Taxonomy Distribution Report

Overview

• Total Concepts: 452
• Number of Taxonomies: 14
• Average Concepts per Taxonomy: 32.3

Distribution Summary

Category	TaxonomyID	Count	Percentage	Status
Collections	COL	68	15.0%	✅
Turtle Graphics & Visualization	VIZ	63	13.9%	✅
Advanced & Applied Python	ADV	61	13.5%	✅
Variables & Data Types	DAT	55	12.2%	✅
Modules & Standard Library	MOD	36	8.0%	✅
Input & Control Flow	CTL	29	6.4%	✅
Environment & Tools	ENV	22	4.9%	✅
Functions & Scope	FUN	22	4.9%	✅
Algorithms & Data Structures	ALG	22	4.9%	✅
Object-Oriented Programming	OOP	20	4.4%	✅
File I/O & Data	FIO	16	3.5%	✅
Text Processing & Regex	TXT	14	3.1%	✅
Error Handling & Debugging	ERR	14	3.1%	✅
Core Syntax & Output	SYN	10	2.2%	ℹ️ Under

Visual Distribution

Collections               ███████  68 ( 15.0%)
Turtle Graphics & Visuali ██████  63 ( 13.9%)
Advanced & Applied Python ██████  61 ( 13.5%)
Variables & Data Types    ██████  55 ( 12.2%)
Modules & Standard Librar ███  36 (  8.0%)
Input & Control Flow      ███  29 (  6.4%)
Environment & Tools       ██  22 (  4.9%)
Functions & Scope         ██  22 (  4.9%)
Algorithms & Data Structu ██  22 (  4.9%)
Object-Oriented Programmi ██  20 (  4.4%)
File I/O & Data           █  16 (  3.5%)
Text Processing & Regex   █  14 (  3.1%)
Error Handling & Debuggin █  14 (  3.1%)
Core Syntax & Output      █  10 (  2.2%)

Balance Analysis

✅ No Over-Represented Categories

All categories are under the 30% threshold. Good balance!

ℹ️ Under-Represented Categories (<3%)

• Core Syntax & Output (SYN): 10 concepts (2.2%)
• Note: Small categories are acceptable for specialized topics

Category Details

Collections (COL)

Count: 68 concepts (15.0%)

Concepts:

• 1. List Type
• 1. Creating a List
• 1. List Indexing
• 1. Negative Indexing
• 1. List Slicing
• 1. len() for Lists
• 1. List append() insert() extend()
• 1. List remove() pop() clear()
• 1. List sort() reverse() copy()
• 1. List index() count()
• 1. Membership with in Operator
• 1. List Concatenation and Repetition
• 1. Iterating over a List
• 1. Nested Lists
• 1. List Comprehensions
• ...and 53 more

Turtle Graphics & Visualization (VIZ)

Count: 63 concepts (13.9%)

Concepts:

• 1. import turtle
• 1. turtle.Turtle() Object
• 1. turtle.Screen() Object
• 1. Screen Setup and bgcolor()
• 1. Movement forward() backward()
• 1. Turning left() right()
• 1. Absolute Positioning goto()
• 1. Pen Control penup() pendown()
• 1. Pen Size and Color
• 1. Fill begin_fill() end_fill()
• 1. Drawing circle() and Polygons
• 1. Turtle Appearance shape()
• 1. Hiding and Showing Turtle
• 1. Writing Text with turtle.write()
• 1. Clearing and Resetting
• ...and 48 more

Advanced & Applied Python (ADV)

Count: 61 concepts (13.5%)

Concepts:

• 1. Machine Learning Overview
• 1. Supervised vs Unsupervised Learning
• 1. keras Library Overview
• 1. Sequential Model
• 1. Dense Fully Connected Layers
• 1. Activation Functions relu softmax
• 1. Conv2D Convolutional Layers
• 1. MaxPooling2D Pooling Layers
• 1. Dropout Regularization
• 1. Flatten Layer
• 1. model.compile()
• 1. model.fit() Training
• 1. model.evaluate() Testing
• 1. model.predict() Inference
• 1. Categorical Crossentropy Loss
• ...and 46 more

Variables & Data Types (DAT)

Count: 55 concepts (12.2%)

Concepts:

• 1. Variable Definition and Assignment
• 1. Variable Naming Rules
• 1. Snake_case Convention
• 1. Meaningful Variable Names
• 1. Multiple Assignment
• 1. Augmented Assignment Operators
• 1. Constants by Convention
• 1. Variable Reassignment
• 1. Swap Two Variables
• 1. Naming Conflicts to Avoid
• 1. Integer Type
• 1. Float Type
• 1. Division Returns Float
• 1. Integer Division Operator
• 1. Modulo Operator
• ...and 40 more

Modules & Standard Library (MOD)

Count: 36 concepts (8.0%)

Concepts:

• 1. import Statement
• 1. from...import Specific Names
• 1. import...as Alias
• 1. from...import Star
• 1. Creating Custom Modules
• 1. name == "main" Guard
• 1. Standard Library Overview
• 1. Module Search Path
• 1. Reloading a Module
• 1. random Module Overview
• 1. random.randint()
• 1. random.choice()
• 1. random.shuffle()
• 1. random.seed()
• 1. random.random() Float
• ...and 21 more

Input & Control Flow (CTL)

Count: 29 concepts (6.4%)

Concepts:

