Categorical

Categorical

Categorical(
    data: DataType | DataFrame,
    *,
    category_axis: str
    | WidgetField
    | CategoryAxis = "category",
    value_axis: ValueAxisSeries | ValueAxis | None = None,
    secondary_value_axis: ValueAxisSeries
    | ValueAxis
    | None = None,
    widget_id: str | None = None,
    legend_position: LegendPosition = BOTTOM,
    title: WidgetTitleType | None = None,
    enable_toolbar: bool = True,
    direction: ChartDirection = VERTICAL,
    tooltips: list[TooltipItem] | None = None,
)

Spec for Categorical widget.

Construct spec for a Categorical widget.

Parameters:

Name	Type	Description	Default
data	DataType | DataFrame	data source for the widget.	required
widget_id	str | None	unique widget id in a dashboard.	None
category_axis	str | WidgetField | CategoryAxis	spec for category axis.	'category'
value_axis	ValueAxisSeries | ValueAxis | None	spec for main value axis.	None
secondary_value_axis	ValueAxisSeries | ValueAxis | None	Spec for secondary value axis.	None
legend_position	LegendPosition	legend of Categorical widget.	BOTTOM
title	WidgetTitleType | None	title of widget can be either a string (fixed value) or determined by a value from another widget using a WidgetField.	None
enable_toolbar	bool	Enable/Disable toolbar flag.	True
direction	ChartDirection	option to set the direction for series in the Chart.	VERTICAL
tooltips	list[TooltipItem] | None	list of tooltip items.	None

Examples:

Create a minimal Categorical widget

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data = pd.DataFrame(
    [
        {"category": "Apple", "value": 100, "value_2": 1999},
        {"category": "Microsoft", "value": 200, "value_2": 2999},
    ]
)

categorical_widget = categorical.Categorical(
    data=data,
    category_axis="category",
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget,
)

Components

CategoryAxis

CategoryAxis(
    *,
    data_column: str | GenericLink,
    label_column: str | GenericLink | None = None,
    title: str | GenericLink = "",
    enable_crosshair: bool = False,
    line: AxisLine | None = None,
    band: AxisBand | None = None,
)

Specs for category axis of a Categorical chart.

Construct category axis for a Categorical chart.

Parameters:

Name	Type	Description	Default
title	str | GenericLink	axis title.	''
data_column	str | GenericLink	name of column in pandas dataframe(s) used for Category axis values.	required
enable_crosshair	bool	whether to enable crosshair that follows either the mouse pointer or the hovered point.	False
label_column	str | GenericLink | None	name of column in pandas dataframe(s) used for the label of each category. Same values are used for each series.	None
line	AxisLine | None	specs for chart axis line.	None
band	AxisBand | None	specs for chart axis band.	None

ValueAxis

ValueAxis(
    *,
    series: ValueAxisSeries,
    formatting: AxisNumberFormatting | None = None,
    title: str | GenericLink | None = None,
    enable_crosshair: bool = False,
    scale: AxisScale | None = None,
    line: AxisLine | None = None,
    band: AxisBand | None = None,
)

Specs for Value Axis of a Categorical chart.

Construct Value Axis for a Categorical chart.

Parameters:

Name	Type	Description	Default
series	ValueAxisSeries	series to be added to the axis.	required
formatting	AxisNumberFormatting | None	formatting spec for axis labels.	None
title	str | GenericLink | None	axis title.	None
scale	AxisScale | None	y axis scale, one of AxisScaleDynamic, AxisScaleSymmetric, AxisScalePositive, AxisScaleNegative.	None
enable_crosshair	bool	whether to enable crosshair that follows either the mouse pointer or the hovered point. Defaults to False.	False
line	AxisLine | None	line to be added to the axis.	None
band	AxisBand | None	band to be added to the axis.	None

