Sub plots

Multiple sub plots can be combined into one plot using the make_subplots function. This function accepts multiple plot objects, and returns a single plot object. The plot objects can be any of the plot types supported by Deephaven Express. They can be arranged in a grid, or in a single row or column. The shared_xaxes and shared_yaxes parameters can be used to share axes between plots.

Examples

Four unique plots

Create a series of plots as subplots, all providing unique perspectives on the data of interest.

import deephaven.plot.express as dx
tips = dx.data.tips() # import a ticking version of the Tips dataset

# create 4 plots from within make_subplots
tipping_plots = dx.make_subplots(
    dx.scatter(tips, x="TotalBill", y="Tip", by="Sex",
        title="Tip amount by total bill"),
    dx.violin(tips, y="TotalBill", by="Day",
        title="Total bill distribution by day"),
    dx.pie(
        tips
        .count_by("Count", by=["Sex", "Smoker"])
        .update_view("SmokerStatus = Smoker == `No` ? `non-smoker` : `smoker`")
        .update_view("SmokerLabel = Sex + ` ` + SmokerStatus"),
        names="SmokerLabel", values="Count",
        title="Total bill by sex and smoking status"),
    dx.bar(tips
        .view(["TotalBill", "Tip", "Day"])
        .avg_by("Day"),
        x="Day", y=["TotalBill", "Tip"],
        title="Average tip as a fraction of total bill"),
    rows=2, cols=2, shared_xaxes=False, shared_yaxes=False
)

Share axes between plots with the shared_xaxes and shared_yaxes parameters.

When shared_xaxes or shared_yaxes is set to "all", all axes of the same type are shared. When one axis is adjusted, all axes are adjusted to match.

import deephaven.plot.express as dx
tips = dx.data.tips() # import a ticking version of the Tips dataset

# filter the tips dataset for separate lunch and dinner charts
lunch_tips = tips.where("Time = `Lunch`")
dinner_tips = tips.where("Time = `Dinner`")

# create chart that shares all axes
tipping_plots = dx.make_subplots(
    dx.scatter(lunch_tips, x="TotalBill", y="Tip", labels={"Tip": "Lunch Tips"}),
    dx.scatter(dinner_tips, x="TotalBill", y="Tip", labels={"Tip": "Dinner Tips"}),
    rows=2, shared_yaxes="all", shared_xaxes="all"
)

When shared_yaxis is set to True, all y axes are shared along the same row. When one y-axis is adjusted, all axes along the same row are adjusted to match.

import deephaven.plot.express as dx
tips = dx.data.tips() # import a ticking version of the Tips dataset

# filter the tips dataset for separate lunch and dinner charts
lunch_tips = tips.where("Time = `Lunch`")
dinner_tips = tips.where("Time = `Dinner`")

# create chart that shares y axes along the row
tipping_plots = dx.make_subplots(
    dx.scatter(lunch_tips, x="TotalBill", y="Tip", labels={"Tip": "Lunch Tips"}),
     dx.scatter(dinner_tips, x="TotalBill", y="Tip", labels={"Tip": "Dinner Tips"}),
    cols=2, shared_yaxes=True
)

To share the y axes along the same column, set shared_yaxes to "columns".

import deephaven.plot.express as dx
tips = dx.data.tips() # import a ticking version of the Tips dataset

# filter the tips dataset for separate lunch and dinner charts
lunch_tips = tips.where("Time = `Lunch`")
dinner_tips = tips.where("Time = `Dinner`")

# create chart that shares y axes along the column
tipping_plots = dx.make_subplots(
    dx.scatter(lunch_tips, x="TotalBill", y="Tip", labels={"Tip": "Lunch Tips"}),
     dx.scatter(dinner_tips, x="TotalBill", y="Tip", labels={"Tip": "Dinner Tips"}),
    rows=2, shared_yaxes="columns"
)

When shared_xaxis is set to True, all x axes are shared along the same column. When one x-axis is adjusted, all axes along the same column are adjusted to match.

import deephaven.plot.express as dx
tips = dx.data.tips() # import a ticking version of the Tips dataset

# filter the tips dataset for separate lunch and dinner charts
lunch_tips = tips.where("Time = `Lunch`")
dinner_tips = tips.where("Time = `Dinner`")

# create chart that shares x axes along the column
tipping_plots = dx.make_subplots(
    dx.scatter(lunch_tips, x="TotalBill", y="Tip", labels={"Tip": "Lunch Tips"}),
     dx.scatter(dinner_tips, x="TotalBill", y="Tip", labels={"Tip": "Dinner Tips"}),
    rows=2, shared_xaxes=True
)

To share the x axes along the same column, set shared_yaxes to "columns".

import deephaven.plot.express as dx
tips = dx.data.tips() # import a ticking version of the Tips dataset

# filter the tips dataset for separate lunch and dinner charts
lunch_tips = tips.where("Time = `Lunch`")
dinner_tips = tips.where("Time = `Dinner`")

# create chart that shares x axes along the row
tipping_plots = dx.make_subplots(
    dx.scatter(lunch_tips, x="TotalBill", y="Tip", labels={"Tip": "Lunch Tips"}),
     dx.scatter(dinner_tips, x="TotalBill", y="Tip", labels={"Tip": "Dinner Tips"}),
    cols=2, shared_xaxes="rows"
)

API Reference

Create subplots. Either figs and at least one of rows and cols or grid should be passed.

Returns: DeephavenFigure The DeephavenFigure with subplots

Parameters	Type	Default	Description
*figs	Figure \| DeephavenFigure		Figures to use. Should be used with rows and/or cols.
rows	int	0	A list of rows in the resulting subplot grid. This is calculated from cols and number of figs provided if not passed but cols is. One of rows or cols should be provided if passing figs directly.
cols	int	0	A list of cols in the resulting subplot grid. This is calculated from rows and number of figs provided if not passed but rows is. One of rows or cols should be provided if passing figs directly.
shared_xaxes	str \| bool \| None	None	"rows", "columns"/True, "all" or None depending on what axes should be shared
shared_yaxes	str \| bool \| None	None	"rows"/True, "columns", "all" or None depending on what axes should be shared
grid	List[List[Figure \| DeephavenFigure]] \| None	None	A grid (list of lists) of figures to draw. None can be provided in a grid entry
horizontal_spacing	float \| None	None	Spacing between each column. Default 0.2 / cols
vertical_spacing	float \| None	None	Spacing between each row. Default 0.3 / rows
column_widths	list[float] \| None	None	The widths of each column. Should sum to 1.
row_heights	list[float] \| None	None	The heights of each row. Should sum to 1.
specs	list[SubplotSpecDict] \| List[List[SubplotSpecDict]] \| None	None	(Default value = None) A list or grid of dicts that contain specs. An empty dictionary represents no specs, and None represents no figure, either to leave a gap on the subplots on provide room for a figure spanning multiple columns. 'l' is a float that adds left padding 'r' is a float that adds right padding 't' is a float that adds top padding 'b' is a float that adds bottom padding 'rowspan' is an int to make this figure span multiple rows 'colspan' is an int to make this figure span multiple columns
unsafe_update_figure	Callable	<function default_callback>	An update function that takes a plotly figure as an argument and optionally returns a plotly figure. If a figure is not returned, the plotly figure passed will be assumed to be the return value. Used to add any custom changes to the underlying plotly figure. Note that the existing data traces should not be removed. This may lead to unexpected behavior if traces are modified in a way that break data mappings.

Sub plots

Examples

Four unique plots

Share Axes

Share All Axes

Share Y Axes

Share X Axes

API Reference