Subplots in Python

How to make subplots in with Plotly's Python graphing library. Examples of stacked, custom-sized, gridded, and annotated subplots.

New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Subplots and Plotly Express¶

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Plotly Express does not support arbitrary subplot capabilities, instead it supports faceting by a given data dimension, and it also supports marginal charts to display distribution information.

This page documents the usage of the lower-level plotly.subplots module and the make_subplots function it exposes to construct figures with arbitrary subplots. Plotly Express faceting uses make_subplots internally so adding traces to Plotly Express facets works just as documented here, with fig.add_trace(..., row=<R>, col=<C>).

Simple Subplot¶

Figures with subplots are created using the make_subplots function from the plotly.subplots module.

Here is an example of creating a figure that includes two scatter traces which are side-by-side since there are 2 columns and 1 row in the subplot layout.

In [1]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

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

fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[4, 5, 6]),
    row=1, col=1
)

fig.add_trace(
    go.Scatter(x=[20, 30, 40], y=[50, 60, 70]),
    row=1, col=2
)

fig.update_layout(height=600, width=800, title_text="Side By Side Subplots")
fig.show()

Stacked Subplots¶

Here is an example of creating a figure with subplots that are stacked on top of each other since there are 3 rows and 1 column in the subplot layout.

In [2]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(rows=3, cols=1)

fig.append_trace(go.Scatter(
    x=[3, 4, 5],
    y=[1000, 1100, 1200],
), row=1, col=1)

fig.append_trace(go.Scatter(
    x=[2, 3, 4],
    y=[100, 110, 120],
), row=2, col=1)

fig.append_trace(go.Scatter(
    x=[0, 1, 2],
    y=[10, 11, 12]
), row=3, col=1)


fig.update_layout(height=600, width=600, title_text="Stacked Subplots")
fig.show()

Multiple Subplots¶

Here is an example of creating a 2 x 2 subplot grid and populating each subplot with a single scatter trace.

In [3]:

import plotly.graph_objects as go
from plotly.subplots import make_subplots

fig = make_subplots(rows=2, cols=2, start_cell="bottom-left")

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]),
              row=1, col=1)

fig.add_trace(go.Scatter(x=[20, 30, 40], y=[50, 60, 70]),
              row=1, col=2)

fig.add_trace(go.Scatter(x=[300, 400, 500], y=[600, 700, 800]),
              row=2, col=1)

fig.add_trace(go.Scatter(x=[4000, 5000, 6000], y=[7000, 8000, 9000]),
              row=2, col=2)

fig.show()

Multiple Subplots with Titles¶

The subplot_titles argument to make_subplots can be used to position text annotations as titles for each subplot.

Here is an example of adding subplot titles to a 2 x 2 subplot grid of scatter traces.

In [4]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=2, cols=2,
    subplot_titles=("Plot 1", "Plot 2", "Plot 3", "Plot 4"))

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]),
              row=1, col=1)

fig.add_trace(go.Scatter(x=[20, 30, 40], y=[50, 60, 70]),
              row=1, col=2)

fig.add_trace(go.Scatter(x=[300, 400, 500], y=[600, 700, 800]),
              row=2, col=1)

fig.add_trace(go.Scatter(x=[4000, 5000, 6000], y=[7000, 8000, 9000]),
              row=2, col=2)

fig.update_layout(height=500, width=700,
                  title_text="Multiple Subplots with Titles")

fig.show()

Subplots with Annotations¶

In [5]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

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

fig.add_trace(
    go.Scatter(
        x=[1, 2, 3],
        y=[4, 5, 6],
        mode="markers+text",
        text=["Text A", "Text B", "Text C"],
        textposition="bottom center"
    ),
    row=1, col=1
)

fig.add_trace(
    go.Scatter(
        x=[20, 30, 40],
        y=[50, 60, 70],
        mode="markers+text",
        text=["Text D", "Text E", "Text F"],
        textposition="bottom center"
    ),
    row=1, col=2
)

fig.update_layout(height=600, width=800, title_text="Subplots with Annotations")

fig.show()

Customize Subplot Column Widths and Row Heights¶

The column_widths argument to make_subplots can be used to customize the relative widths of the columns in a subplot grid. It should be set to a list of numbers with a length that matches the cols argument. These number will be normalized, so that they sum to 1, and used to compute the relative widths of the subplot grid columns. The row_heights argument serves the same purpose for controlling the relative heights of rows in the subplot grid.

