app.py•39.1 kB
"""Example app to show all features of Vizro."""
from typing import Literal
import dash_bootstrap_components as dbc
import pandas as pd
import plotly.graph_objects as go
import vizro.actions as va
import vizro.models as vm
import vizro.plotly.express as px
from dash import dash_table, dcc, get_asset_url, html
from vizro import Vizro
from vizro.figures import kpi_card, kpi_card_reference
from vizro.models.types import capture
from vizro.tables import dash_ag_grid, dash_data_table
iris = px.data.iris()
tips = px.data.tips()
stocks = px.data.stocks(datetimes=True)
gapminder = px.data.gapminder()
gapminder_2007 = px.data.gapminder().query("year == 2007")
gapminder_2007["is_europe"] = gapminder["continent"] == "Europe"
waterfall_df = pd.DataFrame(
{
"measure": ["relative", "relative", "total", "relative", "relative", "total"],
"x": ["Sales", "Consulting", "Net revenue", "Purchases", "Other expenses", "Profit before tax"],
"text": ["+60", "+80", "", "-40", "-20", "Total"],
"y": [60, 80, 0, -40, -20, 0],
}
)
custom_fig_df = pd.DataFrame(
{
"text": [
"Lorem ipsum dolor sit amet, consetetur sadipscing no sea elitr sed diam nonumy.",
"Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.",
"Sed diam voluptua. At vero eos et accusam et justo no duo dolores et ea rebum.",
"Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.",
"Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.",
"Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.",
]
* 2
}
)
df_kpi = pd.DataFrame({"Actual": [100, 200, 700], "Reference": [100, 300, 500], "Category": ["A", "B", "C"]})
example_cards = [
kpi_card(data_frame=df_kpi, value_column="Actual", title="KPI with value"),
kpi_card(data_frame=df_kpi, value_column="Actual", title="KPI with aggregation", agg_func="median"),
kpi_card(
data_frame=df_kpi,
value_column="Actual",
title="KPI with formatting",
value_format="${value:.2f}",
),
kpi_card(
data_frame=df_kpi,
value_column="Actual",
title="KPI with icon",
icon="Shopping Cart",
),
]
example_reference_cards = [
kpi_card_reference(
data_frame=df_kpi,
value_column="Actual",
reference_column="Reference",
title="KPI reference (pos)",
),
kpi_card_reference(
data_frame=df_kpi,
value_column="Actual",
reference_column="Reference",
agg_func="median",
title="KPI reference (neg)",
),
kpi_card_reference(
data_frame=df_kpi,
value_column="Actual",
reference_column="Reference",
title="KPI reference with formatting",
value_format="{value:.2f}$",
reference_format="{delta:.2f}$ vs. last year ({reference:.2f}$)",
),
kpi_card_reference(
data_frame=df_kpi,
value_column="Actual",
reference_column="Reference",
title="KPI reference with icon",
icon="Shopping Cart",
),
]
# HOME ------------------------------------------------------------------------
home = vm.Page(
title="Homepage",
layout=vm.Grid(grid=[[0, 1], [2, 3]], row_gap="16px", col_gap="24px"),
components=[
vm.Card(
text="""
### Components
Main components of Vizro include **charts**, **tables**, **cards**, **figures**, **containers**,
**buttons** and **tabs**.
""",
href="/graphs",
),
vm.Card(
text="""
### Controls
Vizro has two different control types **Filter** and **Parameter**.
You can use any pre-existing selector inside the **Filter** or **Parameter**:
* Dropdown
* Checklist
* RadioItems
* RangeSlider
* Slider
* DatePicker
""",
href="/filters",
),
vm.Card(
text="""
### Actions
Built-in actions are made available including **export data** and **filter interactions**.
""",
href="/export-data",
),
vm.Card(
text="""
### Extensions
Vizro enables customization of **plotly express** and **graph object charts** as well as
creating custom components based on Dash.
""",
href="/custom-charts",
),
],
)
# COMPONENTS ------------------------------------------------------------------
graphs = vm.Page(
title="Graphs",
components=[
vm.Graph(
figure=px.scatter(iris, x="sepal_width", y="sepal_length", color="species"),
title="Relationships between Sepal Width and Sepal Length",
header="""
Each point in the scatter plot represents one of the 150 iris flowers, with colors indicating their
types. The Setosa type is easily identifiable by its short and wide sepals.
However, there is still overlap between the Versicolor and Virginica types when considering only sepal
width and length.