Create a Categorical widget with two ValueAxis

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.styling.color import Palette
from engineai.sdk.dashboard.widgets import categorical
from engineai.sdk.dashboard.widgets.components.charts.styling import (
    BubbleCircleSeriesStyling,
    ColumnSeriesStyling,
    PointSeriesStyling,
)

data = pd.DataFrame(
    [
        {
            "company": "Apple",
            "shares_short": 700,
            "volume": 1200,
            "market_cap": 1500,
        },
        {
            "company": "Microsoft",
            "shares_short": 900,
            "volume": 1600,
            "market_cap": 2000,
        },
    ]
)

categorical_widget = categorical.Categorical(
    data=data,
    category_axis="company",
    value_axis=categorical.ValueAxis(
        series=[
            categorical.PointSeries(
                data_column="volume",
                styling=PointSeriesStyling(color_spec=Palette.PURPLE_7),
            ),
            categorical.ColumnSeries(
                data_column="shares_short",
                styling=ColumnSeriesStyling(color_spec=Palette.SKY_BLUE),
            ),
        ]
    ),
    secondary_value_axis=categorical.ValueAxis(
        series=categorical.BubbleSeries(
            name="Market Cap vs Volume",
            data_column="volume",
            bubble_size_data_column="market_cap",
            bubble_name="Market Cap",
            styling=BubbleCircleSeriesStyling(color_spec=Palette.GOLD_5),
        )
    ),
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget,
)

LegendPosition

Chart legend position options.

Options for positions of charts legend.

Attributes:

Name	Type	Description
RIGHT	str	Legend is placed to the right of the chart.
BOTTOM	str	Legend is placed below the chart.
RIGHT_GROUPED	str	Legend is placed to the right of the chart and grouped with other legends.
BOTTOM_GROUPED	str	Legend is placed below the chart and grouped with other legends.
NEXT_TO_DATA	str	Legend is placed next to the data.

ChartDirection

Options for directions of categorical chart.

Attributes:

Name	Type	Description
VERTICAL		Chart with a vertical direction.
HORIZONTAL		Chart with a horizontal direction.

Series

AreaSeries

AreaSeries(
    *,
    data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    styling: Palette | AreaSeriesStyling | None = None,
    stacked: bool = False,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Area Series of a Categorical widget.

Construct Area Series.

Parameters:

Name	Type	Description	Default
data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series for the Y Axis.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
styling	Palette | AreaSeriesStyling | None	styling spec.	None
stacked	bool	whether area is stacked or not.	False
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with AreaSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_area = pd.DataFrame(
    {
        "category": ["Q1", "Q2", "Q3", "Q4"],
        "revenue": [100, 150, 200, 180],
    }
)

area_series = categorical.AreaSeries(
    data_column="revenue",
    name="Revenue",
)

categorical_widget_area = categorical.Categorical(
    data=data_area,
    category_axis="category",
    value_axis=area_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_area,
)

AreaRangeSeries

AreaRangeSeries(
    *,
    low_data_column: str | GenericLink,
    high_data_column: str | GenericLink,
    name: str | GenericLink,
    styling: Palette | AreaRangeSeriesStyling | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Area Range Series of a Categorical widget.

Construct Area Range Series.

Parameters:

Name	Type	Description	Default
low_data_column	str | GenericLink	name of column in pandas dataframe(s) used for the low values of this series.	required
high_data_column	str | GenericLink	name of column in pandas dataframe(s) used for the high values of this series.	required
name	str | GenericLink	series name (shown in legend and tooltip).	required
styling	Palette | AreaRangeSeriesStyling | None	styling spec.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with AreaRangeSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_area_range = pd.DataFrame(
    {
        "category": ["Jan", "Feb", "Mar", "Apr"],
        "low_temp": [10, 15, 20, 25],
        "high_temp": [25, 30, 35, 40],
    }
)

area_range_series = categorical.AreaRangeSeries(
    low_data_column="low_temp",
    high_data_column="high_temp",
    name="Temperature Range",
)

categorical_widget_area_range = categorical.Categorical(
    data=data_area_range,
    category_axis="category",
    value_axis=area_range_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_area_range,
)

BubbleSeries

BubbleSeries(
    *,
    bubble_size_data_column: str | GenericLink,
    data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    bubble_name: str | GenericLink | None = None,
    bubble_size_formatting: NumberFormatting | None = None,
    styling: Palette | BubbleSeriesStyling | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Bubble Series of a Categorical widget.

Construct a Bubble Series.

