README.md

Maps and Frequency Counting (Python)

This module introduces dictionary-based counting patterns for grouped data.

Learning Metadata

• Difficulty: Intermediate.
• Estimated Time: 30-45 minutes.
• Prerequisites: 01-foundations/arrays-and-vectors, 01-foundations/strings.
• Cross-Language Lens: Compare hash map ergonomics, missing-key behavior, and default-value patterns across the four languages.

Quick Run

python example/main.py

Topics Covered

• Counting occurrences with dictionary lookups.
• Building frequency tables from text and numeric input.
• Producing deterministic output by sorting keys before printing.
• Using frequency data to answer higher-level questions.

Common Pitfalls

• Assuming missing keys already exist.
• Printing unsorted dictionary keys when deterministic output is expected.
• Forgetting to filter separators before counting symbols.

Exercise Focus

• exercises/01.py: count digit frequencies.
• exercises/02.py: first non-repeating character.

Exercise Specs

1. exercises/01.py

• Input: integer count n, then n integers (0-9).
• Output: frequency per digit.
• Edge cases: missing digits should show count 0; all values same digit.

2. exercises/02.py

• Input: one lowercase string.
• Output: first non-repeating character or message if none.
• Edge cases: all repeated characters; one-character string.

Checkpoint

• I can use dictionaries for counting tasks.
• I can build frequency tables from sequences.
• I can use frequency data to answer higher-level questions.
• I completed exercises/01.py.
• I completed exercises/02.py.