Exercism Solutions

This repository contains my solutions to the tracks on Exercism. I use these challenges to sharpen my proficiency in languages like Python, C, and R.

🚀 Progress

Language	Progress	Key Concepts Covered
C	1/84	Functions
Python	2/143	Basics
R	17/85	Conditionals, Arithmetic, Vectors, Lists, Binary, S3, ISODate
x86-64 Assembly	1/114	Basic Syntax

🛠 Project Structure

Each folder is organized by language and then by exercise name: /[language]/[exercise-name]/

📝 Learning Notes

I often document "Aha!" moments from these challenges in my personal PKM system. Significant breakthroughs regarding algorithms or language-specific syntax are mirrored here in the exercise directories.

General Concepts

Cartesian Coordinates

Distance between two points ($x_1, y_1$) and ($x_2, y_2$) is calculated using the formula:

$$ d = \sqrt{(x_2 - x_1)^2 + (y_2 - y_1)^2} $$

Hamming Distance

The Hamming distance between two strings ($s_1$ and $s_2$) of equal length ($n$) is the number of positions at which the corresponding symbols are different. It is calculated by comparing each character in the strings and counting the differences.

$$ \text{Hamming Distance} = \sum_{i=1}^{n} (s_1[i] \neq s_2[i]) $$

R

Mapping Functions

In R, the Map() function applies a specified function to corresponding elements of given vectors or lists. It returns a list of the results. For example:

# Define a function to add two numbers
add <- function(x, y) {
  return(x + y)
}
# Use Map to apply the add function to two vectors
result <- Map(add, c(1, 2, 3), c(4, 5, 6))
print(result)
# Output: [[1]] 5 [[2]] 7 [[3]] 9

# Alternatively, we can also map operators directly
result <- Map(`!=`, c(1, 2, 3), c(1, 0, 3))
print(result)
# Output: [[1]] FALSE [[2]] TRUE [[3]] FALSE
# Summing up the TRUE values to get the count of equal elements
hamming_distance <- sum(unlist(result))
print(hamming_distance)  # Output: 1

# Using anonymous functions with Map
result <- Map(function(x, y) x * y, c(1, 2, 3), c(4, 5, 6))
print(result)
# Output: [[1]] 4 [[2]] 10 [[3]] 18

String Splitting

In R, the strsplit() function is used to split strings into substrings based on a specified delimiter. It returns a list of character vectors. For example:

# Split a string by characters
result <- strsplit("Hello", "")
print(result)
# Output: [[1]] "H" "e" "l" "l" "o"

Vectors

Vectors in R are sequences of data elements of the same basic type. They can be created using the c() function:

my_vector <- c("name" = "value", "age" = "25", "city" = "New York")
print(my_vector)
# Output:
#     name   age        city
#  "value"  "25"  "New York"
names(my_vector)
# [1] "name"  "age"  "city"
my_vector["age"]
# [1] "25"
my_vector[1]
# [1] "value"