Plotly Choropleth地图：如何将1.425887B格式化为1.4B？

问题背景 #

绘制世界人口Choropleth地图时，鼠标悬停显示的人口数值（如中国的1.425887B）需要格式化为保留一位小数的形式（如1.4B）。当前实现代码及数据集结构如下：

当前实现代码 #

data2022 = dict(type = 'choropleth',
            colorscale = 'agsunset',
            reversescale = True,
            locations = df['Country/Territory'],
            locationmode = 'country names',
            z = df['2022 Population'],
            text = df['CCA3'],
            marker = dict(line = dict(color = 'rgb(12, 12, 12)', width=1)),
            colorbar = {'title': 'Population'})

layout2022 = dict(title = '<b>World Population 2022<b>',
               geo = dict(showframe = True,
                          showland = True, landcolor = 'rgb(198, 197, 198)',
                          showlakes = True, lakecolor = 'rgb(85, 173, 240)',
                          showrivers = True, rivercolor = 'rgb(173, 216, 230)', 
                          showocean = True, oceancolor = 'rgb(173, 216, 230)',
                          projection = {'type': 'natural earth'}))

choromap2022 = go.Figure(data=[data2022], layout=layout2022) 

choromap2022.update_geos(lataxis_showgrid = True, lonaxis_showgrid = True)

choromap2022.update_layout(height = 600,
                       title_x = 0.5, 
                       title_font_color = 'red',
                       title_font_family = 'Times New Roman',
                       title_font_size = 30,
                       margin=dict(t=80, r=50,  l=50))

iplot(choromap2022)

数据集结构 #

'CCA3': {0: 'AFG', 1: 'ALB', 2: 'DZA', 3: 'ASM', 4: 'AND'},
 'Country/Territory': {0: 'Afghanistan',
  1: 'Albania',
  2: 'Algeria',
  3: 'American Samoa',
  4: 'Andorra'},
 'Capital': {0: 'Kabul',
  1: 'Tirana',
  2: 'Algiers',
  3: 'Pago Pago',
  4: 'Andorra la Vella'},
 'Continent': {0: 'Asia', 1: 'Europe', 2: 'Africa', 3: 'Oceania', 4: 'Europe'},
 '2022 Population': {0: 41128771, 1: 2842321, 2: 44903225, 3: 44273, 4: 79824},
 '2020 Population': {0: 38972230, 1: 2866849, 2: 43451666, 3: 46189, 4: 77700},
 '2015 Population': {0: 33753499, 1: 2882481, 2: 39543154, 3: 51368, 4: 71746},
 '2010 Population': {0: 28189672, 1: 2913399, 2: 35856344, 3: 54849, 4: 71519},
 '2000 Population': {0: 19542982, 1: 3182021, 2: 30774621, 3: 58230, 4: 66097},
 '1990 Population': {0: 10694796, 1: 3295066, 2: 25518074, 3: 47818, 4: 53569},
 '1980 Population': {0: 12486631, 1: 2941651, 2: 18739378, 3: 32886, 4: 35611},
 '1970 Population': {0: 10752971, 1: 2324731, 2: 13795915, 3: 27075, 4: 19860},
 'Area (km²)': {0: 652230, 1: 28748, 2: 2381741, 3: 199, 4: 468},
 'Density (per km²)': {0: 63.0587,
  1: 98.8702,
  2: 18.8531,
  3: 222.4774,
  4: 170.5641},
 'Growth Rate': {0: 1.0257, 1: 0.9957, 2: 1.0164, 3: 0.9831, 4: 1.01},
 'World Population Percentage': {0: 0.52, 1: 0.04, 2: 0.56, 3: 0.0, 4: 0.0}

解决方案 #

通过自定义hovertemplate参数可以实现悬停数值的格式化，以下提供两种可行方法：

方法一：利用Plotly内置格式化语法（简洁高效） #

直接在data2022中添加hovertemplate，使用Plotly内置的数值格式化规则将人口数转为十亿单位并保留一位小数：

data2022 = dict(type='choropleth',
                colorscale='agsunset',
                reversescale=True,
                locations=df['Country/Territory'],
                locationmode='country names',
                z=df['2022 Population'],
                text=df['CCA3'],
                # 自定义悬停模板，%{z:.1s}自动将数值转为缩写形式并保留一位有效数字
                hovertemplate='<b>%{location}</b><br>' +
                              'CCA3: %{text}<br>' +
                              'Population: %{z:.1s}B<extra></extra>',
                marker=dict(line=dict(color='rgb(12, 12, 12)', width=1)),
                colorbar={'title': 'Population'})

方法二：预先格式化数值（灵活性更高） #

先通过函数将人口数转为指定格式的字符串，再通过customdata传入悬停模板：

# 定义格式化函数，将人口数转为保留一位小数的十亿单位字符串
def format_population(pop):
    return f"{pop / 1e9:.1f}B"

data2022 = dict(type='choropleth',
                colorscale='agsunset',
                reversescale=True,
                locations=df['Country/Territory'],
                locationmode='country names',
                z=df['2022 Population'],
                text=df['CCA3'],
                # 自定义悬停模板，调用customdata中的格式化后数值
                hovertemplate='<b>%{location}</b><br>' +
                              'CCA3: %{text}<br>' +
                              'Population: %{customdata}<extra></extra>',
                # 传入预先格式化好的人口数值
                customdata=df['2022 Population'].apply(format_population),
                marker=dict(line=dict(color='rgb(12, 12, 12)', width=1)),
                colorbar={'title': 'Population'})

替换data2022部分后重新运行代码，即可看到悬停时人口数值显示为1.4B这类保留一位小数的格式。

内容的提问来源于stack exchange，提问作者Đạt Dương