""",
footer="""SOURCE: **Plotly iris data set, 2024**""",
),
],
)
ag_grid = vm.Page(
title="AG Grid",
components=[
vm.AgGrid(
figure=dash_ag_grid(data_frame=gapminder_2007, dashGridOptions={"pagination": True}),
title="Gapminder Data Insights",
header="""#### An Interactive Exploration of Global Health, Wealth, and Population""",
footer="""SOURCE: **Plotly gapminder data set, 2024**""",
)
],
)
table = vm.Page(
title="Table",
components=[
vm.Table(
figure=dash_data_table(data_frame=gapminder_2007),
title="Gapminder Data Insights",
header="""#### An Interactive Exploration of Global Health, Wealth, and Population""",
footer="""SOURCE: **Plotly gapminder data set, 2024**""",
)
],
)
cards = vm.Page(
title="Cards",
components=[
vm.Card(
text="""
# Header level 1 <h1>
## Header level 2 <h2>
### Header level 3 <h3>
#### Header level 4 <h4>
"""
),
vm.Card(
text="""
### Paragraphs
Commodi repudiandae consequuntur voluptatum laborum numquam blanditiis harum quisquam eius sed odit.
Fugiat iusto fuga praesentium option, eaque rerum! Provident similique accusantium nemo autem.
Obcaecati tenetur iure eius earum ut molestias architecto voluptate aliquam nihil, eveniet aliquid.
Culpa officia aut! Impedit sit sunt quaerat, odit, tenetur error, harum nesciunt ipsum debitis quas.
"""
),
vm.Card(
text="""
### Block Quotes
>
> A block quote is a long quotation, indented to create a separate block of text.
>
"""
),
vm.Card(
text="""
### Lists
* Item A
* Sub Item 1
* Sub Item 2
* Item B
"""
),
vm.Card(
text="""
### Emphasis
This word will be *italic*
This word will be **bold**
This word will be _**bold and italic**_
"""
),
],
)
figure = vm.Page(
title="Figure",
layout=vm.Grid(grid=[[0, 1, 2, 3], [4, 5, 6, 7], [-1, -1, -1, -1], [-1, -1, -1, -1]]),
components=[vm.Figure(figure=figure) for figure in example_cards + example_reference_cards],
controls=[vm.Filter(column="Category")],
)
button = vm.Page(
title="Button",
layout=vm.Grid(grid=[[0], [0], [0], [0], [1]]),
components=[
vm.Graph(
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
size="petal_length",
),
),
vm.Button(
text="Export data",
actions=va.export_data(),
),
],
controls=[vm.Filter(column="species", selector=vm.Dropdown(title="Species"))],
)
containers = vm.Page(
title="Containers",
components=[
vm.Tabs(
tabs=[
vm.Container(
title="Default",
layout=vm.Grid(grid=[[0], [1]]),
components=[
vm.Container(
title="Container I",
components=[
vm.Graph(
title="Container I - Scatter",
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
marginal_y="violin",
marginal_x="box",
),
)
],
),
vm.Container(
title="Container II",
layout=vm.Grid(grid=[[0, 1]]),
components=[
vm.Graph(
title="Container II - Scatter",
figure=px.scatter(
iris,
x="sepal_length",
y="petal_width",
color="species",
),
),
vm.Graph(
title="Container II - Bar",
figure=px.bar(
iris,
x="sepal_length",
y="sepal_width",
color="species",
),
),
],
),
],
),
vm.Container(
title="Styled",
layout=vm.Grid(grid=[[0, 0], [1, 2]]),
components=[
vm.Container(
components=[
vm.Graph(
title="Container I - Scatter",
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
marginal_y="violin",
marginal_x="box",
),
)
],
variant="plain",
),
vm.Container(
components=[
vm.Graph(
title="Container II - Scatter",
figure=px.scatter(
iris,
x="sepal_length",
y="petal_width",
color="species",
),
),
],
variant="outlined",
),
vm.Container(
components=[
vm.Graph(
title="Container II - Bar",
figure=px.bar(
iris,
x="sepal_length",
y="sepal_width",
color="species",
),
),
],
variant="filled",
),
],
),
vm.Container(
title="Collapsible",
layout=vm.Flex(),
components=[
vm.Container(
title="Initially collapsed container",
components=[
vm.Graph(
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
marginal_y="violin",
marginal_x="box",
)
)
],
collapsed=True,
),
vm.Container(
title="Initially expanded container",
components=[
vm.Graph(
figure=px.scatter(
iris,
x="sepal_length",
y="petal_width",
color="species",
)
),
],
collapsed=False,
),
],
),
]
)
],
)
tab_1 = vm.Container(
title="Tab I",
components=[
vm.Graph(
figure=px.bar(
gapminder_2007,
title="Graph 1",
x="continent",
y="lifeExp",
color="continent",
),
),
vm.Graph(
figure=px.box(
gapminder_2007,
title="Graph 2",
x="continent",
y="lifeExp",
color="continent",
),
),
],
)
tab_2 = vm.Container(
title="Tab II",
components=[
vm.Graph(
figure=px.scatter(
gapminder_2007,
title="Graph 3",
x="gdpPercap",
y="lifeExp",
size="pop",
color="continent",
),
),
],
)
tabs = vm.Page(title="Tabs", components=[vm.Tabs(tabs=[tab_1, tab_2])], controls=[vm.Filter(column="continent")])
tooltip = vm.Page(
title="Tooltip",
layout=vm.Grid(grid=[[0], [0], [0], [1], [1], [1], [1], [1], [2]]),
components=[
vm.Card(
text="""
The `description` argument allows you to add helpful context to your components by displaying a small
info icon next to the component's title.
