Plotly 等值线图不同方面的不同色标？

Question

我制作了一个具有连续色标的等值线图并将其划分为 4 个子图面。问题是色标尺是所有 4 张地图的一个，即使我尝试更改色标尺，它也会同时应用于所有地图。有没有办法为不同的面设置不同的颜色比例？

fig = px.choropleth(df,
                     geojson=counties,
                     locations='id',
                     color='count',
                     facet_col='age_group',
                     facet_col_wrap=2,
                     color_continuous_scale='BuGn',
                     hover_name='county',
                     width=1000,
                     height=900,
                     animation_frame='year')
fig.update_geos(fitbounds="locations")    
fig.show()

Answer 1

您尚未提供示例 geojson 或数据。选择了美国各州并模拟了一个数据框，因此您的代码几乎可以正常工作（添加 featurekeyid 参数）
这是更新图形和动画帧中的轨迹以使用单独的 coloraxis
跟踪已更新，需要设置每个色轴的定位和色阶

import plotly.express as px
import requests
import geopandas as gpd

# get some geojson
geojson = requests.get(
    "https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_110m_admin_1_states_provinces.geojson"
).json()
counties = {
    k: v
    if k != "features"
    else [
        {
            k: v if k != "properties" else {"id": i, "name": v["name"]}
            for k, v in f.items()
        }
        for i, f in enumerate(v)
    ]
    for k, v in geojson.items()
}

# construct a dataframe of strucrture implied in question
df = (
    pd.json_normalize(counties["features"])
    .pipe(lambda d: d.drop(columns=[c for c in d.columns if not "properties" in c]))
    .rename(columns={"properties.id": "id", "properties.name": "county"})
    .merge(pd.DataFrame({"year": range(2015, 2023)}), how="cross")
    .merge(pd.DataFrame({"age_group": ["<18", "18-30", "30-65", ">65"]}), how="cross")
    .pipe(
        lambda d: d.assign(
            count=np.random.randint(1, 50, len(d))
            * (pd.factorize(d["age_group"])[0] + 1)
        )
    )
)

fig = px.choropleth(
    df,
    geojson=counties,
    locations="id",
    featureidkey="properties.id",
    color="count",
    facet_col="age_group",
    facet_col_wrap=2,
    color_continuous_scale="BuGn",
    hover_name="county",
    width=1000,
    height=900,
    animation_frame="year",
)
fig.update_geos(fitbounds="locations")

# update traces to use different coloraxis
for i, t in enumerate(fig.data):
    t.update(coloraxis=f"coloraxis{i+1}")
for fr in fig.frames:
    # update each of the traces in each of the animation frames
    for i, t in enumerate(fr.data):
        t.update(coloraxis=f"coloraxis{i+1}")

# position / config all coloraxis
fig.update_layout(
    coloraxis={"colorbar": {"x": -0.2, "len": 0.5, "y": 0.8}},
    coloraxis2={
        "colorbar": {
            "x": 1.2,
            "len": 0.5,
            "y": 0.8,
        },
        "colorscale": fig.layout["coloraxis"]["colorscale"],
    },
    coloraxis3={
        "colorbar": {"x": -0.2, "len": 0.5, "y": 0.3},
        "colorscale": fig.layout["coloraxis"]["colorscale"],
    },
    coloraxis4={
        "colorbar": {"x": 1.2, "len": 0.5, "y": 0.3},
        "colorscale": fig.layout["coloraxis"]["colorscale"],
    },
)

Plotly 等值线图不同方面的不同色标？

Different color scales for different facets of choropleth map in Plotly?

python

plotly