@spec chart(VegaLite.t(), Table.Reader.t(), keyword()) :: VegaLite.t()

@spec chart(Table.Reader.t(), atom() | keyword(), keyword()) :: VegaLite.t()

Returns the specification for the a given data, a mark, and a list of fields to be encoded.

The mark is either an atom, such as :line, or a keyword list such as [type: :point, line: true].

It encodes only the given fields from the data by default. More fields can be added using the :extra_fields option. All the other fields must follow the specifications of the VegaLite module.

Options

• :extra_fields - adds extra fields to the data subset for later use

Examples

data = [
  %{"category" => "A", "score" => 28},
  %{"category" => "B", "score" => 55}
]

Data.chart(data, :bar, x: "category", y: "score")

Data.chart(data, :bar, x: "category", extra_fields: ["score"])
|> Vl.encode_field(:y, "score", type: :quantitative)

The above examples achieves the same results as the example below.

Vl.new()
|> Vl.data_from_values(data, only: ["category", "score"])
|> Vl.mark(:bar)
|> Vl.encode_field(:x, "category", type: :nominal)
|> Vl.encode_field(:y, "score", type: :quantitative)

This function may also be called with an existing VegaLite spec and without a mark:

Vl.new()
|> Vl.mark(:bar)
|> Data.chart(data, x: "category", extra_fields: ["score"])

In such cases it is your responsibility to encode the mark.

@spec chart(VegaLite.t(), Table.Reader.t(), atom() | keyword(), keyword()) ::
  VegaLite.t()

Same as chart/3 but receives a valid VegaLite specification as a first argument.

Examples

data = [
  %{"category" => "A", "score" => 28},
  %{"category" => "B", "score" => 55}
]

Vl.new(title: "With title")
|> Data.chart(data, :bar, x: "category", y: "score")

Vl.new(title: "With title")
|> Vl.mark(:bar)
|> Data.chart(data, x: "category", y: "score")

The above example achieves the same results as the example below.

Vl.new(title: "With title")
|> Vl.data_from_values(data, only: ["category", "score"])
|> Vl.mark(:bar)
|> Vl.encode_field(:x, "category", type: :nominal)
|> Vl.encode_field(:y, "score", type: :quantitative)

@spec columns_for(Table.Reader.t()) :: map() | nil

Returns a map with each column and its respective inferred type for the given data.