polars_st 绘制地图

 import polars as pl

import polars_st as st

import altair as alt

import json

alt.data_transformers.enable("vegafusion")

luis=st.read_file('/mnt/c/Users/xuefliang/Downloads/tl_2023_22_prisecroads/tl_2023_22_prisecroads.shp')

features = [

    {"type": "Feature", "geometry": json.loads(r.pop("geometry")), "properties": r}

    for r in luis.st.to_geojson().to_dicts()

]

chart = alt.Chart(alt.Data(values=features)).mark_geoshape(

    filled=False,

    stroke='steelblue',

    strokeWidth=1

).properties(

    width=800,

    height=600,

    title="Louisiana Primary Roads Map"

).project(

    type='mercator'

)

chart

# 使用命名空间名称 'map'

@pl.api.register_dataframe_namespace("map")

class GeoPlotter:

    def __init__(self, df: pl.DataFrame):

        self._df = df

    def plot(self, title="Map", stroke='black', stroke_width=1, simplify=None):

        """执行转换并绘制 Altair 地图"""

        working_df = self._df

       

        # 1. 可选的几何简化

        if simplify is not None:

            working_df = working_df.with_columns(

                pl.col("geometry").st.simplify(simplify)

            )

       

        # 2. 转换为 GeoJSON 字符串列

        geojson_df = working_df.st.to_geojson()

       

        # 3. 构造 Features 列表

        features = [

            {

                "type": "Feature",

                "geometry": json.loads(row.pop("geometry")),

                "properties": row

            }

            for row in geojson_df.to_dicts()

        ]

        # 4. 构建 Altair 图表

        chart = alt.Chart(alt.Data(values=features)).mark_geoshape(

            filled=False,

            stroke=stroke,

            strokeWidth=stroke_width

        ).properties(

            title=title

        ).project(

            type='mercator'

        ).interactive()

        return chart

chart = luis.map.plot(

    title="Louisiana Primary Roads",

    stroke="black",

)