import plotly.express as px df = px.data.gapminder() fig = px.scatter(df.query("year==2007"), x="gdpPercap", y="lifeExp", size="pop", color="continent", hover_name="country", log_x=True, size_max=60) fig.show()
fig = px.scatter_ternary(df, a="Joly", b="Coderre", c="Bergeron", color="winner", size="total", hover_name="district", size_max=15, color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"} ) 3D散点图 df = px.data.election() fig = px.scatter_3d(...
这将创建简单的两个 scatter3d 图,其中 hoverdata 是 x、y 和 z 轴。现在您要将数据 m=[9,8,7,6,5] 添加到第一个图中。您可以在 text 参数中解析 m 并添加 hovertemplate。 fig.add_trace(go.Scatter3d(x=[0,1,2,3],y=[0,1,2,3],z=[0,1,2,3], text=[9,8,7,6], hovertemplate=...
# 气泡图import plotly.express as pxdf = px.data.gapminder()fig = px.scatter(df.query("year==2007"), x="gdpPercap", y="lifeExp", size="pop", # 设置气泡大小依据字段pop color="continent", hover_name="country", log_x=True, size_max=60, #设置最大气泡 )fig.s...
px.scatter(gapminder2002, x='gdpPercap', y='lifeExp', color='continent', size='pop', size_max=60, hover_name="country",# 悬停显示的内容 hover_data=["year","continent","gdpPercap","lifeExp"], title="Mathpretty") 最终的显示的结果如下图所示, 把鼠标放在上面, 会出现国家的信息, 以...
px.scatter_geo(data_frame=None, lat=None, lon=None, locations=None, locationmode=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_di...
fig=px.scatter(stu,x="chinese",y="math",hover_data=["name"],# 列表形式 color="age",size="age",# 散点大小 size_max=60,text="name"# 显示name属性中的数据信息)fig.show() 改变文本显示位置 文本显示位置主要顶部top、中间middle、底部bottom,加上左中右left、center、right的组合: ...
name:"Data", showlegend:true, hoverinfo:"all", line: { color:"blue", width:2, }, marker: { color:"blue", size:8, symbol:"circle", }, };varViol={ type:"scatter", x: [6,9], y: [-7,8], mode:"markers", name:"Violation", ...
import plotly.express as px# 创建一个简单的数据框df = px.data.gapminder().query("year==2007")# 创建一个地图fig = px.scatter_geo(df, locations="iso_alpha", color="continent", hover_name="country", size="pop", projection="natural earth")# 显示地图fig.show()locations="iso_alpha...
三元图: scatter_ternary, line_ternary 普通最小二乘回归可视化 将线性普通最小二乘(OLS)回归趋势线或非线性局部加权散点图平滑(LOWESS)趋势线添加到Python中的散点图。将鼠标悬停在趋势线上将显示该线的方程式及其R平方值,非常方便。 单线拟合 与seaborn类似,plotly图表主题不需要单独设置,使用默认参数即可满足正常...