# Polars

In memory DataFrames in Rust

This is my mock up of DataFrames implemented in Rust, using Apache Arrow as backend.

WIP

Series

• [x] cast
• [x] take by index/ boolean mask
• [x] limit
• [x] Rust iterators!
• [x] append
• [x] aggregation: min, max, sum
• [x] arithmetic
• [x] comparison
• [ ] find
• [x] sorting

DataFrame

• [x] take by index/ boolean mask
• [x] limit
• [x] join: inner, left
• [x] column ops: drop, select, rename
• [ ] group by
• [x] concat (horizontal)
• [x] read csv
• [ ] write csv
• [ ] write json
• [ ] read json
• [x] sorting

Data types

• [x] null
• [x] boolean
• [x] u32
• [x] i32
• [x] i64
• [x] f32
• [x] f64
• [x] utf-8
• [x] date
• [x] time

Example

```rust use polars::prelude::*;

// Create first df. let s0 = Series::init("days", [0, 1, 2, 3, 4].asref()); let s1 = Series::init("temp", [22.1, 19.9, 7., 2., 3.].asref()); let temp = DataFrame::newfromcolumns(vec![s0, s1]).unwrap();

// Create second df. let s0 = Series::init("days", [1, 2].asref()); let s1 = Series::init("rain", [0.1, 0.2].asref()); let rain = DataFrame::newfromcolumns(vec![s0, s1]).unwrap();

// Left join on days column. let joined = temp.left_join(&rain, "days", "days"); println!("{}", joined.unwrap()) ```

```text days temp rain i32 f64 f64 --- --- ---

          0           22.1           null
          1           19.9            0.1
          2              7            0.2
          3              2           null
          4              3           nul

```