可视化神器Plotly美化表格
有时候看到一份表格，没有任何的颜色修饰，总觉得缺点美观效果。在Excel中我们可以直接对字体的颜色、大小等进行设置，还可以进行单元格的颜色填充，在plotly中美化表格输出主要是有两种方式：
使用go.Table方法
使用figure_factory的creat_table方法
Plotly连载文章
import pandas as pd
import numpy as np
import plotly_express as px
import plotly.graph_objects as go
import plotly.figure_factory as ff
go.Table实现
该方法类似其他的图表绘制，直接使用go.Table方法之后往其中加入数据
添加表头和单元格中的数据
import plotly.graph_objects as go
fig = go.Figure(data=[go.Table(
header=dict(values=['语文', '数学']),
cells=dict(values=[[100, 90, 140, 123],
[105, 135, 75, 95]]))
fig.show()
个性化表格设置
import plotly.graph_objects as go
fig = go.Figure(data=[go.Table(
header=dict(values=['语文', '数学'],
line_color="darkslategray",
fill_color="lightskyblue",
align="center"
cells=dict(values=[[100, 90, 140, 123],
[105, 135, 75, 95]],
line_color="darkslategray",
fill_color="lightcyan",
align="center"
fig.update_layout(width=600,height=400)
fig.show()
DataFrame转成表格
将DataFrame数据快速转成漂亮的表格
fig = go.Figure(
data=[go.Table(
header=dict(values=list(data.columns),
fill_color='paleturquoise',
align='left'),
cells=dict(values=[data.性别,data.年龄,data.成绩],
fill_color='lavender',
align='left'
fig.show()
改变row和column的大小
有时候单元格的数据太长，我们需要进行单元格大小的调整
import plotly.graph_objects as go
values = [["李白 唐代","杜甫 唐代","苏轼 宋代","王安石 宋代"],
["床前明月,疑是地上霜;举头望明月,低头思故乡",
"国破山河在，城春草木深。感时花溅泪，恨别鸟惊心。<br>烽火连三月，家书抵万金。白头骚更短，浑欲不胜簪。",
"十年生死两茫茫，不思量，自难忘。千里孤坟，无处话凄凉。<br>纵使相逢应不识，尘满面，鬓如霜。<br>夜来幽梦忽还乡，小轩窗，正梳妆。相顾无言，惟有泪千行。<br>料得年年肠断处，明月夜，短松冈。",
"念往昔、繁华竞逐。叹门外楼头，悲恨相续。<br>千古凭高，对此谩嗟荣辱。<br>六朝旧事随流水，但寒烟、芳草凝绿。<br>至今商女，时时犹唱后庭遗曲。"
fig = go.Figure(data=[go.Table(
columnorder = [1,2],
columnwidth = [800,4000],
header = dict(
values=[["唐宋作家"],["代表作品"]],
line_color='darkslategray',
fill_color='royalblue',
align=['left','center'],
font=dict(color='white', size=12),
font_size=12,
height=40
cells = dict(
values=values,
line_color='darkslategray',
fill=dict(color=['paleturquoise', 'white']),
align=['left', 'center'],
font_size=12,
height=50))
fig.show()
设置表格渐变色
import plotly.graph_objects as go
import pandas as pd
colors = ['rgb(239, 243, 255)',
'rgb(189, 215, 231)',
'rgb(107, 174, 214)',
'rgb(59, 130, 189)',
'rgb(9, 81, 156)']
data = {'Year' : [2015, 2016, 2017, 2018, 2019],
'Color' : colors}
df = pd.DataFrame(data)
print(df)
fig = go.Figure(data=[go.Table(
header=dict(
values=["Color", "<b>YEAR</b>"],
line_color='white',
fill_color='white',
align='center',
font=dict(color='black', size=12)
cells=dict(
values=[df.Color, df.Year],
line_color=[df.Color],
fill_color=[df.Color],
align='center',
font=dict(color='black', size=13)
fig.show()
表格数据滑动
当DataFrame中的数据过多的时候，我们可以进行滑动展示和查看：
student = pd.DataFrame({"性别":["小明","小红","小周","小孙","小苏"] * 100,
"年龄":[19,29,32,20,18] * 100,
"性别":["男","女","男","女","男"] * 100,
"成绩":[590,588,601,670,555] * 100})
student
fig = go.Figure(
data=[go.Table(
header=dict(values=list(student.columns),
fill_color='paleturquoise',
align='left'),
cells=dict(values=[student.性别,student.年龄,student.成绩],
fill_color='lavender',
align='left'
fig.show()
creat_table
第二种方法是使用图形工厂中的creat_table方法来生成
基础图表生成
DataFrame数据生成表格
import plotly.figure_factory as ff
fig = ff.create_table(tips)
fig.show()
数据中添加链接
import plotly.figure_factory as ff
data = [['姓名', '年龄', '成绩'],
['小明', 20, 620],
['小红', 22, 677],
['小周', 19, 606]]
fig = ff.create_table(data,height_constant=20)
fig.show()
改变宽度后的样子：
import plotly.figure_factory as ff
colorscale = [[0, '#4d004c'],[.5, '#f2e5ff'],[1, '#ffffff']]
fig = ff.create_table(tips, colorscale=colorscale)
fig.show()
字体颜色设置
import plotly.figure_factory as ff
data = [['name', 'rank'], ['小明', 1], ['小红', 2],
['小周', 3], ['小张', 4], ['小孙', 5], ['小王', 6]]
colorscale = [[0, '#272D31'],[.5, '#ff9f9f'],[1, '#ffffff']]
font=['#7CFCFC', '#0FEE00', '#008B00', '#F04F00', '#6A0000', '#CD0000', '#FF3030']
fig = ff.create_table(data,
colorscale=colorscale,
font_colors=font)
fig.layout.width=500
fig.show()
图形和表格联用
采用的消费数据集tips
import plotly.graph_objs as go
import plotly.figure_factory as ff
fig = ff.create_table(tips)
fig.add_trace(go.Scatter(
x=tips["tip"],
y=tips["total_bill"],
marker=dict(color='#9099ff'),
name="total_bill <br>tip",
xaxis='x2', yaxis='y2'
fig.add_trace(go.Scatter(
x=tips["size"],
y=tips["total_bill"],
marker=dict(color='#a099af'),
name="total_bill <br>size",
xaxis='x2', yaxis='y2'
fig.update_layout(
title_text="消费数据图表联合",
height=500,
margin={"t":75,"b":100},
xaxis = {'domain': [0, .45]},
xaxis2 = {'domain': [0.6, 1.]},
yaxis2 = {'anchor': 'x2', 'title': 'tips'}
fig.show()
将图形竖直方向上排列：
import plotly.graph_objs as go
import plotly.figure_factory as ff
fig = ff.create_table(tips)
fig.add_trace(go.Scatter(
x=tips["tip"],
y=tips["total_bill"],
marker=dict(color='#9099ff'),
name="total_bill <br>tip",
xaxis='x2', yaxis='y2'
fig.add_trace(go.Scatter(
x=tips["size"],
y=tips["total_bill"],
marker=dict(color='#a099af'),
name="total_bill <br>size",
xaxis='x2', yaxis='y2'
fig.update_layout(
title_text="消费数据图表联合",
height=800,
margin={"t":75,"l":50},
yaxis = {'domain': [0, .5]},
xaxis2 = {'anchor': "y2"},
yaxis2 = {'domain': [0.6, 1], 'anchor':'x2', 'title': 'tips'}
fig.show()
gyratesky
数据可视化