When users hover over the icon, a tooltip appears showing the text you provide.
You can add tooltips to any Vizro component that supports the title argument. The description accepts:
* A `string`, which uses the default info icon.
* A `Tooltip` model, which lets you customize the icon using any symbol from the
[Google Material Icons library](https://fonts.google.com/icons)
Tooltips are a clean, lightweight way to offer additional details without cluttering your dashboard.
"""
),
vm.Graph(
title="Relationships between Sepal Width and Sepal Length",
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
size="petal_length",
),
description="""
**The Iris dataset** includes measurements of 150 iris flowers across three types: Setosa, Versicolor,
and Virginica.
While all samples are labeled by type, they can appear similar when looking at just some features -
making it a useful dataset for exploring patterns and challenges in classification.
""",
),
vm.Button(
text="Export data",
actions=va.export_data(),
description="""
Use this button to export the filtered data from the Iris dataset.
""",
),
],
controls=[
vm.Filter(
column="species",
selector=vm.Dropdown(
title="Species",
description="""
Select one or more species to explore patterns
specific to Setosa, Versicolor, or Virginica.
""",
),
),
vm.Filter(
column="sepal_width",
selector=vm.RangeSlider(
title="Sepal Width",
description="""
Use the slider to filter flowers by sepal width.
Only samples within the selected range will be shown.
""",
),
),
],
description="""
This page provides overview of Tooltip functionality.
""",
)
# CONTROLS --------------------------------------------------------------------
filters = vm.Page(
title="Filters",
components=[
vm.Graph(
figure=px.scatter(
iris,
x="sepal_length",
y="petal_width",
color="species",
)
),
vm.Graph(
id="scatter_chart2",
figure=px.scatter(
iris,
x="petal_length",
y="sepal_width",
color="species",
),
),
],
controls=[
vm.Filter(
column="species",
selector=vm.Dropdown(),
),
vm.Filter(
column="petal_length",
targets=["scatter_chart2"],
selector=vm.RangeSlider(),
),
],
)
parameters = vm.Page(
title="Parameters",
components=[
vm.Graph(
id="scatter_chart_pm",
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
size="petal_length",
color_discrete_map={"setosa": "#00b4ff", "versicolor": "#ff9222"},
),
),
vm.Graph(
id="bar_chart_pm",
figure=px.bar(
iris,
x="sepal_width",
y="sepal_length",
color="species",
color_discrete_map={"setosa": "#00b4ff", "versicolor": "#ff9222"},
),
),
],
controls=[
vm.Parameter(
targets=["scatter_chart_pm.color_discrete_map.virginica", "bar_chart_pm.color_discrete_map.virginica"],
selector=vm.Dropdown(options=["#ff5267", "#3949ab"], multi=False, value="#3949ab"),
)
],
)
selectors = vm.Page(
title="Selectors",
layout=vm.Grid(grid=[[0], [1], [1], [1], [2], [2], [2], [3], [3], [3]], row_min_height="170px", row_gap="24px"),
components=[
vm.Card(
text="""
A selector can be used within the **Parameter** or **Filter** component to allow the user to select a value.
