> For the complete documentation index, see [llms.txt](https://ezel.rustic.dev/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ezel.rustic.dev/basics/2.-concepts.md).

# 2. Concepts

<figure><img src="/files/ffMZS9HCclTeFnfXW9bv" alt=""><figcaption></figcaption></figure>

### Data Source

Ezel's APIs expect `polars::frame::DataFrame` as a data source.

If you have other data types, they should be converted to `DataFrame` first.

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

let mut x = vec![..];
let mut y = vec![..];

let df = df!(
    "x" => &x,
    "y" => &y
)
.unwrap();

let mut plot = Cartesian2::default();
plot.scatter(df, Column("x".to_string()), Column("y".to_string()));
```

More ergonomic interfaces are planned to be added.

```
let x: Vec<f64>;
let y: Vec<f64>;

ezel::quick::scatter_xy(x, y); // Cartesian2 + x + y

let mut plot = Cartesian2::default();
plot.scatter_xy(x, y); // two Vec<f64>
```

### Data Types (i64, f64, ..)

`f64` are expected in most places. If you have `f32` data, simply convert it to `f64`.

### Composition

Ezel borrows the idea of protrusion from `Makie.jl`. The main areas of items in the grid are aligned by rows and columns.

### Composition

TODO

### Protrusion

TODO

### Attribute

Attributes are the properties of plots such as marker size, color, etc.

There are 3 types of attribute value: a const, categorical column, or scalar column.

```rust
marker_size: ConstOrScalar<f64>, // const or scalar
marker_shape: ConstOrCategorical<MarkerShape>, // const or categorical
marker_color: ConstOrColumn<Color>, // const or categorical or scalar
```

* `scatter.marker.size = Const(10.0)` means all markers have the same size 10.0.
* `scatter.marker.shape =` `Column("species".to_string())`assigns to each species a marker shape from the theme's shape cycle (e.g. [🟢](https://whatemoji.org/green-circle/)->[**🟩** ](https://whatemoji.org/green-square/)->[💚](https://whatemoji.org/green-heart/)-> ..).
* `scatter.marker.color = Column("column_name".to_string())`uses a color from the current color cycle ([🟢](https://whatemoji.org/green-circle/)->[🟡](https://whatemoji.org/yellow-circle/)->[🟤](https://whatemoji.org/brown-circle/)->[🔴](https://whatemoji.org/red-circle/)->..) if the column is categorical or string. Otherwise it uses a color from the current color map (![](/files/QKjRTvUsTfmbRl0le0u1))

If you want to use a f64 column in polars' DataFrame as categorical data, the easiest way is to cast it to the string dtype.

<br>