
Draft a simple iterative solution.
3. Identify inefficiency
Look for redundant calculations.
4. Optimize search path
Use hashing or sorting to speed up the process.
5. Final Implementation
Clean up the code for production standards.
Problem Statement
Write a function sort_by_order(arr1, arr2) that sorts the elements of arr1 according to the order defined by arr2. Elements in arr1 that appear in arr2 should come first in the order they appear in arr2. Elements not in arr2 should appear at the end in sorted (ascending) order.
- •1 <= len(arr1) <= 10^5
- •0 <= len(arr2) <= 100
- •Elements of arr2 are distinct
Examples
arr1 = [2, 1, 2, 5, 7, 1, 9, 3, 6, 8, 8], arr2 = [2, 1, 8, 3]
[2, 2, 1, 1, 8, 8, 3, 5, 6, 7, 9]
First all 2s, then 1s, then 8s, then 3s (order from arr2). Remaining [5,6,7,9] sorted ascending.
arr1 = [4, 5, 6], arr2 = [6, 4]
[6, 4, 5]
6 first, then 4 (per arr2 order). 5 is not in arr2, goes at end.
arr1 = [1, 2, 3], arr2 = []
[1, 2, 3]
No order specified, so sort ascending.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
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Interview Insights & Variations
Complexity Analysis Breakdown
Why Time: Directly evaluates all possibilities.
Why Space: Uses standard local memory.
Why Time: Optimized paths reduce total operations.
Why Space: May trade memory for speed.
Optimized Solution Python Code
Optimized Solution Python Code
from collections import Counter
def sort_by_order(arr1, arr2):
# Optimized: Use hash map for frequency counting
counts = Counter(arr1)
res = []
# Process elements in order of arr2
for x in arr2:
if x in counts:
res.extend([x] * counts[x])
del counts[x]
# Process remaining elements sorted
remaining = sorted(counts.elements())
return res + remainingBrute Force Code (Spoiler Guarded)
Brute Force Code (Spoiler Guarded)
def sort_by_order(arr1, arr2):
# Brute force: Build result by searching arr2 elements in arr1
res = []
visited = [False] * len(arr1)
for x in arr2:
for i in range(len(arr1)):
if arr1[i] == x:
res.append(arr1[i])
visited[i] = True
# Add remaining elements in sorted order
remaining = sorted([arr1[i] for i in range(len(arr1)) if not visited[i]])
return res + remainingAlgorithm Pattern Checklist
When dealing with Arrays data patterns.
Core Prerequisites
Revision Key Notes
Common Mistakes & Pitfalls
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