• 1. input() Function
• 1. Prompting the User
• 1. Converting Input to Numbers
• 1. Input Validation Basics
• 1. Reading Multiple Inputs
• 1. Strip Whitespace from Input
• 1. if Statement
• 1. if...else Block
• 1. elif Chains
• 1. Nested if Statements
• 1. Conditional Ternary Expression
• 1. match/case Statement
• 1. Truthiness in Conditions
• 1. Compound Conditions
• 1. for Loop over Sequence
• ...and 14 more

Environment & Tools (ENV)

Count: 22 concepts (4.9%)

Concepts:

• 1. Python Interpreter Overview
• 1. Python 2 vs Python 3
• 1. Browser-Based Python Environments
• 1. Repl.it Online IDE
• 1. Thonny Beginner IDE
• 1. Spyder Scientific IDE
• 1. VS Code Editor
• 1. Jupyter Notebooks
• 1. JupyterLab Environment
• 1. Conda Package Manager
• 1. pip Package Installer
• 1. Virtual Environments
• 1. Installing Python Locally
• 1. Running Scripts from Terminal
• 1. Python REPL Shell
• ...and 7 more

Functions & Scope (FUN)

Count: 22 concepts (4.9%)

Concepts:

• 1. Defining a Function with def
• 1. Calling a Function
• 1. Positional Parameters
• 1. Default Parameter Values
• 1. Keyword Arguments
• 1. return Statement
• 1. Functions Returning None
• 1. Local Scope
• 1. Global Scope
• 1. global Keyword
• 1. nonlocal Keyword
• 1. Docstrings
• 1. Pure Functions vs Side Effects
• 1. Recursion Concept
• 1. Recursion Base Case
• ...and 7 more

Algorithms & Data Structures (ALG)

Count: 22 concepts (4.9%)

Concepts:

• 1. Abstract Data Types Overview
• 1. Stack LIFO Structure
• 1. Queue FIFO Structure
• 1. Queue enqueue() dequeue()
• 1. Graph Nodes and Edges
• 1. Adjacency List Representation
• 1. Breadth-First Search BFS
• 1. BFS Color Tracking
• 1. BFS for Path Finding
• 1. Depth-First Search DFS
• 1. DFS with Recursion
• 1. DFS and BFS for Maze Solving
• 1. Sorting Algorithms Overview
• 1. Bubble Sort
• 1. Selection Sort
• ...and 7 more

Object-Oriented Programming (OOP)

Count: 20 concepts (4.4%)

Concepts:

• 1. Objects and Classes Overview
• 1. Attributes of an Object
• 1. Methods of an Object
• 1. class Keyword
• 1. init() Constructor
• 1. self Parameter
• 1. Creating Class Instances
• 1. Accessing Attributes and Methods
• 1. String Methods as OOP Examples
• 1. List Methods as OOP Examples
• 1. Inheritance Basics
• 1. str() String Representation
• 1. repr() Developer Representation
• 1. Subclasses and Method Overriding
• 1. super() Function
• ...and 5 more

File I/O & Data (FIO)

Count: 16 concepts (3.5%)

Concepts:

• 1. open() Function
• 1. File Modes r w a b
• 1. file.read()
• 1. file.readlines()
• 1. file.readline()
• 1. file.write()
• 1. file.close()
• 1. with Statement Context Manager
• 1. Iterating over File Lines
• 1. Text Processing strip() lower()
• 1. CSV File Reading
• 1. CSV File Writing
• 1. Reading JSON from File
• 1. Writing JSON to File
• 1. File Path Handling
• ...and 1 more

Text Processing & Regex (TXT)

Count: 14 concepts (3.1%)

Concepts:

• 1. re Module Import
• 1. re.search() First Match
• 1. re.findall() All Matches
• 1. re.split() Split by Pattern
• 1. re.sub() Substitute Matches
• 1. Digit Word Whitespace Patterns
• 1. Anchors Start and End
• 1. Character Classes
• 1. Quantifiers Plus Star Question
• 1. Alternation with Pipe
• 1. Escaping Special Characters
• 1. Raw Strings for Regex
• 1. Regex Groups with Parentheses
• 1. Compiled Regex Patterns

Error Handling & Debugging (ERR)

Count: 14 concepts (3.1%)

Concepts:

• 1. Syntax vs Runtime vs Logic Errors
• 1. Common Exception Types
• 1. Reading a Traceback
• 1. try...except Block
• 1. Catching Specific Exceptions
• 1. else Clause in try/except
• 1. finally Clause
• 1. raise Statement
• 1. assert Statement
• 1. Debugging with print()
• 1. Using Search Engines to Debug
• 1. Exception Hierarchy
• 1. Custom Exception Classes
• 1. Exception Chaining

Core Syntax & Output (SYN)

Count: 10 concepts (2.2%)

Concepts:

• 1. print() Function
• 1. Single-Line Comments
• 1. Multi-Line Strings
• 1. Indentation as Syntax
• 1. Case Sensitivity
• 1. Python Keywords
• 1. Blank Lines and Readability
• 1. Code Block Structure
• 1. Statement vs Expression
• 1. Whitespace Rules

Recommendations

• ✅ Excellent balance: Categories are evenly distributed (spread: 12.8%)
• ✅ MISC category minimal: Good categorization specificity

Educational Use Recommendations

• Use taxonomy categories for color-coding in graph visualizations
• Design curriculum modules based on taxonomy groupings
• Create filtered views for focused learning paths
• Use categories for assessment organization
• Enable navigation by topic area in interactive tools

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Report generated by learning-graph-reports/taxonomy_distribution.py