Here is an example of creating a figure with two scatter traces in side-by-side subplots. The left subplot is set to be wider than the right one.

In [6]:

import plotly.graph_objects as go
from plotly.subplots import make_subplots

fig = make_subplots(rows=1, cols=2, column_widths=[0.7, 0.3])

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]),
              row=1, col=1)

fig.add_trace(go.Scatter(x=[20, 30, 40], y=[50, 60, 70]),
              row=1, col=2)

fig.show()

Subplots in Dash¶

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.

Out[7]:

Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.

Customizing Subplot Axes¶

After a figure with subplots is created using the make_subplots function, its axis properties (title, font, range, grid style, etc.) can be customized using the update_xaxes and update_yaxes graph object figure methods. By default, these methods apply to all of the x axes or y axes in the figure. The row and col arguments can be used to control which axes are targeted by the update.

Here is an example that creates a figure with a 2 x 2 subplot grid, populates each subplot with a scatter trace, and then updates the x and y axis titles for each subplot individually.

In [8]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

# Initialize figure with subplots
fig = make_subplots(
    rows=2, cols=2, subplot_titles=("Plot 1", "Plot 2", "Plot 3", "Plot 4")
)

# Add traces
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]), row=1, col=1)
fig.add_trace(go.Scatter(x=[20, 30, 40], y=[50, 60, 70]), row=1, col=2)
fig.add_trace(go.Scatter(x=[300, 400, 500], y=[600, 700, 800]), row=2, col=1)
fig.add_trace(go.Scatter(x=[4000, 5000, 6000], y=[7000, 8000, 9000]), row=2, col=2)

# Update xaxis properties
fig.update_xaxes(title_text="xaxis 1 title", row=1, col=1)
fig.update_xaxes(title_text="xaxis 2 title", range=[10, 50], row=1, col=2)
fig.update_xaxes(title_text="xaxis 3 title", showgrid=False, row=2, col=1)
fig.update_xaxes(title_text="xaxis 4 title", type="log", row=2, col=2)

# Update yaxis properties
fig.update_yaxes(title_text="yaxis 1 title", row=1, col=1)
fig.update_yaxes(title_text="yaxis 2 title", range=[40, 80], row=1, col=2)
fig.update_yaxes(title_text="yaxis 3 title", showgrid=False, row=2, col=1)
fig.update_yaxes(title_text="yaxis 4 title", row=2, col=2)

# Update title and height
fig.update_layout(title_text="Customizing Subplot Axes", height=700)

fig.show()

Subplots with Shared X-Axes¶

The shared_xaxes argument to make_subplots can be used to link the x axes of subplots in the resulting figure. The vertical_spacing argument is used to control the vertical spacing between rows in the subplot grid.

Here is an example that creates a figure with 3 vertically stacked subplots with linked x axes. A small vertical spacing value is used to reduce the spacing between subplot rows.

In [9]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(rows=3, cols=1,
                    shared_xaxes=True,
                    vertical_spacing=0.02)

fig.add_trace(go.Scatter(x=[0, 1, 2], y=[10, 11, 12]),
              row=3, col=1)

fig.add_trace(go.Scatter(x=[2, 3, 4], y=[100, 110, 120]),
              row=2, col=1)

fig.add_trace(go.Scatter(x=[3, 4, 5], y=[1000, 1100, 1200]),
              row=1, col=1)

fig.update_layout(height=600, width=600,
                  title_text="Stacked Subplots with Shared X-Axes")
fig.show()

Subplots with Shared Y-Axes¶

The shared_yaxes argument to make_subplots can be used to link the y axes of subplots in the resulting figure.

Here is an example that creates a figure with a 2 x 2 subplot grid, where the y axes of each row are linked.

