今天我们来讲一下如何使用Python使用Plotly绘图工具，绘制面积图
绘制面积图与绘制散点图和折线图的画法类似，使用plotly graph_objs
中的Scatter函数，不同之处在于面积图对fill属性的设置
也就是说，相当于是在折线图的基础上，对图形进行填充
import plotly as pyimport plotly.graph_objs as goimport numpy as nppyplt = py.offline.plot# 随机生成100个交易日的收益率s1 = np.random.RandomState(8) # 定义局部种子s2 = np.random.RandomState(9) # 定义局部种子rd1 = s1.rand(100)/10 - 0.02rd2 = s2.rand(100)/10 - 0.02# 设定初始资金initial1 = 100000initial2 = 100000total1 = []total2 = []for i in range(len(rd1)):initial1 = initial1*rd1[i] + initial1initial2 = initial2*rd2[i] + initial2total1.append(initial1)total2.append(initial2)trace1 = go.Scatter(#x = [1, 2, 3, 4],y = total1,fill = 'tonexty',mode= 'none', # 无边界线name = "策略1")trace2 = go.Scatter(#x = [1, 2, 3, 4],y = total2,fill = 'tozeroy',mode= 'none',# 无边界线name = "策略2")data = [trace1, trace2]layout = dict(title = '策略净值曲线',xaxis = dict(title = '交易天数'),yaxis = dict(title = '净值'),)fig = dict(data = data, layout = layout)pyplt(fig, filename='tmp/1.html')
运行如上代码，会得到如上图所示的图形面积图
展示了两个不同的交易策略的净值曲线图，数据是随机生成的
就相当于做了折线图后，进行了填充得到
我们在来说一下内部填充面积图
内部填充面积图是仅仅填充两条曲线交叉所形成的面积部分，同样设置fill属性来完成。
只需要在原来的面积图上设置第一条曲线无填充效果即可
下面我们来看看代码
import plotly as pyimport plotly.graph_objs as goimport numpy as nppyplt = py.offline.plot# 随机生成100个交易日的收益率s1 = np.random.RandomState(8) # 定义局部种子s2 = np.random.RandomState(9) # 定义局部种子rd1 = s1.rand(100)/10 - 0.02rd2 = s2.rand(100)/10 - 0.02# 设定初始资金initial1 = 100000initial2 = 100000total1 = []total2 = []for i in range(len(rd1)):initial1 = initial1*rd1[i] + initial1initial2 = initial2*rd2[i] + initial2total1.append(initial1)total2.append(initial2)trace1 = go.Scatter(y = total1,fill = None,mode= 'lines', # 无边界线name = "策略1")trace2 = go.Scatter(#x = [1, 2, 3, 4],y = total2,fill = 'tonexty',mode= 'lines',# 无边界线name = "策略2")data = [trace1, trace2]layout = dict(title = '策略净值曲线',xaxis = dict(title = '交易天数'),yaxis = dict(title = '净值'),)fig = dict(data = data, layout = layout)pyplt(fig, filename='tmp/1.html')
运行上诉代码，我们可以得到如上图所示的内部填充面积图
我们设置了fill = None,
在设置第二条曲线的填充的效果为tonexty
即fill = 'tonexty' 即可得到如上图所示的图例
接下来我们讲解一下堆积面积图
堆积面积图与之前我写的博客中，层叠柱状图类似
都是展示了数据累加的效果
不同之处在于对数据的设置
import plotly as pyimport plotly.graph_objs as godata_1 = go.Scatter(x = ['基金1', '基金2', '基金3', '基金4','基金5'],y = [32.52, 43.12, 43.47, 44.36, 33.11],name = '股票投资',mode = 'lines',line = dict(width=0.5,color = 'rgb(184, 247, 212)'),fill = 'tonexty')data_2 = go.Scatter(x = ['基金1', '基金2', '基金3', '基金4','基金5'],y = [63.24, 54.33, 74.28, 63.91, 63.11],name = '其它投资',mode = 'lines',line = dict(width=0.5,color = 'rgb(111, 231, 219)'),fill = 'tonexty')data_3 = go.Scatter(x = ['基金1', '基金2', '基金3', '基金4','基金5'],y = [83.24, 74.33, 93.91, 79.22, 83.11],name='债券投资',mode='lines',line=dict(width=0.5,color='rgb(127, 166, 238)'),fill='tonexty')data_4 = go.Scatter(x = ['基金1', '基金2', '基金3', '基金4','基金5'],y = [100, 100, 100, 100, 100],name='银行存款',mode='lines',line=dict(width=0.5,color='rgb(131, 90, 241)'),fill='tonexty')data = [data_1, data_2, data_3, data_4]layout = go.Layout(title = '基金资产配置比例图',showlegend = True,xaxis = dict(type = 'category',),yaxis = dict(type = 'linear',range = [1, 100],dtick = 20,ticksuffix = '%'))pyplt = py.offline.plotfig = go.Figure(data = data, layout = layout)pyplt(fig, filename = 'tmp/stacked-area-plot.html')
可以看到，运行上诉代码，可以得到如上图所示的堆积面积图图例
注意的是，在绘制层叠柱状图时需要设置stack模式，而绘制堆积面积图时则不需要
这就是堆积面积图需要累加数据的原因
在本质上，堆积面积图的堆积效果是在同一个图形中绘制对个面积图来实现
今天就讲到这里，谢谢大家阅读，感谢支持！谢谢点赞