Parameters:

Name	Type	Description	Default
bubble_size_data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series associated with the size of the bubble.	required
data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series for the Y Axis.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
bubble_name	str | GenericLink | None	name for the bubble value (show in tooltip).	None
bubble_size_formatting	NumberFormatting | None	formatting spec for size of the bubble (used in tooltip).	None
styling	Palette | BubbleSeriesStyling | None	styling spec.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with BubbleSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_bubble = pd.DataFrame(
    {
        "category": ["Product A", "Product B", "Product C", "Product D"],
        "sales": [100, 200, 150, 300],
        "profit": [20, 50, 30, 80],
        "market_size": [1000, 2000, 1500, 3000],
    }
)

bubble_series = categorical.BubbleSeries(
    data_column="sales",
    bubble_size_data_column="market_size",
    name="Sales vs Market Size",
    bubble_name="Market Size",
)

categorical_widget_bubble = categorical.Categorical(
    data=data_bubble,
    category_axis="category",
    value_axis=bubble_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_bubble,
)

ErrorBarSeries

ErrorBarSeries(
    *,
    low_data_column: str | GenericLink,
    high_data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    styling: Palette | ErrorBarSeriesStyling | None = None,
    stack: str | GenericLink | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec forError Bar Series of a Categorical widget.

Construct Column Series.

Parameters:

Name	Type	Description	Default
low_data_column	str | GenericLink	name of column in pandas dataframe(s) used for the low value of this series.	required
high_data_column	str | GenericLink	name of column in pandas dataframe(s) used for the high value of this series.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
styling	Palette | ErrorBarSeriesStyling | None	styling spec.	None
stack	str | GenericLink | None	id of stack for column.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with ErrorBarSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.styling.color.palette import Palette
from engineai.sdk.dashboard.widgets import categorical

data_error = pd.DataFrame(
    {
        "category": ["Test A", "Test B", "Test C", "Test D"],
        "value": [100, 200, 150, 250],
        "error_low": [90, 180, 130, 220],
        "error_high": [110, 220, 170, 280],
    }
)

error_bar_series = categorical.ErrorBarSeries(
    low_data_column="error_low",
    high_data_column="error_high",
    name="Measurements with Error",
    styling=Palette.AQUA_GREEN,
)

categorical_widget_error = categorical.Categorical(
    data=data_error,
    category_axis="category",
    value_axis=error_bar_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_error,
)

ColumnSeries

ColumnSeries(
    *,
    data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    styling: Palette | ColumnSeriesStyling | None = None,
    stack: str | GenericLink | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Column Series of a Categorical widget.

Construct Column Series.

Parameters:

Name	Type	Description	Default
data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series for the Y Axis.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
styling	Palette | ColumnSeriesStyling | None	styling spec.	None
stack	str | GenericLink | None	id of stack for column.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with ColumnSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_column = pd.DataFrame(
    {
        "category": ["North", "South", "East", "West"],
        "sales": [150, 200, 175, 225],
    }
)

column_series = categorical.ColumnSeries(
    data_column="sales",
    name="Regional Sales",
)

categorical_widget_column = categorical.Categorical(
    data=data_column,
    category_axis="category",
    value_axis=column_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_column,
)

LineSeries

LineSeries(
    *,
    data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    styling: Palette | LineSeriesStyling | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Line Series of a Categorical widget.

Construct Line Series.

Parameters:

Name	Type	Description	Default
data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series for the Y Axis.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
styling	Palette | LineSeriesStyling | None	styling spec.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with LineSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_line = pd.DataFrame(
    {
        "category": ["Week 1", "Week 2", "Week 3", "Week 4"],
        "growth": [5, 8, 12, 15],
    }
)

line_series = categorical.LineSeries(
    data_column="growth",
    name="Weekly Growth",
)

categorical_widget_line = categorical.Categorical(
    data=data_line,
    category_axis="category",
    value_axis=line_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_line,
)

PointSeries

PointSeries(
    *,
    data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    styling: Palette | PointSeriesStyling | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Point Series of a Categorical widget.

Construct Point Series.

Parameters:

Name	Type	Description	Default
data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series for the Y Axis.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
styling	Palette | PointSeriesStyling | None	styling spec.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with PointSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_point = pd.DataFrame(
    {
        "category": ["Alpha", "Beta", "Gamma", "Delta"],
        "score": [85, 92, 78, 95],
    }
)

point_series = categorical.PointSeries(
    data_column="score",
    name="Performance Scores",
)

categorical_widget_point = categorical.Categorical(
    data=data_point,
    category_axis="category",
    value_axis=point_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_point,
)

ScatterSeries

ScatterSeries(
    *,
    data_column: str | GenericLink,
    name: str | GenericLink | None = None,
    styling: Palette | ScatterSeriesStyling | None = None,
    show_in_legend: bool = True,
    required: bool = True,
    visible: bool = True,
    tooltips: list[TooltipItem] | None = None,
)

Spec for a Scatter Series of a Categorical widget.

