本文中介绍的是如何利用px.pie和go.Pie来绘制饼图，以及在饼图中的相关参数设置。
A pie chart is a circular statistical chart, which is divided into sectors to illustrate numerical proportion.
- 基于px.pie
- 基于go.pie
导入库
代码语言：javascript复制import pandas as pd
import numpy as np
import plotly_express as px
import plotly.graph_objects as go
import dash
import dash_core_components as dcc
import dash_html_components as html基于px.pie实现
In px.pie, data visualized by the sectors of the pie is set in values. The sector labels are set in names.
df = px.data.gapminder().query("year == 2007").query("continent == 'Europe'")
df.loc[df["pop"] < 2.e6, "country"] = "Other countries" # 将满足条件的全部改为Other countries
fig = px.pie(df, values="pop", names="country", title="Population of Eurpean contient")
fig.show()
基于go.pie实现
basic
In go.Pie, data visualized by the sectors of the pie is set in values. The sector labels are set in labels. The sector colors are set in marker.colors.
- labels
- values
labels = ['Oxygen','Hydrogen','Carbon_Dioxide','Nitrogen']
values = [4500, 2500, 1053, 500]
fig = go.Figure(data=go.Pie(labels=labels,values=values))
fig.show()
update_traces
代码语言：javascript复制# 颜色选项
colors = ['gold', 'mediumturquoise', 'darkorange', 'lightgreen']
# 绘图
fig = go.Figure(data=go.Pie(labels=['Oxygen','Hydrogen','Carbon_Dioxide','Nitrogen'],
values=[4500,2500,1053,500]))
# 更新饼图配置
fig.update_traces(hoverinfo='label percent', # 悬停信息
textinfo='value', # 饼图中显示的信息
textfont_size=20,
marker=dict(colors=colors, line=dict(color='#000000', width=2)))
fig.show()
文本隐藏
代码语言：javascript复制df = px.data.gapminder().query("continent == 'Asia'")
fig = px.pie(df, values='pop', names='country')
fig.update_traces(textposition='inside') # 文字信息在里面
fig.update_layout(uniformtext_minsize=15, # 文本信息的最小值
uniformtext_mode='hide' # 小于最小值则被隐藏
)
fig.show()
不进行隐藏的效果对比：
设置饼图颜色
通过序列形式
通过color_discrete_sequence=px.colors.sequential.Bluyl来实现
df = px.data.tips()
# 设置饼图的颜色：px.colors.sequential.Bluyl
fig = px.pie(df, values="tip", names="day",color_discrete_sequence=px.colors.sequential.Bluyl)
fig.show()
通过字典形式
代码语言：javascript复制# 通过字典的形式上色：这个颜色好看呀
fig = px.pie(df, values="tip",names="day",color="day",
color_discrete_map={'Thur':'lightcyan',
'Fri':'cyan',
'Sat':'royalblue',
'Sun':'darkblue'})
fig.show()
布局和属性设置
代码语言：javascript复制df = px.data.gapminder().query("year == 2007").query("continent == 'Americas'") # 居然是Americas！！！！
fig = px.pie(df, values='pop', names='country',
title='Population of American continent',
hover_data=['lifeExp'], labels={'lifeExp':'life expectancy'})
fig.update_traces(textposition='inside', textinfo='percent label') # 将文本的信息放在里面
fig.show()
修改参数之后的效果对比：
文本排列
文本信息如何在扇区中进行合理地排列，3种方式：
- horizontal
- radial
- tangential
Donut & Pulling sectors
代码语言：javascript复制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)]) # 通过hole参数实现中心的环
fig.show()
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])]) # 通过pull参数
fig.show()
