Standard plugin · import "csv"

CSV

Read delimited text into typed tables, control how values are interpreted, and write table results back to disk.

Read

`csv::read`

csv::read(path: String, nulls: String = "", delimiter: String = ",", has_header: Bool = true, schema: String = "") -> DataFrame

With default arguments, the first row supplies column names and Ibex infers integer, floating-point, and string/categorical columns. The optional arguments let a script describe common variations without preprocessing the file.

Argument	Default	Purpose
`path`	required	Local path to the CSV file.
`nulls`	`""`	Comma-separated tokens to interpret as null. Use `<empty>` to treat empty fields as null too.
`delimiter`	`","`	Single field delimiter, for example `";"` for semicolon-separated files. Quoted fields are parsed with CSV quoting rules.
`has_header`	`true`	When false, generate column names `col1`, `col2`, and so on.
`schema`	`""`	Optional comma-separated type hints, in file column order. Use this when the schema is known and inference is unnecessary.

Examples

Common read configurations

Null tokens

Preserve empty cells by default; explicitly opt into empty-as-null if the source uses blank fields for missing data.

let data = csv::read("train.csv", "<empty>,NA");

Headerless, known schema

Skip type inference when the input layout is fixed. Headerless columns are named from col1.

let data = csv::read("measurements.txt", "", ";", false, "cat,f64");

import "csv";

let trades = csv::read("data/trades.csv");
trades[filter qty > 0, select { symbol, qty, price }];

Write

`csv::write`

csv::write(df: DataFrame, path: String) -> Int writes a header followed by the rows of df. It returns the number of rows written.

let summary = trades[select { total = sum(qty) }, by symbol];
let rows_written = csv::write(summary, "out/summary.csv");

For a complete CSV-to-Parquet batch job and further options, see the I/O guide.