Indicator Plot

An indicator plot is a type of plot that highlights a collection of numeric values.

What are indicator plots useful for?

Highlight specific metrics: Indicator plots are useful when you want to highlight specific numeric metrics in a visually appealing way.
Compare metrics to a reference value: Indicator plots are useful to compare metrics to a reference value, such as a starting value or a target value.
Compare metrics to each other: Indicator plots are useful to compare multiple metrics to each other by highlighting where they fall relative to each other.

Examples

A basic indicator plot

Visualize a single numeric value by passing the column name to the value argument. The table should contain only one row.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])

indicator_plot = dx.indicator(dog_avg, value="Price")

Indicator Plot Basic Example

A delta indicator plot

Visualize a single numeric value with a delta to a reference value by passing the reference column name to the reference argument.

import deephaven.plot.express as dx
from deephaven import agg as agg
my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_agg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")])

indicator_plot = dx.indicator(dog_agg, value="Price", reference="StartingPrice")

Indicator plots from variables

Pass variables into a table to create an indicator plot.

import deephaven.plot.express as dx
from deephaven import new_table
from deephaven.column import int_col

my_value = 10
my_reference = 5

my_table = new_table([
    int_col("MyValue", [my_value]),
    int_col("MyReference", [my_reference])
])

indicator_plot = dx.indicator(my_table, value="MyValue", reference="MyReference")

Delta only indicator plot

Visualize only the delta to a reference value by passing number=False.

import deephaven.plot.express as dx
from deephaven import agg as agg
my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_agg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")])

indicator_plot = dx.indicator(dog_agg, value="Price", reference="StartingPrice", number=False)

An angular indicator plot

Visualize a single numeric value with an angular gauge by passing gauge="angular".

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])

indicator_plot = dx.indicator(dog_avg, value="Price", gauge="angular")

A hidden axis bullet indicator plot

Visualize a single numeric value with a bullet gauge by passing gauge="bullet". Hide the axis by passing axis=False.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])

indicator_plot = dx.indicator(dog_avg, value="Price", gauge="bullet", axis=False)

Prefixes and suffixes

Add a prefix and suffix to the numeric value by passing prefix and suffix.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")])

indicator_plot = dx.indicator(dog_avg, value="Price", reference="StartingPrice", prefix="$", suffix=" USD")

Number Format

Format the numbers by passing a format string to the number_format argument.
\\ The format follows the GWT Java NumberFormat syntax. The default format is set within the Settings panel. If only value is specified, the default format matches the type of that column.
\\ If reference is specified, the default format is the Integer format if they are both integers. Otherwise, the default format is the Decimal format.
\\ If a prefix or suffix is passed within the format string, it will be overridden by the prefix and suffix arguments.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])

# format the number with a dollar sign prefix, USD suffix, and three decimal places
indicator_plot = dx.indicator(dog_avg, value="Price", number_format="$#,##0.000USD")

# prefix overrides the prefix from the number_format
indicator_plot_prefix = dx.indicator(
    dog_avg, value="Price", number_format="$#,##0.000USD", prefix="Dollars: "
)

Delta Symbols

Modify the symbol before the delta value by passing increasing_text and decreasing_text.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
dog_agg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")])

indicator_plot = dx.indicator(
    dog_agg,
    value="Price",
    reference="StartingPrice",
    increasing_text="Up: ",
    decreasing_text="Down: "
)

Indicator with text

Add text to the indicator by passing the text column name to the text argument.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate prices, keeping the Sym
dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")], by="Sym")

indicator_plot = dx.indicator(dog_avg, value="Price", by="Sym", text="Sym")

Multiple indicators

Visualize multiple numeric values by passing in a table with multiple rows and the by argument. By default, a square grid of indicators is created.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# aggregate for average prices by Sym
sym_avg = my_table.agg_by([agg.avg(cols="Price")], by="Sym")

indicator_plot = dx.indicator(sym_avg, value="Price", by="Sym")

Multiple rows

By default, a grid of indicators is created. To create a specific amount of rows with a dynamic number of columns, pass the number of rows to the rows argument.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# aggregate for average prices by Sym
sym_avg = my_table.agg_by([agg.avg(cols="Price")], by="Sym")

indicator_plot = dx.indicator(sym_avg, value="Price", by="Sym", rows=2)

Multiple columns

By default, a grid of indicators is created. To create a specific amount of columns with a dynamic number of rows, pass the number of columns to the columns argument.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# aggregate for average prices by Sym
sym_avg = my_table.agg_by([agg.avg(cols="Price")], by="Sym")

indicator_plot = dx.indicator(sym_avg, value="Price", by="Sym", cols=2)

