将多个图形绘制为子图

问题描述 投票：0回答：5

这些资源展示了如何从单个 Pandas DataFrame 中获取数据并在 Plotly 图表上绘制不同的列子图。我有兴趣从单独的 DataFrame 创建图形并将它们绘制到与子图相同的图形中。这对 Plotly 来说可能吗？

https://plot.ly/python/subplots/

https://plot.ly/pandas/subplots/

我正在从这样的数据框中创建每个图形：

import pandas as pd
import cufflinks as cf
from plotly.offline import download_plotlyjs, plot,iplot
cf.go_offline()

fig1 = df.iplot(kind='bar',barmode='stack',x='Type',
                       y=mylist,asFigure=True)

编辑： 这是一个基于 Naren 反馈的例子：

创建数据框：

a={'catagory':['loc1','loc2','loc3'],'dogs':[1,5,6],'cats':[3,1,4],'birds':[4,12,2]}
df1 = pd.DataFrame(a)
b={'catagory':['loc1','loc2','loc3'],'dogs':[12,3,5],'cats':[4,6,1],'birds':[7,0,8]}
df2 = pd.DataFrame(b)

情节只会显示狗的信息，而不是鸟或猫的信息：

fig = tls.make_subplots(rows=2, cols=1)

fig1 = df1.iplot(kind='bar',barmode='stack',x='catagory',
                       y=['dogs','cats','birds'],asFigure=True)

fig.append_trace(fig1['data'][0], 1, 1)

fig2 = df2.iplot(kind='bar',barmode='stack',x='catagory',
                       y=['dogs','cats','birds'],asFigure=True)

fig.append_trace(fig2['data'][0], 2, 1)

iplot(fig)

python plotly plotly-python
5个回答
27
投票

这是一个工作示例中的一个简短函数，用于将图形列表全部保存到单个 HTML 文件中。

def figures_to_html(figs, filename="dashboard.html"):
    with open(filename, 'w') as dashboard:
        dashboard.write("<html><head></head><body>" + "\n")
        for fig in figs:
            inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]
            dashboard.write(inner_html)
        dashboard.write("</body></html>" + "\n")


# Example figures
import plotly.express as px
gapminder = px.data.gapminder().query("country=='Canada'")
fig1 = px.line(gapminder, x="year", y="lifeExp", title='Life expectancy in Canada')
gapminder = px.data.gapminder().query("continent=='Oceania'")
fig2 = px.line(gapminder, x="year", y="lifeExp", color='country')
gapminder = px.data.gapminder().query("continent != 'Asia'")
fig3 = px.line(gapminder, x="year", y="lifeExp", color="continent",
               line_group="country", hover_name="country")

figures_to_html([fig1, fig2, fig3])

12
投票

您可以获得一个仪表板，其中包含多个图表，每个图表旁边都有图例：

import plotly
import plotly.offline as py
import plotly.graph_objs as go
fichier_html_graphs=open("DASHBOARD.html",'w')
fichier_html_graphs.write("<html><head></head><body>"+"\n")

i=0
while 1:
    if i<=40:
        i=i+1


        #______________________________--Plotly--______________________________________


        color1 = '#00bfff'
        color2 = '#ff4000'

        trace1 = go.Bar(
            x = ['2017-09-25','2017-09-26','2017-09-27','2017-09-28','2017-09-29','2017-09-30','2017-10-01'],
            y = [25,100,20,7,38,170,200],
            name='Debit',
            marker=dict(
                color=color1
            )

        )
        trace2 = go.Scatter(

            x=['2017-09-25','2017-09-26','2017-09-27','2017-09-28','2017-09-29','2017-09-30','2017-10-01'],
            y = [3,50,20,7,38,60,100],
            name='Taux',
            yaxis='y2'

        )
        data = [trace1, trace2]
        layout = go.Layout(
            title= ('Chart Number: '+str(i)),
            titlefont=dict(
            family='Courier New, monospace',
            size=15,
            color='#7f7f7f'
            ),
            paper_bgcolor='rgba(0,0,0,0)',
            plot_bgcolor='rgba(0,0,0,0)',

            yaxis=dict(
                title='Bandwidth Mbit/s',
                titlefont=dict(
                    color=color1
                ),
                tickfont=dict(
                    color=color1
                )
            ),
            yaxis2=dict(
                title='Ratio %',
                overlaying='y',
                side='right',
                titlefont=dict(
                    color=color2
                ),
                tickfont=dict(
                    color=color2
                )

            )

        )
        fig = go.Figure(data=data, layout=layout)
        plotly.offline.plot(fig, filename='Chart_'+str(i)+'.html',auto_open=False)
        fichier_html_graphs.write("  <object data=\""+'Chart_'+str(i)+'.html'+"\" width=\"650\" height=\"500\"></object>"+"\n")
    else:
        break


fichier_html_graphs.write("</body></html>")
print("CHECK YOUR DASHBOARD.html In the current directory")

