Mateusz Kubaszek - mkubasz
Paweł Walus - Losseheil

type DataFrame -> Data Enginnering
    eg: 
    DataFrame::new(
                vec![
                    row![0.4, 0.7, "poster", true, 1],
                    row![3.0, 4.7, "table", true, 1],
                    row![3.0, 4.7, "book", true, 1],
                ],
                vec!["A", "B", "C", "D", "E"]
            );
type DataFrameGroupBy -> Hashmap
type Series -> Vectorize structure
    eg:
    Series::new(
        row![0.4, 0.7, "poster", true, 1],
        String::from("A")
    )
type Cell -> One element in Data Frame
    - Number
    - Float
    - Float64
    - Bool
    - Text
type Matrix -> Algebraic matrix

fn push(&mut self, element: Vec<Cell>);

fn series(&mut self, index: usize) -> &mut Series<Cell>;

fn to_rows(&self) -> Option<Vec<Vec<Cell>>>;

fn by(&mut self, label: &str) -> Option<&mut Series<Cell>>;

fn many(&mut self, labels: Vec<&str>) -> Vec<Series<Cell>>;

fn map(&mut self, col: &str, obj: HashMap<&str, u32>) -> DataFrame;

fn concat(&mut self, df: DataFrame) -> DataFrame;

fn drop(&mut self, label: Vec<&str>) -> Option<DataFrame>;

fn drop_idx(&mut self, position: usize) -> Option<DataFrame>;

fn contains(self, label: &str) -> bool;

fn join(&mut self, df: DataFrame);

fn group_by(&mut self, label: &str) -> Option<DataFrameGroupBy>;

fn sort(&mut self, label: &str) -> Option<DataFrame>;

fn read_csv(file_name: String) -> Result<DataFrame, Box<dyn Error>>;

fn get_dummies(&mut self, label: &str) -> DataFrame;

fn from_vec<T>(vec: Vec<Vec<T>>, labels: Vec<&str>) -> DataFrame where T: PrimInt + Signed + Product;

fn to_matrix(&self) -> Option<Matrix>;

fn sigmoid(x: f64) -> f64;

fn minmax_item<T: Into<f64> + Copy>(min_max: (f64, f64), item: T) -> (f64, f64);

fn minmax<T: Into<f64> + Copy>(series: Vec<T>) -> Option<(f64, f64)>;

fn series_minmax(series: Series<Cell>) -> (f64, f64);