Construct Scatter Series.

Parameters:

Name	Type	Description	Default
data_column	str | GenericLink	name of column in pandas dataframe(s) used for the values of this series for the Y Axis.	required
name	str | GenericLink | None	series name (shown in legend and tooltip).	None
styling	Palette | ScatterSeriesStyling | None	styling spec.	None
show_in_legend	bool	whether to show series in legend or not.	True
required	bool	Flag to make the Series mandatory. If required == True and no Data the widget will show an error. If required==False and no Data, the widget hides the Series.	True
visible	bool	Flag to make the Series visible when chart is loaded.	True
tooltips	list[TooltipItem] | None	Tooltip items to show in the tooltip.	None

Create a Categorical widget with ScatterSeries

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.widgets import categorical

data_scatter = pd.DataFrame(
    {
        "category": ["Item 1", "Item 2", "Item 3", "Item 4"],
        "efficiency": [0.75, 0.85, 0.65, 0.95],
    }
)

scatter_series = categorical.ScatterSeries(
    data_column="efficiency",
    name="Efficiency Ratings",
)

categorical_widget_scatter = categorical.Categorical(
    data=data_scatter,
    category_axis="category",
    value_axis=scatter_series,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_scatter,
)

Axis lines and bands

AxisLine

AxisLine(
    data: DataType | DataFrame,
    *,
    data_column: str,
    label: str | AxisLabel | None = None,
    styling: Palette | AxisLineStyling | None = None,
    dash_style: DashStyle = DASH,
)

Spec for Axis Line.

Construct a plot line for an axis.

Parameters:

Name	Type	Description	Default
data	DataType | DataFrame	data source for the Axis line.	required
data_column	str	name of column in pandas dataframe(s) used for the value of axis line	required
label	str | AxisLabel | None	label annotation.	None
styling	Palette | AxisLineStyling | None	specs for chart band styling.	None
dash_style	DashStyle	line dash style.	DASH

Create a Categorical widget with AxisLine

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.enum.align import HorizontalAlignment
from engineai.sdk.dashboard.widgets import categorical

data_line = pd.DataFrame(
    {
        "category": ["Jan", "Feb", "Mar", "Apr"],
        "performance": [85, 92, 78, 95],
    }
)

axis_line_data = pd.DataFrame(
    {
        "target_value": [90],
    }
)

axis_line = categorical.AxisLine(
    data=axis_line_data,
    data_column="target_value",
    label=categorical.AxisLabel(
        text="Target: 90%",
        x_position=-5,
        y_position=30,
        horizontal_align=HorizontalAlignment.LEFT,
    ),
)

performance_series = categorical.LineSeries(
    data_column="performance",
    name="Monthly Performance",
)

categorical_widget_line = categorical.Categorical(
    data=data_line,
    category_axis="category",
    value_axis=categorical.ValueAxis(
        series=performance_series,
        line=axis_line,
        title="Performance vs Target",
    ),
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_line,
)

AxisBand

AxisBand(
    data: DataType | DataFrame,
    *,
    from_column: str,
    to_column: str,
    label: str | AxisLabel | None = None,
    styling: Palette | AxisBandStyling | None = None,
)

Spec for Axis Band.

Construct a plot line for an axis.

Parameters:

Name	Type	Description	Default
data	DataType | DataFrame	data source for the Axis Band.	required
from_column	str	name of column in pandas dataframe(s) used for the start value for the band.	required
to_column	str	name of column in pandas dataframe(s) used for the end value for the band.	required
label	str | AxisLabel | None	label annotation.	None
styling	Palette | AxisBandStyling | None	specs for chart band styling.	None