In [10]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(rows=2, cols=2, shared_yaxes=True)

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[2, 3, 4]),
              row=1, col=1)

fig.add_trace(go.Scatter(x=[20, 30, 40], y=[5, 5, 5]),
              row=1, col=2)

fig.add_trace(go.Scatter(x=[2, 3, 4], y=[600, 700, 800]),
              row=2, col=1)

fig.add_trace(go.Scatter(x=[4000, 5000, 6000], y=[7000, 8000, 9000]),
              row=2, col=2)

fig.update_layout(height=600, width=600,
                  title_text="Multiple Subplots with Shared Y-Axes")
fig.show()

Subplots with Shared Colorscale¶

To share colorscale information in multiple subplots, you can use coloraxis.

In [11]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(rows=1, cols=2, shared_yaxes=True)

fig.add_trace(go.Bar(x=[1, 2, 3], y=[4, 5, 6],
                    marker=dict(color=[4, 5, 6], coloraxis="coloraxis")),
              1, 1)

fig.add_trace(go.Bar(x=[1, 2, 3], y=[2, 3, 5],
                    marker=dict(color=[2, 3, 5], coloraxis="coloraxis")),
              1, 2)

fig.update_layout(coloraxis=dict(colorscale='Bluered_r'), showlegend=False)
fig.show()

Custom Sized Subplot with Subplot Titles¶

The specs argument to make_subplots is used to configure per-subplot options. specs must be a 2-dimension list with dimensions that match those provided as the rows and cols arguments. The elements of specs may either be None, indicating no subplot should be initialized starting with this grid cell, or a dictionary containing subplot options. The colspan subplot option specifies the number of grid columns that the subplot starting in the given cell should occupy. If unspecified, colspan defaults to 1.

Here is an example that creates a 2 by 2 subplot grid containing 3 subplots. The subplot specs element for position (2, 1) has a colspan value of 2, causing it to span the full figure width. The subplot specs element for position (2, 2) is None because no subplot begins at this location in the grid.

In [12]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=2, cols=2,
    specs=[[{}, {}],
           [{"colspan": 2}, None]],
    subplot_titles=("First Subplot","Second Subplot", "Third Subplot"))

fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2]),
                 row=1, col=1)

fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2]),
                 row=1, col=2)
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[2, 1, 2]),
                 row=2, col=1)

fig.update_layout(showlegend=False, title_text="Specs with Subplot Title")
fig.show()

Multiple Custom Sized Subplots¶

If the print_grid argument to make_subplots is set to True, then a text representation of the subplot grid will be printed.

Here is an example that uses the rowspan and colspan subplot options to create a custom subplot layout with subplots of mixed sizes. The print_grid argument is set to True so that the subplot grid is printed to the screen.

In [13]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=5, cols=2,
    specs=[[{}, {"rowspan": 2}],
           [{}, None],
           [{"rowspan": 2, "colspan": 2}, None],
           [None, None],
           [{}, {}]],
    print_grid=True)

fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(1,1)"), row=1, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(1,2)"), row=1, col=2)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(2,1)"), row=2, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(3,1)"), row=3, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(5,1)"), row=5, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(5,2)"), row=5, col=2)

fig.update_layout(height=600, width=600, title_text="specs examples")
fig.show()

This is the format of your plot grid:
[ (1,1) x,y   ]  ⎡ (1,2) x2,y2 ⎤
[ (2,1) x3,y3 ]  ⎣      :      ⎦
⎡ (3,1) x4,y4           -      ⎤
⎣      :                :      ⎦
[ (5,1) x5,y5 ]  [ (5,2) x6,y6 ]

Subplots Types¶

By default, the make_subplots function assumes that the traces that will be added to all subplots are 2-dimensional cartesian traces (e.g. scatter, bar, histogram, violin, etc.). Traces with other subplot types (e.g. scatterpolar, scattergeo, parcoords, etc.) are supported by specifying the type subplot option in the specs argument to make_subplots.

Here are the possible values for the type option:

"xy": 2D Cartesian subplot type for scatter, bar, etc. This is the default if no type is specified.
"scene": 3D Cartesian subplot for scatter3d, cone, etc.
"polar": Polar subplot for scatterpolar, barpolar, etc.
"ternary": Ternary subplot for scatterternary.
"mapbox": Mapbox subplot for scattermapbox.
"domain": Subplot type for traces that are individually positioned. pie, parcoords, parcats, etc.
trace type: A trace type name (e.g. "bar", "scattergeo", "carpet", "mesh", etc.) which will be used to determine the appropriate subplot type for that trace.

