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Python Plotly: Sharing x-axis and making subplots by group

I am trying to have two subplots share the x-axis and have them separated out by Type which would look something like this below:

image

FYI

  • I made two dataframes A_df and B_df by 'Type' to give you an idea of what I want to do, but you're welcome to use final_df!
  • I colored weekend as grey for a reason and would like to keep them.

Here's the reproducible code:

rng = pd.date_range('2022-04-09', periods=20, freq='D')
first_df = pd.DataFrame({ 'Date': rng, 'Val' : np.random.randn(len(rng))}) 
first_df['Type'] = 'A'

second_df = pd.DataFrame({ 'Date': rng, 'Val' : np.random.randn(len(rng))}) 
second_df['Type'] = 'B'

final_df =  pd.concat([first_df,second_df]).sort_values(by = 'Date')
final_df['Is_Weekend'] = np.where((final_df['Date'].dt.weekday == 5), 1, 0 )

A_df = final_df[final_df['Type']=='A']
B_df = final_df[final_df['Type']=='B']

fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(go.Scatter(x=A_df['Date'], y=A_df['Is_Weekend'],
                         fill = 'tonexty', fillcolor = 'rgba(128,128,128, 0.2)',
                         line_shape = 'hv', line_color = 'rgba(0,0,0,0)',
                         showlegend = False
                        ),
              row = 1, col = 1, secondary_y=True)

fig.update_xaxes(showgrid=False)
fig.update_layout(yaxis2_range=[-0,0.1], yaxis2_showgrid=False,  yaxis2_tickfont_color = 'rgba(0,0,0,0)')
fig.add_trace(go.Scatter(x=A_df['Date'], 
                         y = A_df['Val'], 
                         line_color = 'orange',
                         mode = 'lines+markers',
                         showlegend = False),
              secondary_y = False)

fig.show()

fig2 = make_subplots(specs=[[{"secondary_y": True}]])
fig2.add_trace(go.Scatter(x=B_df['Date'], y=B_df['Is_Weekend'],
                         fill = 'tonexty', fillcolor = 'rgba(128,128,128, 0.2)',
                         line_shape = 'hv', line_color = 'rgba(0,0,0,0)',
                         showlegend = False
                        ),
              row = 1, col = 1, secondary_y=True)

fig2.update_xaxes(showgrid=False)
fig2.update_layout(yaxis2_range=[-0,0.1], yaxis2_showgrid=False,  yaxis2_tickfont_color = 'rgba(0,0,0,0)')
fig2.add_trace(go.Scatter(x=B_df['Date'], 
                         y = B_df['Val'], 
                         line_color = 'blue',
                         mode = 'lines+markers',
                         showlegend = False),
              secondary_y = False)

fig2.show()

Edit:

How to change the order to legends?

legend_img

Solution

  • If you want to combine both figures into one figure with subplots and a shared xaxis, you can define your figure the following way:

    fig = make_subplots(rows=2, cols=1,
                    shared_xaxes=True,
                    specs=[[{"secondary_y": True}],[{"secondary_y": True}]])

    Then when you add traces and update the layout(s), you can use the appropriate row and col parameters.

    For example:

    import numpy as np
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots 

rng = pd.date_range('2022-04-09', periods=20, freq='D')
np.random.seed(42)
first_df = pd.DataFrame({ 'Date': rng, 'Val' : np.random.randn(len(rng))}) 
first_df['Type'] = 'A'

second_df = pd.DataFrame({ 'Date': rng, 'Val' : np.random.randn(len(rng))}) 
second_df['Type'] = 'B'

final_df =  pd.concat([first_df,second_df]).sort_values(by = 'Date')
final_df['Is_Weekend'] = np.where((final_df['Date'].dt.weekday == 5), 1, 0 )

A_df = final_df[final_df['Type']=='A']
B_df = final_df[final_df['Type']=='B']

fig = make_subplots(rows=2, cols=1,
                    shared_xaxes=True,
                    specs=[[{"secondary_y": True}],[{"secondary_y": True}]])
fig.add_trace(go.Scatter(x=A_df['Date'], y=A_df['Is_Weekend'],
                         fill = 'tonexty', fillcolor = 'rgba(128,128,128, 0.2)',
                         line_shape = 'hv', line_color = 'rgba(0,0,0,0)',
                         showlegend = False
                        ),
              row = 1, col = 1, secondary_y=True)

fig.update_xaxes(showgrid=False, row=1, col=1)
fig.update_yaxes(range=[-0,0.1], showgrid=False, tickfont_color = 'rgba(0,0,0,0)', secondary_y=True, row=1, col=1)
fig.add_trace(go.Scatter(x=A_df['Date'], 
                         y = A_df['Val'], 
                         line_color = 'orange',
                         mode = 'lines+markers',
                         showlegend = False),
              row=1, col=1,
              secondary_y = False)

fig.add_trace(go.Scatter(x=B_df['Date'], y=B_df['Is_Weekend'],
                         fill = 'tonexty', fillcolor = 'rgba(128,128,128, 0.2)',
                         line_shape = 'hv', line_color = 'rgba(0,0,0,0)',
                         showlegend = False
                        ),
              row=2, col=1, secondary_y=True)

fig.update_xaxes(showgrid=False, row=2, col=1)
fig.update_yaxes(range=[-0,0.1], showgrid=False,  tickfont_color = 'rgba(0,0,0,0)', secondary_y=True, row=2, col=1)
fig.add_trace(go.Scatter(x=B_df['Date'], 
                         y = B_df['Val'], 
                         line_color = 'blue',
                         mode = 'lines+markers',
                         showlegend = False),
              row=2, col=1,
              secondary_y = False)

fig.show()

    enter image description here