CODEWITHSUNDEEP
pythonplotlyplotly-python
sparrow
sparrow

Reputation: 11460

Plot multiple figures as subplots

These resources show how to take data from a single Pandas DataFrame and plot different columns subplots on a Plotly graph. I'm interested in creating figures from separate DataFrames and plotting them to the same graph as subplots. Is this possible with Plotly?

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

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

I'm creating each figure from a dataframe like this:

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)

Edit: Here is an example based on Naren's feedback:

Create the dataframes:

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)

The plot will just show the information for the dogs, not the birds or cats:

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)

Just the dogs are shown, not the cats or birds:

Upvotes: 31

Views: 86693

Answers (5)

pyjamas
pyjamas

Reputation: 5357

Here's a short function in a working example to save a list of figures all to a single HTML file.

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])

enter image description here

Upvotes: 32

vestland
vestland

Reputation: 61104

You've already received a few suggestions that work perfectly well. They do however require a lot of coding. 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")

enter image description here

The only extra steps you'll have to take is to introduce a variable on which to split your data, and then gather or concatenate your dataframes like this:

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

And if you'd like to include the other variables as well, just do:

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

enter image description here

Complete code:

# 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')

Upvotes: 4

belkacem mekakleb
belkacem mekakleb

Reputation: 604

You can get a dashboard that contains several charts with legends next to each one:

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")

Result:

enter image description here

Upvotes: 13

jorge.santos
jorge.santos

Reputation: 301

You can also try the following using cufflinks:

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

And this should give you:

Upvotes: 9

Naren Murali
Naren Murali

Reputation: 56054

New Answer:

We need to loop through each of the animals and append a new trace to generate what you need. This will give the desired output I am hoping.

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)

Output: stacked subplot bar chart

Old Answer:

This will be the solution

Explanation:

Plotly tools has a subplot function to create subplots you should read the documentation for more details here. So I first use cufflinks to create a figure of the bar chart. One thing to note is cufflinks create and object with both data and layout. Plotly will only take one layout parameter as input, hence I take only the data parameter from the cufflinks figure and append_trace it to the make_suplots object. so fig.append_trace() the second parameter is row number and third parameter is column number

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)

If you want to add a common layout to the subplot I suggest that you do 

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

or even

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

So in the first example before plotting, I access the individual parameters of the layout object and change them, you need to go through layout object properties for refernce.

In the second example before plotting, I update the layout of the figure with the cufflinks generated layout this will produce the same output as we see in cufflinks.

Upvotes: 5

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