Here is an example that creates and populates a 2 x 2 subplot grid containing 4 different subplot types.

In [14]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=2, cols=2,
    specs=[[{"type": "xy"}, {"type": "polar"}],
           [{"type": "domain"}, {"type": "scene"}]],
)

fig.add_trace(go.Bar(y=[2, 3, 1]),
              row=1, col=1)

fig.add_trace(go.Barpolar(theta=[0, 45, 90], r=[2, 3, 1]),
              row=1, col=2)

fig.add_trace(go.Pie(values=[2, 3, 1]),
              row=2, col=1)

fig.add_trace(go.Scatter3d(x=[2, 3, 1], y=[0, 0, 0],
                           z=[0.5, 1, 2], mode="lines"),
              row=2, col=2)

fig.update_layout(height=700, showlegend=False)

fig.show()

As an alternative to providing the name of a subplot type (e.g. "xy", "polar", "domain", "scene", etc), the type option may also be set to a string containing the name of a trace type (e.g. "bar", "barpolar", "pie", "scatter3d", etc.), which will be used to determine the subplot type that is compatible with that trace.

Here is the example above, modified to specify the subplot types using trace type names.

In [15]:

from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=2, cols=2,
    specs=[[{"type": "bar"}, {"type": "barpolar"}],
           [{"type": "pie"}, {"type": "scatter3d"}]],
)

fig.add_trace(go.Bar(y=[2, 3, 1]),
              row=1, col=1)

fig.add_trace(go.Barpolar(theta=[0, 45, 90], r=[2, 3, 1]),
              row=1, col=2)

fig.add_trace(go.Pie(values=[2, 3, 1]),
              row=2, col=1)

fig.add_trace(go.Scatter3d(x=[2, 3, 1], y=[0, 0, 0],
                           z=[0.5, 1, 2], mode="lines"),
              row=2, col=2)

fig.update_layout(height=700, showlegend=False)

fig.show()

Side by Side Subplot (low-level API)¶

In [16]:

import plotly.graph_objects as go

trace1 = go.Scatter(
    x=[1, 2, 3],
    y=[4, 5, 6]
)
trace2 = go.Scatter(
    x=[20, 30, 40],
    y=[50, 60, 70],
    xaxis="x2",
    yaxis="y2"
)
data = [trace1, trace2]
layout = go.Layout(
    xaxis=dict(
        domain=[0, 0.7]
    ),
    xaxis2=dict(
        domain=[0.8, 1]
    ),
    yaxis2=dict(
        anchor="x2"
    )
)
fig = go.Figure(data=data, layout=layout)
fig.show()

Subplots with shared axes (low-level API)¶

In [17]:

import plotly.graph_objects as go

trace1 = go.Scatter(
    x=[1, 2, 3],
    y=[2, 3, 4]
)
trace2 = go.Scatter(
    x=[20, 30, 40],
    y=[5, 5, 5],
    xaxis="x2",
    yaxis="y"
)
trace3 = go.Scatter(
    x=[2, 3, 4],
    y=[600, 700, 800],
    xaxis="x",
    yaxis="y3"
)
trace4 = go.Scatter(
    x=[4000, 5000, 6000],
    y=[7000, 8000, 9000],
    xaxis="x4",
    yaxis="y4"
)
data = [trace1, trace2, trace3, trace4]
layout = go.Layout(
    xaxis=dict(
        domain=[0, 0.45]
    ),
    yaxis=dict(
        domain=[0, 0.45]
    ),
    xaxis2=dict(
        domain=[0.55, 1]
    ),
    xaxis4=dict(
        domain=[0.55, 1],
        anchor="y4"
    ),
    yaxis3=dict(
        domain=[0.55, 1]
    ),
    yaxis4=dict(
        domain=[0.55, 1],
        anchor="x4"
    )
)
fig = go.Figure(data=data, layout=layout)
fig.show()

