Layering multiple plots

Introduction to Data Visualization with Plotly in Python

Alex Scriven

Data Scientist

What is plot layering?

Overlaying several plots within the same plot

GDP layered plot

No separate grid positions
Use add_trace()

No separate grid positions
Use add_trace()

Why layer plots?

Accessing more customization
- Example: layering multiple line graphs

Displaying complementary plot types

Using different plot types to direct attention

Comparing data closely

Bar + line layered plot

Allows to compare exact values and the overall trend in one view

Layered plot example

GDP growth layered plot

from plotly.graph_objects import Figure

layered_fig = Figure()

bar_fig = px.bar(df, x='Date'
      , y='Quarterly Growth (%)')

line_fig = px.line(df, x='Date'
      , y='Rolling YTD Growth (%)'
      , color_discrete_sequence=['red'])

layered_fig = Figure(data=
   [*bar_fig.data, *line_fig.data])
layered_fig.show()

GDP layered plot

Adding more plots

# Code the same bar_fig, line_fig
line_fig2 = px.line(df, x='Date'
    , y='OECD Average GDP Growth (%)'
    , color_discrete_sequence=['green'])

layered_fig = Figure(data=
   [*bar_fig.data
    , *line_fig.data, *line_fig2.data])
layered_fig.show()

GDP layered plot

Adding more plots later

# Create with 2 figures
layered_fig = Figure(data=[*bar_fig.data, *line_fig.data])

# Add last line
layered_fig.add_trace(line_fig2.data[0])

Let's practice!

Introduction to Data Visualization with Plotly in Python