Plotly中的Pie Charts

饼图

效果

代码

import plotly.express as px

# This dataframe has 244 lines, but 4 distinct values for `day`
df = px.data.tips()
fig = px.pie(df, values='tip', names='day')
fig.show()

这里会将values的值自动整合汇总

饼图扇形颜色

效果

代码

import plotly.express as px

df = px.data.tips()
fig = px.pie(df, values='tip', names='day', color_discrete_sequence=px.colors.sequential.RdBu)
fig.show()

设置风格

效果

代码

import plotly.graph_objects as go

colors = ['gold', 'mediumturquoise', 'darkorange', 'lightgreen']

fig = go.Figure(data=[go.Pie(labels=['Oxygen', 'Hydrogen', 'Carbon_Dioxide', 'Nitrogen'],
                             values=[4500, 2500, 1053, 500])])
fig.update_traces(hoverinfo='label+percent', textinfo='value', textfont_size=20,
                  marker=dict(colors=colors, line=dict(color='#000000', width=2)))
fig.show()

圈图

效果

代码

import plotly.graph_objects as go

labels = ['Oxygen', 'Hydrogen', 'Carbon_Dioxide', 'Nitrogen']
values = [4500, 2500, 1053, 500]

# Use `hole` to create a donut-like pie chart
fig = go.Figure(data=[go.Pie(labels=labels, values=values, hole=.3)])
fig.show()

将扇区拉出

效果

代码

import plotly.graph_objects as go

labels = ['Oxygen', 'Hydrogen', 'Carbon_Dioxide', 'Nitrogen']
values = [4500, 2500, 1053, 500]

# pull is given as a fraction of the pie radius
fig = go.Figure(data=[go.Pie(labels=labels, values=values, pull=[0, 0, 0.2, 0])])
fig.show()

子图中的饼图

效果

代码

import plotly.graph_objects as go
from plotly.subplots import make_subplots

labels = ["US", "China", "European Union", "Russian Federation", "Brazil", "India",
          "Rest of World"]

# Create subplots: use 'domain' type for Pie subplot
fig = make_subplots(rows=1, cols=2, specs=[[{'type': 'domain'}, {'type': 'domain'}]])
fig.add_trace(go.Pie(labels=labels, values=[16, 15, 12, 6, 5, 4, 42], name="GHG Emissions"),
              1, 1)
fig.add_trace(go.Pie(labels=labels, values=[27, 11, 25, 8, 1, 3, 25], name="CO2 Emissions"),
              1, 2)

# Use `hole` to create a donut-like pie chart
fig.update_traces(hole=.4, hoverinfo="label+percent+name")

fig.update_layout(
    title_text="Global Emissions 1990-2011",
    # Add annotations in the center of the donut pies.
    annotations=[dict(text='GHG', x=0.21, y=0.5, font_size=20, showarrow=False),
                 dict(text='CO2', x=0.79, y=0.5, font_size=20, showarrow=False)])
fig.show()

面积与总计数成比例

效果

代码

import plotly.graph_objects as go
from plotly.subplots import make_subplots

labels = ["Asia", "Europe", "Africa", "Americas", "Oceania"]

fig = make_subplots(1, 2, specs=[[{'type':'domain'}, {'type':'domain'}]],
                    subplot_titles=['1980', '2007'])
fig.add_trace(go.Pie(labels=labels, values=[4, 7, 1, 7, 0.5], scalegroup='one',
                     name="World GDP 1980"), 1, 1)
fig.add_trace(go.Pie(labels=labels, values=[21, 15, 3, 19, 1], scalegroup='one',
                     name="World GDP 2007"), 1, 2)

fig.update_layout(title_text='World GDP')
fig.show()

scalegroup='one'即可

朝阳图

效果

代码

import plotly.graph_objects as go

fig = go.Figure(go.Sunburst(
    labels=["Eve", "Cain", "Seth", "Enos", "Noam", "Abel", "Awan", "Enoch", "Azura"],
    parents=["", "Eve", "Eve", "Seth", "Seth", "Eve", "Eve", "Awan", "Eve"],
    values=[10, 14, 12, 10, 2, 6, 6, 4, 4],
))
fig.update_layout(margin=dict(t=0, l=0, r=0, b=0))

fig.show()

官方文档