Create a Categorical widget with AxisBand

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.enum.align import HorizontalAlignment, VerticalAlignment
from engineai.sdk.dashboard.widgets import categorical

data_band = pd.DataFrame(
    {
        "category": ["Week 1", "Week 2", "Week 3", "Week 4"],
        "sales": [100, 120, 140, 160],
    }
)

axis_band_data = pd.DataFrame(
    {
        "band_from": [95, 120],
        "band_to": [105, 145],
    }
)

axis_band = categorical.AxisBand(
    data=axis_band_data,
    from_column="band_from",
    to_column="band_to",
    label=categorical.AxisLabel(
        text="Optimal Range",
        horizontal_align=HorizontalAlignment.LEFT,
        vertical_align=VerticalAlignment.BOTTOM,
    ),
)

sales_series = categorical.ColumnSeries(
    data_column="sales",
    name="Weekly Sales",
)

categorical_widget_band = categorical.Categorical(
    data=data_band,
    category_axis="category",
    value_axis=categorical.ValueAxis(
        series=sales_series,
        band=axis_band,
        title="Sales with Target Band",
    ),
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_band,
)

Create a Categorical widget with multiple Axis and AxisBand

import pandas as pd

from engineai.sdk.dashboard.dashboard import Dashboard
from engineai.sdk.dashboard.enum.align import HorizontalAlignment, VerticalAlignment
from engineai.sdk.dashboard.styling.color.palette import Palette
from engineai.sdk.dashboard.widgets import categorical
from engineai.sdk.dashboard.widgets.components.charts.styling import ColumnSeriesStyling, LineSeriesStyling

data_multiple = pd.DataFrame(
    {
        "category": ["Product A", "Product B", "Product C", "Product D"],
        "revenue": [1000, 1500, 1200, 1800],
        "units_sold": [50, 75, 60, 90],
        "profit_margin": [20, 25, 22, 28],
    }
)

revenue_series = categorical.ColumnSeries(
    data_column="revenue",
    name="Revenue ($)",
    styling=ColumnSeriesStyling(color_spec=Palette.GOLD_5),
)

units_series = categorical.LineSeries(
    data_column="units_sold",
    name="Units Sold",
    styling=LineSeriesStyling(color_spec=Palette.BLUE_POSITIVE_4),
)

revenue_target_data = pd.DataFrame(
    {
        "revenue_min": [1700],
        "revenue_max": [1900],
    }
)

revenue_target_band = categorical.AxisBand(
    data=revenue_target_data,
    from_column="revenue_min",
    to_column="revenue_max",
    label=categorical.AxisLabel(
        text="Target Range",
        x_position=-5,
        y_position=25,
        horizontal_align=HorizontalAlignment.LEFT,
        vertical_align=VerticalAlignment.BOTTOM,
    ),
)

primary_value_axis = categorical.ValueAxis(
    series=revenue_series,
    title="Revenue ($)",
    band=revenue_target_band,
)

secondary_value_axis = categorical.ValueAxis(
    series=units_series,
    title="Units & Profit %",
)

categorical_widget_multiple = categorical.Categorical(
    data=data_multiple,
    category_axis=categorical.CategoryAxis(
        data_column="category",
        title="Products",
    ),
    value_axis=primary_value_axis,
    secondary_value_axis=secondary_value_axis,
)

Dashboard(
    workspace_slug="my-workspace",
    app_slug="my-app",
    slug="first-dashboard",
    content=categorical_widget_multiple,
)

AxisLabel

AxisLabel(
    *,
    text: str | DataField | None = None,
    x_position: int | DataField = -5,
    y_position: int | DataField = 2,
    horizontal_align: HorizontalAlignment = CENTER,
    vertical_align: VerticalAlignment = TOP,
    rotation: float | int | None = -90,
)

Spec for label of axis band or line.

Construct spec for label of axis band or line.

Parameters:

Name	Type	Description	Default
text	str | DataField | None	name of column in pandas dataframe(s) used for the label text.	None
x_position	int | DataField	name of column in pandas dataframe(s) used for the x value for the label position.	-5
y_position	int | DataField	name of column in pandas dataframe(s) used for they value for the label position.	2
horizontal_align	HorizontalAlignment	horizontal alignment spec.	CENTER
vertical_align	VerticalAlignment	vertical alignment spec.	TOP
rotation	float | int | None	Rotation of the text label in degrees.	-90

Types

CategoricalSeries module-attribute

CategoricalSeries = (
    LineSeries
    | AreaSeries
    | AreaRangeSeries
    | ColumnSeries
    | BubbleSeries
    | ScatterSeries
    | ErrorBarSeries
    | PointSeries
)

ValueAxisSeries module-attribute

ValueAxisSeries = (
    str
    | list[str]
    | WidgetField
    | list[WidgetField]
    | CategoricalSeries
    | Sequence[CategoricalSeries]
)