Stacked Subplots with a Shared X-Axis (low-level API)¶

In [18]:

import plotly.graph_objects as go

trace1 = go.Scatter(
    x=[0, 1, 2],
    y=[10, 11, 12]
)
trace2 = go.Scatter(
    x=[2, 3, 4],
    y=[100, 110, 120],
    yaxis="y2"
)
trace3 = go.Scatter(
    x=[3, 4, 5],
    y=[1000, 1100, 1200],
    yaxis="y3"
)
data = [trace1, trace2, trace3]
layout = go.Layout(
    yaxis=dict(
        domain=[0, 0.33]
    ),
    legend=dict(
        traceorder="reversed"
    ),
    yaxis2=dict(
        domain=[0.33, 0.66]
    ),
    yaxis3=dict(
        domain=[0.66, 1]
    )
)
fig = go.Figure(data=data, layout=layout)
fig.show()

Setting Subplots on a Figure Directly¶

new in 4.13

Subplots can be added to an already existing figure, provided it doesn't already have subplots. go.Figure.set_subplots accepts all the same arguments as plotly.subplots.make_subplots.

In [19]:

import plotly.graph_objects as go
fig = go.Figure().set_subplots(2, 3, horizontal_spacing=0.1)

is equivalent to:

In [20]:

from plotly.subplots import make_subplots
fig = make_subplots(2, 3, horizontal_spacing=0.1)

Reference¶

All of the x-axis properties are found here: https://plotly.com/python/reference/XAxis/ All of the y-axis properties are found here: https://plotly.com/python/reference/YAxis/

In [21]:

from plotly.subplots import make_subplots
help(make_subplots)

Help on function make_subplots in module plotly.subplots:

make_subplots(rows=1, cols=1, shared_xaxes=False, shared_yaxes=False, start_cell='top-left', print_grid=False, horizontal_spacing=None, vertical_spacing=None, subplot_titles=None, column_widths=None, row_heights=None, specs=None, insets=None, column_titles=None, row_titles=None, x_title=None, y_title=None, figure=None, **kwargs) -> plotly.graph_objs._figure.Figure
    Return an instance of plotly.graph_objs.Figure with predefined subplots
    configured in 'layout'.
    
    Parameters
    ----------
    rows: int (default 1)
        Number of rows in the subplot grid. Must be greater than zero.
    
    cols: int (default 1)
        Number of columns in the subplot grid. Must be greater than zero.
    
    shared_xaxes: boolean or str (default False)
        Assign shared (linked) x-axes for 2D cartesian subplots
    
          - True or 'columns': Share axes among subplots in the same column
          - 'rows': Share axes among subplots in the same row
          - 'all': Share axes across all subplots in the grid.
    
    shared_yaxes: boolean or str (default False)
        Assign shared (linked) y-axes for 2D cartesian subplots
    
          - 'columns': Share axes among subplots in the same column
          - True or 'rows': Share axes among subplots in the same row
          - 'all': Share axes across all subplots in the grid.
    
    start_cell: 'bottom-left' or 'top-left' (default 'top-left')
        Choose the starting cell in the subplot grid used to set the
        domains_grid of the subplots.
    
          - 'top-left': Subplots are numbered with (1, 1) in the top
                        left corner
          - 'bottom-left': Subplots are numbererd with (1, 1) in the bottom
                           left corner
    
    print_grid: boolean (default True):
        If True, prints a string representation of the plot grid.  Grid may
        also be printed using the `Figure.print_grid()` method on the
        resulting figure.
    
    horizontal_spacing: float (default 0.2 / cols)
        Space between subplot columns in normalized plot coordinates. Must be
        a float between 0 and 1.
    
        Applies to all columns (use 'specs' subplot-dependents spacing)
    
    vertical_spacing: float (default 0.3 / rows)
        Space between subplot rows in normalized plot coordinates. Must be
        a float between 0 and 1.
    
        Applies to all rows (use 'specs' subplot-dependents spacing)
    
    subplot_titles: list of str or None (default None)
        Title of each subplot as a list in row-major ordering.
    
        Empty strings ("") can be included in the list if no subplot title
        is desired in that space so that the titles are properly indexed.
    
    specs: list of lists of dict or None (default None)
        Per subplot specifications of subplot type, row/column spanning, and
        spacing.
    
        ex1: specs=[[{}, {}], [{'colspan': 2}, None]]
    
        ex2: specs=[[{'rowspan': 2}, {}], [None, {}]]
    
        - Indices of the outer list correspond to subplot grid rows
          starting from the top, if start_cell='top-left',
          or bottom, if start_cell='bottom-left'.
          The number of rows in 'specs' must be equal to 'rows'.
    
