Crispy13

use std::fmt::Write;

use polars::prelude::*;

fn make_sorted_array_series(input: Vec<String>, datatype: &DataType) -> Vec<String> {
    input
        .into_iter()
        .map(|s| {
            let splited = s.split(",");

Crispy13

use polars::prelude::*;

fn main() {
    let s = Series::new("a", 0..100.collect::<Vec<i64>>);
    
    println!("{:?}", s.slice(20, 10)); // 20..30

}

Crispy13

use polars::prelude::*; // cargo add polars

pub fn load_tsv(file_path:&PathBuf) -> DataFrame {
    let mut df = CsvReader::from_path(file_path)
                .unwrap()
                .with_delimiter(b'\t')
                .infer_schema(None) // if None polars look through all data, so when loading big data it probably takes long time. You can limit the records polars will look into.
                .has_header(false) // if it has then 'true'
                .finish()
                .unwrap();