The following selectors are available:
* Dropdown (**categorical** multi and single option selector)
* Checklist (**categorical** multi option selector only)
* RadioItems (**categorical** single option selector only)
* RangeSlider (**numerical** multi option selector only)
* Slider (**numerical** single option selector only)
* DatePicker(**temporal** multi and single option selector)
"""
),
vm.Table(
id="table-gapminder",
figure=dash_data_table(data_frame=gapminder_2007, page_size=10),
title="Gapminder Data",
),
vm.Table(id="table-tips", figure=dash_data_table(data_frame=tips, page_size=10), title="Tips Data"),
vm.Graph(
id="graph-stocks",
figure=px.line(stocks, x="date", y="GOOG", title="Stocks Data"),
),
],
controls=[
vm.Filter(
targets=["table-gapminder"],
column="lifeExp",
selector=vm.RangeSlider(title="Range Slider (Gapminder - lifeExp)", step=1, marks=None),
),
vm.Filter(
targets=["table-gapminder"],
column="continent",
selector=vm.Checklist(title="Checklist (Gapminder - continent)"),
),
vm.Filter(
targets=["table-gapminder"],
column="country",
selector=vm.Dropdown(title="Dropdown (Gapminder - country)"),
),
vm.Filter(
targets=["table-gapminder"],
column="is_europe",
selector=vm.Switch(title="Is Europe?"),
),
vm.Filter(
targets=["table-tips"],
column="day",
selector=vm.Dropdown(title="Dropdown (Tips - day)", multi=False, value="Sat"),
),
vm.Filter(
targets=["table-tips"],
column="sex",
selector=vm.RadioItems(title="Radio Items (Tips - sex)"),
),
vm.Filter(
targets=["table-tips"],
column="size",
selector=vm.Slider(title="Slider (Tips - size)", step=1, value=2),
),
vm.Filter(targets=["graph-stocks"], column="date", selector=vm.DatePicker(title="Date Picker (Stocks - date)")),
],
)
controls_in_containers = vm.Page(
title="Controls in containers",
components=[
vm.Container(
layout=vm.Grid(grid=[[0, 1]]),
components=[
vm.Container(
components=[
vm.Graph(
figure=px.scatter(
iris,
x="sepal_width",
y="sepal_length",
color="species",
marginal_y="violin",
marginal_x="box",
),
)
],
controls=[
vm.Filter(column="species", selector=vm.Checklist()),
],
variant="outlined",
),
vm.Container(
components=[
vm.Graph(
figure=px.box(
gapminder_2007,
x="continent",
y="lifeExp",
color="continent",
custom_data=["continent"],
),
),
vm.Graph(
figure=px.scatter(
gapminder_2007,
x="gdpPercap",
y="lifeExp",
size="pop",
color="continent",
),
),
],
controls=[
vm.Filter(column="continent", selector=vm.RadioItems()),
],
variant="outlined",
),
],
),
],
)
# LAYOUT ------------------------------------------------------------------
grid_layout = vm.Page(
title="Grid layout",
layout=vm.Grid(grid=[[0, 0, 0, 0], [1, 1, 3, 3], [1, 1, 4, 4], [2, 2, 5, 5], [2, 2, 6, 6]]),
components=[
vm.Card(
text="""
### Card #1
Lorem ipsum dolor sit amet, consetetur sadipscing no sea elitr sed diam nonumy.
Sed diam voluptua. At vero eos et accusam et justo no duo dolores et ea rebum.
"""
),
vm.Card(
text="""
### Card #2
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
"""
),
vm.Card(
text="""
### Card #3
Sed diam voluptua. At vero eos et accusam et justo no duo dolores et ea rebum.
Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.
"""
),
vm.Card(
text="""
### Card #4
Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
"""
),
vm.Card(
text="""
### Card #5
Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
"""
),
vm.Card(
text="""
### Card #6
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.
"""
),
vm.Card(
text="""
### Card #7
Lorem ipsum dolor sit amet, consetetur sadipscing no sea elitr sed diam nonumy.
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
"""
),
],
description="""
Use Grid when you have a specific layout in mind—like a dashboard with clearly defined sections
(e.g. top summary row, bottom detail view).
""",
)
flex_layout = vm.Page(
id="flex-layout",
title="Flex layout",
layout=vm.Flex(
direction="row",
wrap=True,
),
components=[
vm.Card(
text="""
### Card #1
Lorem ipsum dolor sit amet, consetetur sadipscing no sea elitr sed diam nonumy.
