rustframe

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Rustframe: A lightweight dataframe & math toolkit for Rust

Rustframe provides intuitive dataframe, matrix, and series operations small-to-mid scale data analysis and manipulation.

Rustframe keeps things simple, safe, and readable. It is handy for quick numeric experiments and small analytical tasks, but it is not meant to compete with powerhouse crates like polars or ndarray.

What it offers

• Math that reads like math - element‑wise +, −, ×, ÷ on entire frames or scalars.
• Broadcast & reduce - sum, product, any/all across rows or columns without boilerplate.
• Boolean masks made simple - chain comparisons, combine with &/|, get a tidy BoolMatrix back.
• Date‑centric row index - business‑day ranges and calendar slicing built in.
• Pure safe Rust - 100 % safe, zero unsafe.

Heads up

• Not memory‑efficient (yet) - footprint needs work.
• Feature set still small - expect missing pieces.

On the horizon

• Optional GPU help (Vulkan or similar) for heavier workloads.
• Straightforward Python bindings using pyo3.

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Quick start

use chrono::NaiveDate;
use rustframe::{
    frame::{Frame, RowIndex},
    matrix::{BoolOps, Matrix, SeriesOps},
    utils::{DateFreq, BDatesList},
};

let n_periods = 4;

// Four business days starting 2024‑01‑02
let dates: Vec<NaiveDate> =
    BDatesList::from_n_periods("2024-01-02".to_string(), DateFreq::Daily, n_periods)
        .unwrap()
        .list().unwrap();

let col_names: Vec<String> = vec!["a".to_string(), "b".to_string()];

let ma: Matrix<f64> =
    Matrix::from_cols(vec![vec![1.0, 2.0, 3.0, 4.0], vec![5.0, 6.0, 7.0, 8.0]]);
let mb: Matrix<f64> =
    Matrix::from_cols(vec![vec![4.0, 3.0, 2.0, 1.0], vec![8.0, 7.0, 6.0, 5.0]]);

let fa: Frame<f64> = Frame::new(
    ma.clone(),
    col_names.clone(),
    Some(RowIndex::Date(dates.clone())),
);
let fb: Frame<f64> = Frame::new(mb, col_names, Some(RowIndex::Date(dates)));

// Math that reads like math
let result: Frame<f64> = &fa * &fb; // element‑wise multiply
let total: f64 = result.sum_vertical().iter().sum::<f64>();
assert_eq!(total, 184.0);

// broadcast & reduce
let result: Matrix<f64> = ma.clone() + 1.0; // add scalar
let result: Matrix<f64> = result + &ma - &ma; // add matrix
let result: Matrix<f64> = result - 1.0; // subtract scalar
let result: Matrix<f64> = result * 2.0; // multiply by scalar
let result: Matrix<f64> = result / 2.0; // divide by scalar

let check: bool = result.eq_elem(ma.clone()).all();
assert!(check);

// The above math can also be written as:
let check: bool = (&(&(&(&ma + 1.0) - 1.0) * 2.0) / 2.0)
    .eq_elem(ma.clone())
    .all();
assert!(check);

// The above math can also be written as:
let check: bool = ((((ma.clone() + 1.0) - 1.0) * 2.0) / 2.0)
    .eq_elem(ma.clone())
    .all();
assert!(check);

// Matrix multiplication
let mc: Matrix<f64> = Matrix::from_cols(vec![vec![1.0, 2.0], vec![3.0, 4.0]]);
let md: Matrix<f64> = Matrix::from_cols(vec![vec![5.0, 6.0], vec![7.0, 8.0]]);
let mul_result: Matrix<f64> = mc.matrix_mul(&md);
// Expected:
// 1*5 + 3*6 = 5 + 18 = 23
// 2*5 + 4*6 = 10 + 24 = 34
// 1*7 + 3*8 = 7 + 24 = 31
// 2*7 + 4*8 = 14 + 32 = 46
assert_eq!(mul_result.data(), &[23.0, 34.0, 31.0, 46.0]);

// Dot product (alias for matrix_mul for FloatMatrix)
let dot_result: Matrix<f64> = mc.dot(&md);
assert_eq!(dot_result, mul_result);

// Transpose
let original_matrix: Matrix<f64> = Matrix::from_cols(vec![vec![1.0, 2.0, 3.0], vec![4.0, 5.0, 6.0]]);
// Original:
// 1 4
// 2 5
// 3 6
let transposed_matrix: Matrix<f64> = original_matrix.transpose();
// Transposed:
// 1 2 3
// 4 5 6
assert_eq!(transposed_matrix.rows(), 2);
assert_eq!(transposed_matrix.cols(), 3);
assert_eq!(transposed_matrix.data(), &[1.0, 4.0, 2.0, 5.0, 3.0, 6.0]);

// Map
let matrix = Matrix::from_cols(vec![vec![1.0, 2.0, 3.0], vec![4.0, 5.0, 6.0]]);
// Map function to double each value
let mapped_matrix = matrix.map(|x| x * 2.0);
// Expected data after mapping
// 2 8
// 4 10
// 6 12
assert_eq!(mapped_matrix.data(), &[2.0, 4.0, 6.0, 8.0, 10.0, 12.0]);

// Zip
let a = Matrix::from_cols(vec![vec![1.0, 2.0], vec![3.0, 4.0]]); // 2x2 matrix
let b = Matrix::from_cols(vec![vec![5.0, 6.0], vec![7.0, 8.0]]); // 2x2 matrix
                                                                   // Zip function to add corresponding elements
let zipped_matrix = a.zip(&b, |x, y| x + y);
// Expected data after zipping
// 6 10
// 8 12
assert_eq!(zipped_matrix.data(), &[6.0, 8.0, 10.0, 12.0]);

More examples

See the examples directory for some demonstrations of Rustframe's syntax and functionality.

To run the examples, use:

cargo run --example <example_name>

E.g. to run the game_of_life example:

cargo run --example game_of_life