结果：

9
投票

您还可以使用袖扣尝试以下方法：

cf.subplots([df1.figure(kind='bar',categories='category'),
         df2.figure(kind='bar',categories='category')],shape=(2,1)).iplot()

这应该给你：

5
投票

新答案：

我们需要遍历每只动物并附加一条新的轨迹来生成你需要的东西。这将提供我希望的所需输出。

import pandas as pd
import numpy as np
import cufflinks as cf
import plotly.tools as tls
from plotly.offline import download_plotlyjs, plot,iplot
cf.go_offline()
import random

def generate_random_color():
    r = lambda: random.randint(0,255)
    return '#%02X%02X%02X' % (r(),r(),r())

a={'catagory':['loc1','loc2','loc3'],'dogs':[1,5,6],'cats':[3,1,4],'birds':[4,12,2]}
df1 = pd.DataFrame(a)
b={'catagory':['loc1','loc2','loc3'],'dogs':[12,3,5],'cats':[4,6,1],'birds':[7,0,8]}
df2 = pd.DataFrame(b)

#shared Xaxis parameter can make this graph look even better
fig = tls.make_subplots(rows=2, cols=1)

for animal in ['dogs','cats','birds']: 
    animal_color = generate_random_color()
    fig1 = df1.iplot(kind='bar',barmode='stack',x='catagory',
                       y=animal,asFigure=True,showlegend=False, color = animal_color)
    fig.append_trace(fig1['data'][0], 1, 1)

    fig2 = df2.iplot(kind='bar',barmode='stack',x='catagory',
                       y=animal,asFigure=True, showlegend=False, color = animal_color)
    #if we do not use the below line there will be two legend
    fig2['data'][0]['showlegend'] = False

    fig.append_trace(fig2['data'][0], 2, 1)
    #additional bonus
    #use the below command to use the bar chart three mode
    # [stack, overlay, group]
    #as shown below
    #fig['layout']['barmode'] = 'overlay'
iplot(fig)

输出：

旧答案：

这将是解决方案

说明：

Plotly 工具具有创建子图的子图功能，您应该阅读文档了解更多详情here。所以我先用袖扣制作了一张图的条形图。需要注意的一件事是袖扣创建并同时包含数据和布局。 Plotly 只会将一个布局参数作为输入，因此我只从袖扣图中获取数据参数并将其追加到 make_suplots 对象。所以 fig.append_trace() 第二个参数是行号，第三个参数是列号

import pandas as pd
import cufflinks as cf
import numpy as np
import plotly.tools as tls
from plotly.offline import download_plotlyjs, plot,iplot
cf.go_offline()

fig = tls.make_subplots(rows=2, cols=1)

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
fig1 = df.iplot(kind='bar',barmode='stack',x='A',
                       y='B',asFigure=True)
fig.append_trace(fig1['data'][0], 1, 1)
df2 = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('EFGH'))
fig2 = df2.iplot(kind='bar',barmode='stack',x='E',
                       y='F',asFigure=True)
fig.append_trace(fig2['data'][0], 2, 1)
iplot(fig)

如果你想在子图中添加一个通用布局，我建议你这样做 

fig.append_trace(fig2['data'][0], 2, 1)
fig['layout']['showlegend'] = False
iplot(fig)

甚至

fig.append_trace(fig2['data'][0], 2, 1)
fig['layout'].update(fig1['layout'])
iplot(fig)

所以在绘图之前的第一个示例中，我访问了布局对象的各个参数并更改了它们，您需要通过布局对象属性进行参考。

在绘图之前的第二个示例中，我使用袖扣生成的布局更新图形的布局，这将产生与我们在袖扣中看到的相同的输出。

4
投票

您已经收到了一些非常有效的建议。然而，它们确实需要大量编码。 Facet / trellis plots using 

px.bar()
will let you produce the plot below using (almost) only this:

px.bar(df, x="category", y="dogs", facet_row="Source")

您唯一需要采取的额外步骤是引入一个变量来拆分数据，然后像这样收集或连接数据帧：

df1['Source'] = 1
df2['Source'] = 2
df = pd.concat([df1, df2])

如果您还想包括其他变量，只需执行以下操作：

fig = px.bar(df, x="category", y=["dogs", "cats", "birds"], facet_row="Source")
fig.update_layout(barmode = 'group')

完整代码：

# imports
import plotly.express as px
import pandas as pd

# data building
a={'category':['loc1','loc2','loc3'],'dogs':[1,5,6],'cats':[3,1,4],'birds':[4,12,2]}
df1 = pd.DataFrame(a)
b={'category':['loc1','loc2','loc3'],'dogs':[12,3,5],'cats':[4,6,1],'birds':[7,0,8]}
df2 = pd.DataFrame(b)

# data processing 
df1['Source'] = 1
df2['Source'] = 2
df = pd.concat([df1, df2])

# plotly figure
fig = px.bar(df, x="category", y="dogs", facet_row="Source")
fig.show()

#fig = px.bar(df, x="category", y=["dogs", "cats", "birds"], facet_row="Source")
#fig.update_layout(barmode = 'group')
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