Sed diam voluptua. At vero eos et accusam et justo no duo dolores et ea rebum.
"""
),
vm.Card(
text="""
### Card #2
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
"""
),
vm.Card(
text="""
### Card #3
Sed diam voluptua. At vero eos et accusam et justo no duo dolores et ea rebum.
Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.
"""
),
vm.Card(
text="""
### Card #4
Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
"""
),
vm.Card(
text="""
### Card #5
Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
"""
),
vm.Card(
text="""
### Card #6
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
Lorem ipsum dolor sit amet, consetetur sadipscing no sea est elitr dolor sit amet.
"""
),
vm.Card(
text="""
### Card #7
Lorem ipsum dolor sit amet, consetetur sadipscing no sea elitr sed diam nonumy.
Sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat.
"""
),
],
description="""
Use Flex when you want a responsive row of items that adjusts automatically—great for things like
dynamic card collections or tag-like elements that should flow naturally.
""",
)
# ACTIONS ---------------------------------------------------------------------
export_data_action = vm.Page(
title="Export data",
components=[
vm.Graph(figure=px.scatter(iris, x="petal_length", y="sepal_length", color="species")),
vm.Graph(figure=px.histogram(iris, x="petal_length", color="species")),
vm.Button(text="Export data", actions=va.export_data()),
],
controls=[vm.Filter(column="species")],
)
# CUSTOM CHARTS ------------------------------------------------------------------
@capture("graph")
def scatter_with_line(data_frame, x, y, hline=None, title=None):
"""Custom scatter chart based on px."""
fig = px.scatter(data_frame=data_frame, x=x, y=y, title=title)
fig.add_hline(y=hline, line_color="orange")
return fig
@capture("graph")
def waterfall(data_frame, measure, x, y, text, title=None):
"""Custom waterfall chart based on go."""
fig = go.Figure()
fig.add_traces(
go.Waterfall(
measure=data_frame[measure],
x=data_frame[x],
y=data_frame[y],
text=data_frame[text],
decreasing={"marker": {"color": "#ff5267"}},
increasing={"marker": {"color": "#08bdba"}},
totals={"marker": {"color": "#00b4ff"}},
)
)
fig.update_layout(title=title)
return fig
custom_charts = vm.Page(
title="Custom Charts",
components=[
vm.Graph(
id="custom_scatter",
figure=scatter_with_line(
x="sepal_length",
y="sepal_width",
hline=3.5,
data_frame=iris,
title="Custom px chart",
),
),
vm.Graph(
id="custom_waterfall",
figure=waterfall(
data_frame=waterfall_df,
measure="measure",
x="x",
y="y",
text="text",
title="Custom go chart",
),
),
],
controls=[
vm.Filter(column="petal_width", targets=["custom_scatter"]),
vm.Filter(
column="x",
targets=["custom_waterfall"],
selector=vm.Dropdown(title="Financial categories", multi=True),
),
],
)
# CUSTOM TABLE ------------------------------------------------------------------
@capture("table")
def my_custom_table(data_frame=None, chosen_columns: list[str] | None = None):
"""Custom table with added logic to filter on chosen columns."""
columns = [{"name": i, "id": i} for i in chosen_columns]
defaults = {
"style_as_list_view": True,
"style_data": {"border_bottom": "1px solid var(--bs-border-color)", "height": "40px"},
"style_header": {
"border_bottom": "1px solid var(--bs-border-color-translucent)",
"border_top": "None",
"height": "32px",
},
}
return dash_table.DataTable(data=data_frame.to_dict("records"), columns=columns, **defaults)
custom_tables = vm.Page(
title="Custom Tables",
components=[
vm.Table(
id="custom_table",
title="Custom Dash DataTable",
figure=my_custom_table(
data_frame=gapminder_2007,
chosen_columns=["country", "continent", "lifeExp", "pop", "gdpPercap"],
),
)
],
controls=[
vm.Parameter(
targets=["custom_table.chosen_columns"],
selector=vm.Dropdown(
title="Choose columns",
options=gapminder_2007.columns.to_list(),
multi=True,
),
)
],
)
# CUSTOM COMPONENTS -------------------------------------------------------------
# 1. Extend existing components
class TooltipNonCrossRangeSlider(vm.RangeSlider):
"""Custom numeric multi-selector `TooltipNonCrossRangeSlider`."""