Delta colors

Change the color of the delta value based on whether it is increasing or decreasing by passing increasing_color_sequence and decreasing_color_sequence. These colors are applied sequentially to the indicators and looped if there are more indicators than colors.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
sym_agg = my_table.agg_by(
    [agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")]
)

indicator_plot = dx.indicator(
    sym_agg,
    value="Price",
    reference="StartingPrice",
    increasing_color_sequence=["darkgreen", "green"],
    decreasing_color_sequence=["darkred", "red"],
)

Gauge colors

Change the color of the gauge based on the value by passing gauge_color_sequence. These colors are applied sequentially to the indicators and looped if there are more indicators than colors.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate for DOG prices
sym_agg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])

indicator_plot = dx.indicator(
    sym_agg, value="Price", gauge="angular", gauge_color_sequence=["darkgreen", "green"]
)

Plot by

Create groups of styled indicators by passing the grouping categorical column name to the by argument. increasing_color_map and decreasing_color_map can be used to style the indicators based on the group.

import deephaven.plot.express as dx
from deephaven import agg as agg

my_table = dx.data.stocks()

# subset data and aggregate prices, keeping the Sym
sym_agg = my_table.agg_by(
    [
        agg.avg(cols="Price"),
        agg.first(cols="StartingPrice = Price"),
    ],
    by="Sym",
)

indicator_plot = dx.indicator(
    sym_agg,
    value="Price",
    reference="StartingPrice",
    by="Sym",
    by_vars=("increasing_color", "decreasing_color"),
    increasing_color_map={"DOG": "darkgreen"},
    decreasing_color_map={"DOG": "darkred"},
)

API Reference

Create an indicator chart.

Returns: DeephavenFigure A DeephavenFigure that contains the indicator chart

Parameters	Type	Default	Description
table	PartitionedTable \| Table \| DataFrame		A table to pull data from.
value	str \| None		The column to use as the value.
reference	str \| None	None	The column to use as the reference value.
by	str \| list[str] \| None	None	A column or list of columns that contain values to plot the figure traces by. All values or combination of values map to a unique design. The variable by_vars specifies which design elements are used. This is overriden if any specialized design variables such as increasing_color are specified
by_vars	str \| tuple[str, ...]	'gauge_color'	A string or list of string that contain design elements to plot by. Can contain increasing_color and decreasing_color If associated maps or sequences are specified, they are used to map by column values to designs. Otherwise, default values are used.
increasing_color	str \| list[str] \| None	None	A column or list of columns used for a plot by on delta increasing color. Only valid if reference is not None. See increasing_color_map for additional behaviors.
decreasing_color	str \| list[str] \| None	None	A column or list of columns used for a plot by on delta increasing color. Only valid if reference is not None. See decreasing_color_map for additional behaviors.
gauge_color	str \| list[str] \| None	None	A column or list of columns used for a plot by on color. Only valid if gauge is not None. See gauge_color_map for additional behaviors.
text	str \| Literal[False] \| None	None	A column that contains text annotations. Set to "by" if by is specified and is one column. Set to False to hide text annotations.
increasing_color_sequence	list[str] \| None	None	A list of colors to sequentially apply to the series. The colors loop, so if there are more series than colors, colors are reused.
increasing_color_map	Dict[str \| Tuple[str], str] \| None	None	A dict with keys that are strings of the column values (or a tuple of combinations of column values) which map to colors.
decreasing_color_sequence	list[str] \| None	None	A list of colors to sequentially apply to the series. The colors loop, so if there are more series than colors, colors are reused.
decreasing_color_map	Dict[str \| Tuple[str], str] \| None	None	A dict with keys that are strings of the column values (or a tuple of combinations of column values) which map to colors.
gauge_color_sequence	list[str] \| None	None	A list of colors to sequentially apply to the series. The colors loop, so if there are more series than colors, colors are reused.
gauge_color_map	Dict[str \| Tuple[str], str] \| None	None	A dict with keys that are strings of the column values (or a tuple of combinations of column values) which map to colors.
number	bool	True	True to show the number, False to hide it.
gauge	Literal['angular', 'bullet'] \| None	None	Specifies the type of gauge to use. Set to "angular" for a half-circle gauge and "bullet" for a horizontal gauge.
axis	bool	True	True to show the axis. Only valid if gauge is set.
prefix	str \| None	None	A string to prepend to the number value.
suffix	str \| None	None	A string to append to the number value.
increasing_text	str \| None	'▲'	The text to display before the delta if the number value is greater than the reference value.
decreasing_text	str \| None	'▼'	The text to display before the delta if the number value is less than the reference value.
number_format	str \| None	None	A string that specifies the number format for values and deltas. Default is "#,##0.00" which formats numbers with commas every three digits and two decimal places.
rows	int \| None	None	The number of rows of indicators to create. If None, the number of rows is determined by the number of columns. If both rows and columns are None, a square grid is created.
cols	int \| None	None	The number of columns of indicators to create. If None, the number of columns is determined by the number of rows. If both rows and columns are None, a square grid is created.
title	str \| None	None	The title of the chart
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.