data_02_select_columns/
data_02_select_columns.rs

1//! # data_02 — Selecting columns by name
2//!
3//! Run: `cargo run -p matten-data --example data_02_select_columns`
4//!
5//! ## What this shows
6//! Choosing a subset of columns by name, in the order you ask for them, and what
7//! happens when you ask for a column that does not exist.
8//!
9//! ## Teaching points
10//! - selection is **by name**, and the output column order matches your request
11//!   (not the original CSV order);
12//! - selecting an unknown column is a clean, structured error, never a panic;
13//! - selection does not convert anything — it returns another `Table`.
14
15use matten_data::{MattenDataError, Table};
16
17fn main() -> Result<(), MattenDataError> {
18    let csv = "\
19region,sales,cost,quantity
20north,100,40,5
21south,150,45,7";
22
23    let table = Table::from_csv_str(csv)?;
24
25    // Ask for a subset in a deliberately different order than the CSV.
26    let reordered = table.select_columns(["quantity", "sales"])?;
27    println!("selected names: {:?}", reordered.column_names());
28
29    // The output order is exactly what was requested.
30    assert_eq!(
31        reordered.column_names(),
32        &["quantity".to_string(), "sales".to_string()]
33    );
34    assert_eq!(reordered.column_count(), 2);
35    assert_eq!(reordered.row_count(), 2);
36
37    // Asking for a column that does not exist is a structured error.
38    match table.select_columns(["sales", "profit"]) {
39        Err(MattenDataError::MissingColumn { name }) => {
40            println!("missing column reported: {name}");
41            assert_eq!(name, "profit");
42        }
43        other => panic!("expected MissingColumn, got {other:?}"),
44    }
45
46    println!("data_02_select_columns: OK");
47    Ok(())
48}
data_02_select_columns/data_02_select_columns.rs

data_02_select_columns/
data_02_select_columns.rs