        - Indices of the inner lists correspond to subplot grid columns
          starting from the left. The number of columns in 'specs'
          must be equal to 'cols'.
    
        - Each item in the 'specs' list corresponds to one subplot
          in a subplot grid. (N.B. The subplot grid has exactly 'rows'
          times 'cols' cells.)
    
        - Use None for a blank a subplot cell (or to move past a col/row span).
    
        - Note that specs[0][0] has the specs of the 'start_cell' subplot.
    
        - Each item in 'specs' is a dictionary.
            The available keys are:
            * type (string, default 'xy'): Subplot type. One of
                - 'xy': 2D Cartesian subplot type for scatter, bar, etc.
                - 'scene': 3D Cartesian subplot for scatter3d, cone, etc.
                - 'polar': Polar subplot for scatterpolar, barpolar, etc.
                - 'ternary': Ternary subplot for scatterternary
                - 'mapbox': Mapbox subplot for scattermapbox
                - 'domain': Subplot type for traces that are individually
                            positioned. pie, parcoords, parcats, etc.
                - trace type: A trace type which will be used to determine
                              the appropriate subplot type for that trace
    
            * secondary_y (bool, default False): If True, create a secondary
                y-axis positioned on the right side of the subplot. Only valid
                if type='xy'.
            * colspan (int, default 1): number of subplot columns
                for this subplot to span.
            * rowspan (int, default 1): number of subplot rows
                for this subplot to span.
            * l (float, default 0.0): padding left of cell
            * r (float, default 0.0): padding right of cell
            * t (float, default 0.0): padding right of cell
            * b (float, default 0.0): padding bottom of cell
    
        - Note: Use 'horizontal_spacing' and 'vertical_spacing' to adjust
          the spacing in between the subplots.
    
    insets: list of dict or None (default None):
        Inset specifications.  Insets are subplots that overlay grid subplots
    
        - Each item in 'insets' is a dictionary.
            The available keys are:
    
            * cell (tuple, default=(1,1)): (row, col) index of the
                subplot cell to overlay inset axes onto.
            * type (string, default 'xy'): Subplot type
            * l (float, default=0.0): padding left of inset
                  in fraction of cell width
            * w (float or 'to_end', default='to_end') inset width
                  in fraction of cell width ('to_end': to cell right edge)
            * b (float, default=0.0): padding bottom of inset
                  in fraction of cell height
            * h (float or 'to_end', default='to_end') inset height
                  in fraction of cell height ('to_end': to cell top edge)
    
    column_widths: list of numbers or None (default None)
        list of length `cols` of the relative widths of each column of subplots.
        Values are normalized internally and used to distribute overall width
        of the figure (excluding padding) among the columns.
    
        For backward compatibility, may also be specified using the
        `column_width` keyword argument.
    
    row_heights: list of numbers or None (default None)
        list of length `rows` of the relative heights of each row of subplots.
        If start_cell='top-left' then row heights are applied top to bottom.
        Otherwise, if start_cell='bottom-left' then row heights are applied
        bottom to top.
    
        For backward compatibility, may also be specified using the
        `row_width` kwarg. If specified as `row_width`, then the width values
        are applied from bottom to top regardless of the value of start_cell.
        This matches the legacy behavior of the `row_width` argument.
    
    column_titles: list of str or None (default None)
        list of length `cols` of titles to place above the top subplot in
        each column.
    
    row_titles: list of str or None (default None)
        list of length `rows` of titles to place on the right side of each
        row of subplots. If start_cell='top-left' then row titles are
        applied top to bottom. Otherwise, if start_cell='bottom-left' then
        row titles are applied bottom to top.
    
    x_title: str or None (default None)
        Title to place below the bottom row of subplots,
        centered horizontally
    
    y_title: str or None (default None)
        Title to place to the left of the left column of subplots,
        centered vertically
    
    figure: go.Figure or None (default None)
        If None, a new go.Figure instance will be created and its axes will be
        populated with those corresponding to the requested subplot geometry and
        this new figure will be returned.
        If a go.Figure instance, the axes will be added to the
        layout of this figure and this figure will be returned. If the figure
        already contains axes, they will be overwritten.
    
