散点图 Scatter

import itertools
from ... import options as opts
from ... import types
from ...charts.chart import RectChart
from ...globals import ChartType
class Scatter(RectChart):
    """
    <<< Scatter >>>
    The scatter diagram on the rectangular coordinate system can be used to
    show the relationship between x and y of the data. If the data item has
    multiple dimensions, it can be represented by color, and the
    visualmap component can be used.
    """
    def add_yaxis(
        self,
        series_name: str,
        y_axis: types.Sequence,
        *,
        is_selected: bool = True,
        xaxis_index: types.Optional[types.Numeric] = None,
        yaxis_index: types.Optional[types.Numeric] = None,
        color: types.Optional[str] = None,
        symbol: types.Optional[str] = None,
        symbol_size: types.Union[types.Numeric, types.Sequence] = 10,
        label_opts: types.Label = opts.LabelOpts(position="right"),
        markpoint_opts: types.MarkPoint = None,
        markline_opts: types.MarkLine = None,
        tooltip_opts: types.Tooltip = None,
        itemstyle_opts: types.ItemStyle = None,
    ):
        self._append_color(color)
        self._append_legend(series_name, is_selected)
        if len(y_axis) > 0 and isinstance(y_axis[0], types.Sequence):
            data = [
                list(itertools.chain(list([x]), y))
                for x, y in zip(self._xaxis_data, y_axis)
            ]
        else:
            data = [list(z) for z in zip(self._xaxis_data, y_axis)]
        self.options.get("series").append(
            {
                "type": ChartType.SCATTER,
                "name": series_name,
                "xAxisIndex": xaxis_index,
                "yAxisIndex": yaxis_index,
                "symbol": symbol,
                "symbolSize": symbol_size,
                "data": data,
                "label": label_opts,
                "markPoint": markpoint_opts,
                "markLine": markline_opts,
                "tooltip": tooltip_opts,
                "itemStyle": itemstyle_opts,
            }
        )
        return self

class pyecharts.charts.Scatter(RectChart)

class Scatter(
    # 初始化配置项，参考 `global_options.InitOpts`
    init_opts: opts.InitOpts = opts.InitOpts()
)

func pyecharts.charts.Scatter.add_yaxis

def add_yaxis(
    # 系列名称，用于 tooltip 的显示，legend 的图例筛选。
    series_name: str,

    # 系列数据
    y_axis: Sequence,

    # 是否选中图例
    is_selected: bool = True,

    # 使用的 x 轴的 index，在单个图表实例中存在多个 x 轴的时候有用。
    xaxis_index: Optional[Numeric] = None,

    # 使用的 y 轴的 index，在单个图表实例中存在多个 y 轴的时候有用。
    yaxis_index: Optional[Numeric] = None,

    # 系列 label 颜色
    color: Optional[str] = None,

    # 标记的图形。
    # ECharts 提供的标记类型包括 'circle', 'rect', 'roundRect', 'triangle', 
    # 'diamond', 'pin', 'arrow', 'none'
    # 可以通过 'image://url' 设置为图片，其中 URL 为图片的链接，或者 dataURI。
    symbol: Optional[str] = None,

    # 标记的大小，可以设置成诸如 10 这样单一的数字，也可以用数组分开表示宽和高，
    # 例如 [20, 10] 表示标记宽为 20，高为 10。
    symbol_size: Numeric = 10,

    # 标记的旋转角度。注意在 markLine 中当 symbol 为 'arrow' 时会忽略 symbolRotate 强制设置为切线的角度。
    symbol_rotate: types.Optional[types.Numeric] = None,

    # 标签配置项，参考 `series_options.LabelOpts`
    label_opts: Union[opts.LabelOpts, dict] = opts.LabelOpts(position="right"),

    # 标记点配置项，参考 `series_options.MarkPointOpts`
    markpoint_opts: Union[opts.MarkPointOpts, dict, None] = None,

    # 标记线配置项，参考 `series_options.MarkLineOpts`
    markline_opts: Union[opts.MarkLineOpts, dict, None] = None,

    # 提示框组件配置项，参考 `series_options.TooltipOpts`
    tooltip_opts: Union[opts.TooltipOpts, dict, None] = None,

    # 图元样式配置项，参考 `series_options.ItemStyleOpts`
    itemstyle_opts: Union[opts.ItemStyleOpts, dict, None] = None,

    # 可以定义 data 的哪个维度被编码成什么。
    encode: types.Union[types.JSFunc, dict, None] = None,
)