运行Plotly县级别Choropleth脚本遇TypeError: 'MultiPolygon'不可迭代错误

问题详情 #

运行Plotly官方文档中的县级别Choropleth示例代码时，启动后立即报错：TypeError: 'MultiPolygon' object is not iterable。我查找了相关问题的解决方案，但不确定是否适配当前场景，其中某方案看似可行，但疑惑Plotly官方发布的基础代码为何需要变通处理，怀疑是自己代码写法存在疏漏。

运行代码 #

import plotly.figure_factory as ff

import numpy as np
import pandas as pd

df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv')
df_sample_r = df_sample[df_sample['STNAME'] == 'Florida']

values = df_sample_r['TOT_POP'].tolist()
fips = df_sample_r['FIPS'].tolist()

endpts = list(np.mgrid[min(values):max(values):4j])
colorscale = ["#030512","#1d1d3b","#323268","#3d4b94","#3e6ab0",
              "#4989bc","#60a7c7","#85c5d3","#b7e0e4","#eafcfd"]
fig = ff.create_choropleth(
    fips=fips, values=values, scope=['Florida'], show_state_data=True,
    colorscale=colorscale, binning_endpoints=endpts, round_legend_values=True,
    plot_bgcolor='rgb(229,229,229)',
    paper_bgcolor='rgb(229,229,229)',
    legend_title='Population by County',
    county_outline={'color': 'rgb(255,255,255)', 'width': 0.5},
    exponent_format=True,
)
fig.layout.template = None
fig.show()

原因分析与解决方案 #

这个报错本质是依赖库版本不兼容导致：新版本的geopandas（或其依赖的shapely库）对MultiPolygon对象的迭代逻辑做了调整，而Plotly的create_choropleth函数尚未适配这一变化，导致无法直接迭代MultiPolygon对象。

方案1：锁定兼容版本的依赖库 #

这是最直接的解决方式，无需修改代码：

• 将plotly版本降级到5.15.0及以下
• 将geopandas版本降级到0.13.2及以下
• 执行安装命令：

  pip install plotly==5.15.0 geopandas==0.13.2
  

方案2：替换为兼容的绘图函数（无需降级） #

如果不想修改依赖版本，可以使用plotly.express的choropleth_mapbox函数替代，该函数对新版本地理库兼容性更好：

import plotly.express as px
import pandas as pd

df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv')
df_sample_r = df_sample[df_sample['STNAME'] == 'Florida']

# 使用plotly.express的choropleth_mapbox实现相同效果
fig = px.choropleth_mapbox(df_sample_r, 
                           geojson="https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json",
                           locations='FIPS', 
                           color='TOT_POP',
                           color_continuous_scale=["#030512","#1d1d3b","#323268","#3d4b94","#3e6ab0",
                                                  "#4989bc","#60a7c7","#85c5d3","#b7e0e4","#eafcfd"],
                           range_color=(df_sample_r['TOT_POP'].min(), df_sample_r['TOT_POP'].max()),
                           mapbox_style="carto-positron",
                           zoom=6, center = {"lat": 27.994402, "lon": -81.760254},
                           opacity=0.5,
                           labels={'TOT_POP':'Population'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

内容的提问来源于stack exchange，提问作者Dave