fig=px.bar(data_canada,x="year",y="pop",color="lifeExp",height=400,hover_data=["lifeExp","gdpPercap"],labels={"pop":"population of Canada"}# 将y轴的名称pop改掉)fig.show() 堆叠柱状图 When several rows share the same value ofx(here Female or Male), the rectangles are stacked on...
Plotly Express是一个基于Plotly的高级数据可视化库,它提供了一种简单且快速的方式来创建各种类型的图表。在使用Plotly Express创建柱状图(Bar Chart)时,可以通过设置颜色栏参数来实现数据的颜色编码。 在Plotly Express中,使用color参数来指定颜色栏参数。对于柱状图(Bar Chart),可以使用go.Bar函数来创建。然而,目前版本...
import plotly.express as px # 示例3: 创建柱状图 categories = ['A', 'B', 'C', 'D', 'E'] values = [30, 45, 60, 25, 50] # 创建柱状图 fig = px.bar(x=categories, y=values, color=categories, title='示例柱状图') # 设置图形布局 fig.update_layout( xaxis_title='类别', yaxis_...
importplotly_expressaspx importplotly plotly.offline.init_notebook_mode(connected=True) wind = px.data.wind() wind_plot = px.bar_polar(wind, r="value", theta="direction", color="strength", template="plotly_dark", color_discrete_sequence= px.colors.sequential.Plotly[-2::-1]) plotly.offli...
基于plotly_express绘制 2.1 基础树状图 在绘制树图的时候是基于数据的列表形式 name=["中国","福建","广东","厦门","深圳","珠海","湖北","湖南","长沙","陕西","衡阳","咸阳","东莞"]parent=["","中国","中国","福建","广东","广东","中国","中国","湖南","中国","湖南","陕西","广东...
使用Plotly Express创建带有渐变颜色的散点图。 size和color参数在图中表示第三个维度。 03 3D曲面图 import plotly.graph_objects as go import numpy as np # 生成示例数据 x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) x, y = np.meshgrid(x, y) ...
import plotly_express as px import plotly.graph_objects as go from datetime import datetime # yfinance 是一个流行的开源库,用于访问雅虎财经上可用的财务数据 import yfinance as yf 2 导入数据 网络OK的话,可以使用下面的代码直接从yfinance直接下载数据,然后保存到data.csv文件中。
OccupancyDetection | project Temperature, Humidity, CO2, Occupancy | where rand() < 0.1 | evaluate python(typeof(plotly:string), ```if 1: import plotly.express as px fig = px.scatter_3d(df, x='Temperature', y='Humidity', z='CO2', color='Occupancy') fig.update_layout(title=dict(tex...
import plotly.express as px df = px.data.gapminder() fig = px.scatter( df, x="gdp...
import plotly.express as px df = px.data.iris() fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", size='petal_length', hover_data=['petal_width']) fig.show() 气泡图 Bubble Chart 气泡图是我觉得基本图表类型中比较适合用plotly制作的,因为通常来说气泡图会有大量...