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# -*- coding: utf-8 -*-import plotly as pyimport plotly.graph_objs as gopyplt = py.offline.plot# Tracetrace_basic = [go.Bar( x = ['Variable_1', 'Variable_2', 'Variable_3','Variable_4','Variable_5'], y = [1, 2, 3, 2, 4], )]# Layoutlayout_basic = go.Layout( title = 'The Graph Title', xaxis = go.XAxis(range = [-0.5,4.5], domain = [0,1]) )# Figurefigure_basic = go.Figure(data = trace_basic, layout = layout_basic)# Plotpyplt(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 pyimport plotly.graph_objs as gopyplt = py.offline.plot# Tracestrace_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]# Layoutlayout = go.Layout( title = '净资产收益率对比图' )# Figurefigure = go.Figure(data = trace, layout = layout)# Plotpyplt(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 pyimport plotly.graph_objs as gopyplt = py.offline.plot # Stacked Bar Charttrace_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 pyimport plotly.graph_objs as gopyplt = 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'] # Basetrace0 = go.Bar( x=x_data, y=[0, 57999848, 0, 66899764, 0], marker=dict( color='rgba(1,1,1, 0.0)', ))# Tracetrace1 = 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 pyimport plotly.graph_objs as gopyplt = py.offline.plot # Customizing Individual Bar Colorsvolume = [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')

运行上述代码，可以看到上图所示图例

柱状图展示了5种金属，在某个交易日的最高涨幅与波动率情况，柱形图宽度表示相对波动率的高低。

柱形图越宽，波动率越大，高度表示涨幅，红色表示上涨，绿色表示下跌。

用line设置柱状图外部线框，用width设置柱状图的宽度，用opacity设置柱状图颜色的透明度情况。

基本的柱状图情况，就讲到这里。

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。

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