    Examples
    --------
    
    Example 1:
    
    >>> # Stack two subplots vertically, and add a scatter trace to each
    >>> from plotly.subplots import make_subplots
    >>> import plotly.graph_objects as go
    >>> fig = make_subplots(rows=2)
    
    This is the format of your plot grid:
    [ (1,1) xaxis1,yaxis1 ]
    [ (2,1) xaxis2,yaxis2 ]
    
    >>> fig.add_scatter(y=[2, 1, 3], row=1, col=1) # doctest: +ELLIPSIS
    Figure(...)
    >>> fig.add_scatter(y=[1, 3, 2], row=2, col=1) # doctest: +ELLIPSIS
    Figure(...)
    
    or see Figure.append_trace
    
    Example 2:
    
    >>> # Stack a scatter plot
    >>> fig = make_subplots(rows=2, shared_xaxes=True)
    
    This is the format of your plot grid:
    [ (1,1) xaxis1,yaxis1 ]
    [ (2,1) xaxis2,yaxis2 ]
    
    >>> fig.add_scatter(y=[2, 1, 3], row=1, col=1) # doctest: +ELLIPSIS
    Figure(...)
    >>> fig.add_scatter(y=[1, 3, 2], row=2, col=1) # doctest: +ELLIPSIS
    Figure(...)
    
    Example 3:
    
    >>> # irregular subplot layout (more examples below under 'specs')
    >>> fig = make_subplots(rows=2, cols=2,
    ...                     specs=[[{}, {}],
    ...                     [{'colspan': 2}, None]])
    
    This is the format of your plot grid:
    [ (1,1) xaxis1,yaxis1 ]  [ (1,2) xaxis2,yaxis2 ]
    [ (2,1) xaxis3,yaxis3           -              ]
    
    >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=1) # doctest: +ELLIPSIS
    Figure(...)
    >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=2) # doctest: +ELLIPSIS
    Figure(...)
    >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=2, col=1) # doctest: +ELLIPSIS
    Figure(...)
    
    Example 4:
    
    >>> # insets
    >>> fig = make_subplots(insets=[{'cell': (1,1), 'l': 0.7, 'b': 0.3}])
    
    This is the format of your plot grid:
    [ (1,1) xaxis1,yaxis1 ]
    
    With insets:
    [ xaxis2,yaxis2 ] over [ (1,1) xaxis1,yaxis1 ]
    
    >>> fig.add_scatter(x=[1,2,3], y=[2,1,1]) # doctest: +ELLIPSIS
    Figure(...)
    >>> fig.add_scatter(x=[1,2,3], y=[2,1,2], xaxis='x2', yaxis='y2') # doctest: +ELLIPSIS
    Figure(...)
    
    Example 5:
    
    >>> # include subplot titles
    >>> fig = make_subplots(rows=2, subplot_titles=('Plot 1','Plot 2'))
    
    This is the format of your plot grid:
    [ (1,1) x1,y1 ]
    [ (2,1) x2,y2 ]
    
    >>> fig.add_scatter(x=[1,2,3], y=[2,1,2], row=1, col=1) # doctest: +ELLIPSIS
    Figure(...)
    >>> fig.add_bar(x=[1,2,3], y=[2,1,2], row=2, col=1) # doctest: +ELLIPSIS
    Figure(...)
    
    Example 6:
    
    Subplot with mixed subplot types
    
    >>> fig = make_subplots(rows=2, cols=2,
    ...                     specs=[[{'type': 'xy'},    {'type': 'polar'}],
    ...                            [{'type': 'scene'}, {'type': 'ternary'}]])
    
    >>> fig.add_traces(
    ...     [go.Scatter(y=[2, 3, 1]),
    ...      go.Scatterpolar(r=[1, 3, 2], theta=[0, 45, 90]),
    ...      go.Scatter3d(x=[1, 2, 1], y=[2, 3, 1], z=[0, 3, 5]),
    ...      go.Scatterternary(a=[0.1, 0.2, 0.1],
    ...                        b=[0.2, 0.3, 0.1],
    ...                        c=[0.7, 0.5, 0.8])],
    ...     rows=[1, 1, 2, 2],
    ...     cols=[1, 2, 1, 2]) # doctest: +ELLIPSIS
    Figure(...)

What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter