Struct DataFrame 

pub struct DataFrame { /* private fields */ }

A DataFrame represents a collection of named Series (columns)

Implementations

impl DataFrame

pub fn new() -> DataFrame

Create a new empty DataFrame

pub fn from_series(columns: HashMap<String, Series>) -> Result<DataFrame, Error>

Create a DataFrame from a map of column names to Series

Examples found in repository

examples/simple.rs (line 21)

fn main() {
    println!("=== StatOxide Simple Example ===\n");
    
    // 1. Create a DataFrame
    println!("1. Creating DataFrame:");
    let mut columns = HashMap::new();
    columns.insert("x".to_string(), Series::new("x", Array1::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0])));
    columns.insert("y".to_string(), Series::new("y", Array1::from_vec(vec![2.0, 4.0, 5.0, 4.0, 5.0])));
    
    let df = DataFrame::from_series(columns).unwrap();
    
    println!("   DataFrame shape: {} rows × {} columns", df.n_rows(), df.n_cols());
    println!("   Column names: {:?}\n", df.column_names());
    
    // 2. Parse a formula
    println!("2. Parsing formula:");
    let formula = Formula::parse("y ~ x").unwrap();
    println!("   Formula parsed successfully, variables: {:?}\n", formula.variables());
    
    // 3. Compute statistics
    println!("3. Computing statistics:");
    let x_view = df.column("x").unwrap().data();
    let y_view = df.column("y").unwrap().data();
    
    // Convert views to owned arrays
    let x_data = x_view.to_owned();
    let y_data = y_view.to_owned();
    
    let x_mean = mean(&x_data).unwrap();
    let x_std = std(&x_data, 1.0).unwrap();
    let corr = correlation(&x_data, &y_data).unwrap();
    
    println!("   Mean of x: {:.4}", x_mean);
    println!("   Std of x: {:.4}", x_std);
    println!("   Correlation(x, y): {:.4}\n", corr);
    
    // 4. Demonstrate module structure
    println!("4. Module structure available:");
    println!("   - statoxide::models::*  (GLM, linear regression, mixed effects)");
    println!("   - statoxide::stats::*   (statistical functions and tests)");
    println!("   - statoxide::tsa::*     (time series analysis)");
    println!("   - statoxide::linalg::*  (linear algebra)");
    println!("   - statoxide::utils::*   (utilities)\n");
    
    println!("=== StatOxide version {} ===", statoxide::version());
}

pub fn n_rows(&self) -> usize

Get number of rows

Examples found in repository

examples/simple.rs (line 23)

fn main() {
    println!("=== StatOxide Simple Example ===\n");
    
    // 1. Create a DataFrame
    println!("1. Creating DataFrame:");
    let mut columns = HashMap::new();
    columns.insert("x".to_string(), Series::new("x", Array1::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0])));
    columns.insert("y".to_string(), Series::new("y", Array1::from_vec(vec![2.0, 4.0, 5.0, 4.0, 5.0])));
    
    let df = DataFrame::from_series(columns).unwrap();
    
    println!("   DataFrame shape: {} rows × {} columns", df.n_rows(), df.n_cols());
    println!("   Column names: {:?}\n", df.column_names());
    
    // 2. Parse a formula
    println!("2. Parsing formula:");
    let formula = Formula::parse("y ~ x").unwrap();
    println!("   Formula parsed successfully, variables: {:?}\n", formula.variables());
    
    // 3. Compute statistics
    println!("3. Computing statistics:");
    let x_view = df.column("x").unwrap().data();
    let y_view = df.column("y").unwrap().data();
    
    // Convert views to owned arrays
    let x_data = x_view.to_owned();
    let y_data = y_view.to_owned();
    
    let x_mean = mean(&x_data).unwrap();
    let x_std = std(&x_data, 1.0).unwrap();
    let corr = correlation(&x_data, &y_data).unwrap();
    
    println!("   Mean of x: {:.4}", x_mean);
    println!("   Std of x: {:.4}", x_std);
    println!("   Correlation(x, y): {:.4}\n", corr);
    
    // 4. Demonstrate module structure
    println!("4. Module structure available:");
    println!("   - statoxide::models::*  (GLM, linear regression, mixed effects)");
    println!("   - statoxide::stats::*   (statistical functions and tests)");
    println!("   - statoxide::tsa::*     (time series analysis)");
    println!("   - statoxide::linalg::*  (linear algebra)");
    println!("   - statoxide::utils::*   (utilities)\n");
    
    println!("=== StatOxide version {} ===", statoxide::version());
}

pub fn n_cols(&self) -> usize

Get number of columns

Examples found in repository

examples/simple.rs (line 23)

fn main() {
    println!("=== StatOxide Simple Example ===\n");
    
    // 1. Create a DataFrame
    println!("1. Creating DataFrame:");
    let mut columns = HashMap::new();
    columns.insert("x".to_string(), Series::new("x", Array1::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0])));
    columns.insert("y".to_string(), Series::new("y", Array1::from_vec(vec![2.0, 4.0, 5.0, 4.0, 5.0])));
    
    let df = DataFrame::from_series(columns).unwrap();
    
    println!("   DataFrame shape: {} rows × {} columns", df.n_rows(), df.n_cols());
    println!("   Column names: {:?}\n", df.column_names());
    
    // 2. Parse a formula
    println!("2. Parsing formula:");
    let formula = Formula::parse("y ~ x").unwrap();
    println!("   Formula parsed successfully, variables: {:?}\n", formula.variables());
    
    // 3. Compute statistics
    println!("3. Computing statistics:");
    let x_view = df.column("x").unwrap().data();
    let y_view = df.column("y").unwrap().data();
    
    // Convert views to owned arrays
    let x_data = x_view.to_owned();
    let y_data = y_view.to_owned();
    
    let x_mean = mean(&x_data).unwrap();
    let x_std = std(&x_data, 1.0).unwrap();
    let corr = correlation(&x_data, &y_data).unwrap();
    
    println!("   Mean of x: {:.4}", x_mean);
    println!("   Std of x: {:.4}", x_std);
    println!("   Correlation(x, y): {:.4}\n", corr);
    
    // 4. Demonstrate module structure
    println!("4. Module structure available:");
    println!("   - statoxide::models::*  (GLM, linear regression, mixed effects)");
    println!("   - statoxide::stats::*   (statistical functions and tests)");
    println!("   - statoxide::tsa::*     (time series analysis)");
    println!("   - statoxide::linalg::*  (linear algebra)");
    println!("   - statoxide::utils::*   (utilities)\n");
    
    println!("=== StatOxide version {} ===", statoxide::version());
}

pub fn column_names(&self) -> Vec<String>

Get column names

Examples found in repository

examples/simple.rs (line 24)

fn main() {
    println!("=== StatOxide Simple Example ===\n");
    
    // 1. Create a DataFrame
    println!("1. Creating DataFrame:");
    let mut columns = HashMap::new();
    columns.insert("x".to_string(), Series::new("x", Array1::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0])));
    columns.insert("y".to_string(), Series::new("y", Array1::from_vec(vec![2.0, 4.0, 5.0, 4.0, 5.0])));
    
    let df = DataFrame::from_series(columns).unwrap();
    
    println!("   DataFrame shape: {} rows × {} columns", df.n_rows(), df.n_cols());
    println!("   Column names: {:?}\n", df.column_names());
    
    // 2. Parse a formula
    println!("2. Parsing formula:");
    let formula = Formula::parse("y ~ x").unwrap();
    println!("   Formula parsed successfully, variables: {:?}\n", formula.variables());
    
    // 3. Compute statistics
    println!("3. Computing statistics:");
    let x_view = df.column("x").unwrap().data();
    let y_view = df.column("y").unwrap().data();
    
    // Convert views to owned arrays
    let x_data = x_view.to_owned();
    let y_data = y_view.to_owned();
    
    let x_mean = mean(&x_data).unwrap();
    let x_std = std(&x_data, 1.0).unwrap();
    let corr = correlation(&x_data, &y_data).unwrap();
    
    println!("   Mean of x: {:.4}", x_mean);
    println!("   Std of x: {:.4}", x_std);
    println!("   Correlation(x, y): {:.4}\n", corr);
    
    // 4. Demonstrate module structure
    println!("4. Module structure available:");
    println!("   - statoxide::models::*  (GLM, linear regression, mixed effects)");
    println!("   - statoxide::stats::*   (statistical functions and tests)");
    println!("   - statoxide::tsa::*     (time series analysis)");
    println!("   - statoxide::linalg::*  (linear algebra)");
    println!("   - statoxide::utils::*   (utilities)\n");
    
    println!("=== StatOxide version {} ===", statoxide::version());
}

pub fn column(&self, name: &str) -> Option<&Series>

Get a column by name

Examples found in repository

examples/simple.rs (line 33)

fn main() {
    println!("=== StatOxide Simple Example ===\n");
    
    // 1. Create a DataFrame
    println!("1. Creating DataFrame:");
    let mut columns = HashMap::new();
    columns.insert("x".to_string(), Series::new("x", Array1::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0])));
    columns.insert("y".to_string(), Series::new("y", Array1::from_vec(vec![2.0, 4.0, 5.0, 4.0, 5.0])));
    
    let df = DataFrame::from_series(columns).unwrap();
    
    println!("   DataFrame shape: {} rows × {} columns", df.n_rows(), df.n_cols());
    println!("   Column names: {:?}\n", df.column_names());
    
    // 2. Parse a formula
    println!("2. Parsing formula:");
    let formula = Formula::parse("y ~ x").unwrap();
    println!("   Formula parsed successfully, variables: {:?}\n", formula.variables());
    
    // 3. Compute statistics
    println!("3. Computing statistics:");
    let x_view = df.column("x").unwrap().data();
    let y_view = df.column("y").unwrap().data();
    
    // Convert views to owned arrays
    let x_data = x_view.to_owned();
    let y_data = y_view.to_owned();
    
    let x_mean = mean(&x_data).unwrap();
    let x_std = std(&x_data, 1.0).unwrap();
    let corr = correlation(&x_data, &y_data).unwrap();
    
    println!("   Mean of x: {:.4}", x_mean);
    println!("   Std of x: {:.4}", x_std);
    println!("   Correlation(x, y): {:.4}\n", corr);
    
    // 4. Demonstrate module structure
    println!("4. Module structure available:");
    println!("   - statoxide::models::*  (GLM, linear regression, mixed effects)");
    println!("   - statoxide::stats::*   (statistical functions and tests)");
    println!("   - statoxide::tsa::*     (time series analysis)");
    println!("   - statoxide::linalg::*  (linear algebra)");
    println!("   - statoxide::utils::*   (utilities)\n");
    
    println!("=== StatOxide version {} ===", statoxide::version());
}

pub fn column_mut(&mut self, name: &str) -> Option<&mut Series>

Get a mutable reference to a column

pub fn with_column(self, series: Series) -> Result<DataFrame, Error>

Add a column to the DataFrame

pub fn drop_column(self, name: &str) -> DataFrame

Remove a column

pub fn select(&self, col_names: &[&str]) -> Result<DataFrame, Error>

Select specific columns

pub fn filter(&self, mask: &[bool]) -> Result<DataFrame, Error>

Filter rows based on a boolean mask

pub fn design_matrix( &self, formula: &Formula, ) -> Result<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, Error>

Get design matrix for regression

Trait Implementations

impl Clone for DataFrame

fn clone(&self) -> DataFrame

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DataFrame

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl Default for DataFrame

fn default() -> DataFrame

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for DataFrame

fn deserialize<__D>( __deserializer: __D, ) -> Result<DataFrame, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl FromData<Vec<Vec<f64>>> for DataFrame

fn from_data(data: Vec<Vec<f64>>) -> Result<DataFrame, Error>

impl Serialize for DataFrame

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.