python使用Plotly绘图工具绘制柱状图

本文实例为大家分享了python使用Plotly绘图工具绘制柱状图的具体代码，供大家参考，具体内容如下使用Plotly绘制基本的柱状图，需要用到的函数是graph_objs 中 Bar函数通过参数，可以设

本文实例为大家分享了python使用Plotly绘图工具绘制柱状图的具体代码，供大家参考，具体内容如下

使用Plotly绘制基本的柱状图，需要用到的函数是graph_objs 中 Bar函数

通过参数，可以设置柱状图的样式。

通过barmod进行设置可以绘制出不同类型的柱状图出来。

我们先来实现一个简单的柱状图：

# -*- coding: utf-8 -*-
import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
# Trace
trace_basic = [go.Bar(
 x = ['Variable_1', 'Variable_2', 'Variable_3','Variable_4','Variable_5'],
 y = [1, 2, 3, 2, 4],
 )]
# Layout
layout_basic = go.Layout(
 title = 'The Graph Title',
 xaxis = go.XAxis(range = [-0.5,4.5], domain = [0,1])
 )
# Figure
figure_basic = go.Figure(data = trace_basic, layout = layout_basic)
# Plot
pyplt(figure_basic, filename='tmp/1.html')

上面这个例子，就是一个简单的柱状图。

下面我们讲下另外一种图，柱状簇

实现过程则是，在基本的柱状图中，加入多租数据即可实现，柱状簇

import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
# Traces
trace_1 = go.Bar(
 x = ["西南石油", "东方明珠", "海泰发展"],
 y = [4.12, 5.32, 0.60],
 name = "201609"
 )
trace_2 = go.Bar(
 x = ["西南石油", "东方明珠", "海泰发展"],
 y = [3.65, 6.14, 0.58],
 name = "201612"
 )
 
trace_3 = go.Bar(
 x = ["西南石油", "东方明珠", "海泰发展"],
 y = [2.15, 1.35, 0.19],
 name = "201703"
 )
trace = [trace_1, trace_2, trace_3]
# Layout
layout = go.Layout(
 title = '净资产收益率对比图'
 )
# Figure
figure = go.Figure(data = trace, layout = layout)
# Plot
pyplt(figure, filename='tmp/2.html')

执行上述代码，我们可以看到如上图所示柱状簇图例

可将数据堆叠生成。

接下来在讲讲如何绘制层叠柱状图

层叠柱状图的绘制方法与柱状簇的绘制方法基本差不多

也就是对同一个柱状簇进行叠加，实现方法是对Layout中的barmode属性进行设置

barmode = 'stack'

其余参数，与柱状簇相同。

# -*- coding: utf-8 -*-
import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
 
# Stacked Bar Chart
trace_1 = go.Bar(
 x = ['深证50', '上证50', '西南50', '西北50','华中50'],
 y = [0.7252, 0.9912, 0.5347, 0.4436, 0.9911],
 name = '股票投资'
)
 
trace_2 = go.Bar(
 x = ['深证50', '上证50', '西南50', '西北50','华中50'],
 y = [0.2072, 0, 0.4081, 0.4955, 0.02],
 name='其它投资'
)
 
trace_3 = go.Bar(
 x = ['深证50', '上证50', '西南50', '西北50','华中50'],
 y = [0, 0, 0.037, 0, 0],
 name='债券投资'
)
 
trace_4 = go.Bar(
 x = ['深证50', '上证50', '西南50', '西北50','华中50'],
 y = [0.0676, 0.0087, 0.0202, 0.0609, 0.0087],
 name='银行存款'
)
 
trace = [trace_1, trace_2, trace_3, trace_4]
layout = go.Layout(
 title = '基金资产配置比例图',
 barmode='stack'
)
 
fig = go.Figure(data = trace, layout = layout)
pyplt(fig, filename='tmp/1.html')

瀑布式柱状图

瀑布式柱状图是层叠柱状图的另外一种表现

可以选择性地显示层叠部分来实现柱状图的悬浮效果。

# -*- coding: utf-8 -*-
import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
 
x_data = ['资产1', '资产2',
  '资产3','资产4', '总资产']
y_data = [56000000, 65000000, 65000000, 81000000, 81000000]
text = ['666,999,888万元', '8,899,666万元', '88,899,666万元', '16,167,657万元', '888,888,888万元']
 
# Base
trace0 = go.Bar(
 x=x_data,
 y=[0, 57999848, 0, 66899764, 0],
 marker=dict(
 color='rgba(1,1,1, 0.0)',
 )
)
# Trace
trace1 = go.Bar(
 x=x_data,
 y=[57999848, 8899916, 66899764,16167657, 83067421],
 marker=dict(
 color='rgba(55, 128, 191, 0.7)',
 line=dict(
  color='rgba(55, 128, 191, 1.0)',
  width=2,
 )
 )
)
 
data = [trace0, trace1]
layout = go.Layout(
 title = '测试图例',
 barmode='stack',
 showlegend=False
)
 
annotations = []
 
for i in range(0, 5):
 annotations.append(dict(x=x_data[i], y=y_data[i], text=text[i],
     font=dict(family='Arial', size=14,
     color='rgba(245, 246, 249, 1)'),
     showarrow=False,))
 layout['annotations'] = annotations
 
fig = go.Figure(data=data, layout=layout)
pyplt(fig, filename = 'tmp/1.html')

运行上述代码，可以得到如上图所示的瀑布式柱状图。

下面我们说说，图形样式的设置。

对于柱状图颜色与样式的设置可以通过设置下面这个案例来说明。

import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
 
# Customizing Individual Bar Colors
volume = [0.49,0.71,1.43,1.4,0.93]
width = [each*3/sum(volume) for each in volume]
trace0 = go.Bar(
 x = ['AU.SHF', 'AG.SHF', 'SN.SHF',
 'PB.SHF', 'CU.SHF'],
 y = [0.85, 0.13, -0.93, 0.46, 0.06],
 width = width,
 marker = dict(
 color=['rgb(205,38,38)', 'rgb(205,38,38)',
  'rgb(34,139,34)', 'rgb(205,38,38)',
  'rgb(205,38,38)'],
 line=dict(
  color='rgb(0,0,0)',
  width=1.5,
 )),
 opacity = 0.8,
)
 
data = [trace0]
layout = go.Layout(
 title = '有色金属板块主力合约日内最高涨幅与波动率图',
 xaxis=dict(tickangle=-45),
)
 
fig = go.Figure(data=data, layout=layout)
pyplt(fig, filename='tmp/4.html')