type: Literal["other_range_slider"] = "other_range_slider"
def build(self):
"""Extend existing component by calling the super build and update properties."""
range_slider_build_obj = super().build()
range_slider_build_obj[self.id].allowCross = False
range_slider_build_obj[self.id].tooltip = {"always_visible": True, "placement": "bottom"}
return range_slider_build_obj
vm.Filter.add_type("selector", TooltipNonCrossRangeSlider)
# 2. Create new custom component
class Jumbotron(vm.VizroBaseModel):
"""New custom component `Jumbotron`."""
type: Literal["jumbotron"] = "jumbotron"
title: str
subtitle: str
text: str
def build(self):
"""Build the new component based on Dash components."""
return html.Div([html.H2(self.title), html.H3(self.subtitle), html.P(self.text)])
vm.Page.add_type("components", Jumbotron)
custom_components = vm.Page(
title="Custom Components",
components=[
Jumbotron(
title="Custom component based on new creation",
subtitle="This is a subtitle to summarize some content.",
text="This is the main body of text of the Jumbotron.",
),
vm.Graph(
id="for_custom_chart",
figure=px.scatter(
iris,
title="Iris Dataset",
x="sepal_length",
y="petal_width",
color="sepal_width",
),
),
],
controls=[
vm.Filter(
column="sepal_length",
targets=["for_custom_chart"],
selector=TooltipNonCrossRangeSlider(title="Custom component based on extension"),
)
],
)
# CUSTOM FIGURE ----------------------------------------------------------------
@capture("figure") # (1)!
def multiple_cards(data_frame: pd.DataFrame, n_rows: int | None = 1) -> html.Div:
"""Creates a list with a variable number of `vm.Card` components from the provided data_frame.
Args:
data_frame: Data frame containing the data.
n_rows: Number of rows to use from the data_frame. Defaults to 1.
Returns:
html.Div with a list of dbc.Card objects generated from the data.
"""
texts = data_frame.head(n_rows)["text"]
return html.Div(
[dbc.Card(dcc.Markdown(f"### Card #{i}\n{text}")) for i, text in enumerate(texts, 1)],
className="multiple-cards-container",
)
custom_figures = vm.Page(
title="Custom Figures",
components=[vm.Figure(id="my-figure", figure=multiple_cards(data_frame=custom_fig_df))],
controls=[
vm.Parameter(
targets=["my-figure.n_rows"],
selector=vm.Slider(min=2, max=12, step=2, value=8, title="Number of cards to display"),
),
],
)
kpi_indicators = vm.Page(
title="KPI Indicators",
layout=vm.Grid(grid=[[0, 1, 2, 3], [4, 5, 6, 7], [-1, -1, -1, -1], [-1, -1, -1, -1]]),
components=[vm.Figure(figure=figure) for figure in example_cards + example_reference_cards],
controls=[vm.Filter(column="Category")],
)
# DASHBOARD -------------------------------------------------------------------
components = [graphs, ag_grid, table, cards, figure, button, containers, tabs, tooltip]
controls = [filters, parameters, selectors, controls_in_containers]
actions = [export_data_action]
layout = [grid_layout, flex_layout]
extensions = [custom_charts, custom_tables, custom_figures, custom_components]
dashboard = vm.Dashboard(
title="Vizro Features",
pages=[home, *components, *controls, *actions, *layout, *extensions],
navigation=vm.Navigation(
nav_selector=vm.NavBar(
items=[
vm.NavLink(label="Homepage", pages=["Homepage"], icon="Home"),
vm.NavLink(
label="Features",
pages={
"Components": [
"Graphs",
"AG Grid",
"Table",
"Cards",
"Figure",
"Button",
"Containers",
"Tabs",
"Tooltip",
],
"Controls": ["Filters", "Parameters", "Selectors", "Controls in containers"],
"Layout": ["Grid layout", "flex-layout"],
"Actions": ["Export data"],
"Extensions": [
"Custom Charts",
"Custom Tables",
"Custom Components",
"Custom Figures",
],
},
icon="Library Add",
),
]
)
),
)
if __name__ == "__main__":
# Move app definition outside of __main__ block for the HF demo to work
app = Vizro().build(dashboard)
app.dash.layout.children.append(
dbc.NavLink(
["Made with ", html.Img(src=get_asset_url("logo.svg"), id="banner", alt="Vizro logo"), "vizro"],
href="https://github.com/mckinsey/vizro",
target="_blank",
class_name="anchor-container",
)
)
app.run()