PC-algorithms

Introduction

• 1. Introduction
  • 1.1. Control structures
  • 1.2. Home pages:
  • 1.3. Key references:
  • 1.4. Online editors:

Pseudocode

• 1. Pseudocode
  • 1.1. Python to Pseudocode Summary
• 2. Assignment
  • 2.1. Assignment
• 3. Input and Output
  • 3.1. Input
  • 3.2. Output
• 4. Sequence
  • 4.1. Input and output
• 5. Selection
  • 5.1. If, else
  • 5.2. If, elif, else
  • 5.3. And, or, not
  • 5.4. Nested if
• 6. Iteration
  • 6.1. Loops
  • 6.2. For loops
  • 6.3. While loops: forever
  • 6.4. While loops: pre-test
  • 6.5. Pseudocode: post-test REPEAT UNTIL
  • 6.6. Pseudocode: post-test DO WHILE
  • 6.7. Practice Questions
• 7. Case
  • 7.1. Match-case
  • 7.2. Alternatives
  • 7.3. Wildcard
  • 7.4. Matching tuples for coordinates
  • 7.5. Pseudocode alternatives

Flowcharts

• 1. Flowcharts intro
• 2. Selection
  • 2.1. if
  • 2.2. if - else
  • 2.3. if - elif
  • 2.4. If - elif - else
  • 2.5. If - elif - elif - else
• 3. While True loops
  • 3.1. While true
• 4. While loops
  • 4.1. Events as conditions
  • 4.2. Counters
  • 4.3. Counting up
  • 4.4. Counting down
  • 4.5. Step size

Pseudocode for maths

• 1. Pseudocode for maths
  • 1.1. Python to Pseudocode Summary
• 2. Newton’s method
  • 2.1. Usage Example - cubic
  • 2.2. Usage Example - exponential

Maths python intro

• 1. Introduction to maths python
  • 1.1. Previous curricula

Maths python level 5

• 1. Highest common factors
  • 1.1. Euclidean algorithm for HCF
  • 1.2. HCF pseudocode
  • 1.3. HCF by repeated subtraction
  • 1.4. HCF by repeatedly getting remainders from division
  • 1.5. HCF of triples and more
  • 1.6. HCF of triples and more by repeated subtraction
  • 1.7. HCF of triples and more by math.gcd
• 2. Lowest common multiple
  • 2.1. LCM
  • 2.2. LCM pseudocode
  • 2.3. LCM of multiple numbers
  • 2.4. LCM using gcd
  • 2.5. LCM of multiple numbers using gcd
• 3. Multiple or factor
  • 3.1. Pseudocode
  • 3.2. Multiple or factor code
• 4. Random walks
  • 4.1. 1D walk plot: Walking the plank
  • 4.2. Walking the plank analysis
  • 4.3. 2D walk plot
  • 4.4. 2D walks analysis
  • 4.5. Levy flights
• 5. Sets of numbers
  • 5.1. Simple rule
  • 5.2. Even numbers
  • 5.3. Sum numbers in sequence
• 6. Spreadsheet fill down
  • 6.1. Simple rule

Maths python level 6

• 1. Fraction sequence
  • 1.1. Fraction sequence
• 2. Flow charts
  • 2.1. Adding fractions
  • 2.2. Adding fractions using the fractions module
• 3. Sieve of Eratosthenes
  • 3.1. Sieve_v1: Primes below 100
  • 3.2. Sieve_v2: Primes below 100
  • 3.3. Sieve_v3: Primes below 100
• 4. Prime factors
  • 4.1. Prime factor list
  • 4.2. Prime factor lists
• 5. Primes as sums of squares
  • 5.1. Primes 1 mod 4

Maths python level 7

• 1. Sums of sequences
  • 1.1. Sum of consecutive numbers
• 2. Geometric patterns
  • 2.1. Turtle basics
  • 2.2. Tessellation (tiling)
  • 2.3. Square patterns
  • 2.4. Hexagon patterns

Maths python level 8

• 1. Simple debugging
  • 1.1. Errors and debugging
  • 1.2. Checking that a list has been sorted in ascending order
• 2. Divisibility
  • 2.1. Prime number divisibility tests
  • 2.2. Other divisibility tests

Maths python level 9

• 1. Pythagorean triples
  • 1.1. Pythagorean triples up to a given integer
• 2. Angle bisection
  • 2.1. Angle bisector
• 3. Polygon construction
  • 3.1. Equilateral triangle
  • 3.2. Hexagon construction

Maths python level 10

• 1. Pointers
  • 1.1. Pointers
  • 1.2. Two pointers: palindrome checker
  • 1.3. Two pointers: sum in list
  • 1.4. Two pointers: Length of longest substring
  • 1.5. Two pointers: longest mountain
• 2. Matrix transformations
  • 2.1. Translation
  • 2.2. Translation of multiple points
  • 2.3. Transformations
  • 2.4. Reflections
  • 2.5. Rotations
  • 2.6. Dilation

Maths python level 10A

• 1. Bisection
  • 1.1. The Bisection method
  • 1.2. Bisection with specified Iterations
  • 1.3. Cubic Example
  • 1.4. Example with sin function
  • 1.5. Bisection with specified error tolerance
  • 1.6. Cubic Example
• 2. Monty Hall
  • 2.1. Monty Hall simulation
  • 2.2. Monty Hall explanation
• 3. Derangements
  • 3.1. Derangements theory
  • 3.2. Derangement simulation

Maths python general

• 1. Selection sort
  • 1.1. Selection sort algorithm
  • 1.2. Example
  • 1.3. Usage: find the median
  • 1.4. Selection sort of a dictionary
  • 1.5. Example: Life expectancy by state
• 2. Population_sampling
  • 2.1. Population mean
  • 2.2. Sample Mean
  • 2.3. Sample Means: Increasing samples
  • 2.4. Sample Means: Increasing sample size
  • 2.5. Population Proportion
  • 2.6. Sample Proportion
  • 2.7. Sample Proportion: Increasing samples
  • 2.8. Sample Proportion: Increasing sample size

Maths python Y7

• 1. Simple stats
  • 1.1. Mean
  • 1.2. Sort list
  • 1.3. Median
  • 1.4. Mode
  • 1.5. Range

Matplotlib

• 1. Matplotlib intro
  • 1.1. Installation
  • 1.2. Importing Pyplot
  • 1.3. Figure
  • 1.4. Plot
  • 1.5. Patch
• 2. Matplotlib plot 1 line
  • 2.1. Simple Linear plot
  • 2.2. Python code
  • 2.3. Straight line graph to scale
  • 2.4. Python code
• 3. Matplotlib plot multiple lines
  • 3.1. Simple Multiple line plot
  • 3.2. Python code
  • 3.3. Straight line graph with parabola
  • 3.4. Python code
• 4. Matplotlib plot json
  • 4.1. Temperature forecast
  • 4.2. Python code
• 5. Matplotlib pie chart
  • 5.1. Simple pie chart
  • 5.2. Python code
  • 5.3. Customized pie chart
  • 5.4. Python code
• 6. Matplotlib pie chart csv
  • 6.1. Python code
• 7. Matplotlib histogram
  • 7.1. Python code
• 8. Matplotlib bar chart
  • 8.1. Simple bar chart
  • 8.2. Python code
  • 8.3. Customized bar chart
  • 8.4. Python code
• 9. Matplotlib dot plot
  • 9.1. Examples
• 10. Matplotlib box plot
  • 10.1. Random box plot
  • 10.2. Python code
  • 10.3. Comparing skewness in box plots
  • 10.4. Python code
  • 10.5. Version 1 of code
  • 10.6. Version 2 of code