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first exercise!
- create exercise vec statistics calculator (shout out claude) - finish hacky solution (it works... but at what cost) - update current state
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6
exercises/vec-stats/Cargo.toml
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exercises/vec-stats/Cargo.toml
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[package]
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name = "vec-stats"
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version = "0.1.0"
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edition = "2024"
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[dependencies]
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71
exercises/vec-stats/src/main.rs
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exercises/vec-stats/src/main.rs
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fn main() {
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let test_vec = vec![1, 2, 2, 2, 2, 3, 4, 5]; // should return (3.0, 3, 3)
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println!("{:?}", calculate_stats(test_vec));
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}
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#[derive(Debug)]
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struct Stats {
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mean: f64,
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median: i32,
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mode: i32,
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}
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fn calculate_stats(numbers: Vec<i32>) -> Stats {
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use std::collections::HashMap;
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let mut tmp: Vec<i32> = numbers;
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let len = tmp.len();
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tmp.sort();
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let mut median: i32 = 0;
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// median
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if len % 2 != 0 {
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median = tmp[len / 2];
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} else {
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median = (tmp[len / 2] + tmp[(len / 2) - 1]) / 2;
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}
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// mean
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let mut sum: i32 = 0;
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let tmp2 = tmp.clone();
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for i in tmp2 {
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sum += i;
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}
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let mean = sum as f64 / len as f64;
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//mode
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let mut map = HashMap::new();
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let tmp3 = tmp.clone();
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for num in tmp3 {
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let count = map.entry(num).or_insert(0);
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*count += 1;
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}
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let tmp4 = tmp.clone();
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let mut mode_calc = *map.get(&1).unwrap();
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let mut mode: i32 = 0;
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for (k, v) in map {
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if v > mode_calc {
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mode = k;
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}
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}
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println!("{:?}", tmp4);
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let return_value = Stats {
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mean: mean,
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median: median,
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mode: mode,
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};
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return_value
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}
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26
exercises/vec-stats/vec-stats-exercise.md
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exercises/vec-stats/vec-stats-exercise.md
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# Exercise: Vec Statistics Calculator
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**Concepts practiced:** Vec operations, HashMap for counting, basic math functions
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**Objective:** Build a simple stats calculator that takes a list of numbers and returns basic statistics
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## Requirements:
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- Create a function `calculate_stats(numbers: Vec<i32>) -> (f64, i32, i32)` that returns (mean, median, mode)
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- Use Vec sorting for median calculation
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- Use HashMap for mode calculation (most frequent number)
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- Handle edge cases (empty vec should panic with clear message)
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## Success criteria:
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- Code compiles and runs
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- Test with `vec![1, 2, 3, 3, 4, 5]` returns approximately `(3.0, 3, 3)`
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## Stretch goal:
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Return a struct instead of tuple for better readability
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## Getting Started:
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1. `cd exercises`
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2. `cargo new vec-stats`
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3. `cd vec-stats`
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4. Implement the function in `src/main.rs` or `src/lib.rs`
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5. Test with the example input
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Expected time: 30-45 minutes
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