Utah

Utah is a Rust crate backed by ndarray for type-conscious, tabular data manipulation with an expressive, functional interface.

Note: This crate works on stable. However, if you are working with dataframes with f64 data and String column/index labels, use nightly, because you will get the performance benefits of specialization.

API currently in development and subject to change.

For an in-depth introduction to the mechanics of this crate, as well as future goals, read this blog post: PLACEHOLDER

Install

Add the following to your Cargo.toml:

utah="0.0.1"

extern crate utah in lib.rs and you're good to go.

Examples

Create dataframes on the fly

```rust use utah::prelude::*; let df = DataFrame = dataframe!( { "a" => column!([2., 3., 2.]), "b" => column!([2., NAN, 2.]) });

let a = arr2(&[[2.0, 7.0], [3.0, 4.0]]); let df : Result> = DataFrame::new(a).index(&["1", "2"]); ```

Transform the dataframe

rust use utah::prelude::*; let df: DataFrame<f64, String> = DataFrame::read_csv("test.csv")?; let res : DataFrame<f64, String> = df.remove(&["a", "c"], UtahAxis::Column).as_df()?;

Chain operations

rust use utah::prelude::*; let df: DataFrame<f64, String> = DataFrame::read_csv("test.csv").unwrap(); let res : DataFrame<f64, String> = df.df_iter(UtahAxis::Row) .remove(&["1"]) .select(&["2"]) .append("8", new_data.view()) .sumdf() .as_df()?;

Support mixed types

rust use utah::prelude::*; let a = DataFrame<InnerType, OuterType> = dataframe!( { "name" => column!([InnerType::Str("Alice"), InnerType::Str("Bob"), InnerType::Str("Jane")]), "data" => column!([InnerType::Float(2.0), InnerType::Empty(), InnerType::Float(3.0)]) }); let b: DataFrame<InnerType, OuterType> = DataFrame::read_csv("test.csv")?; let res : DataFrame<InnerType, OuterType> = a.left_inner_join(&b).as_df()?;