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Get started with Vizro

This tutorial introduces Vizro. It is a step-by-step guide to create a first dashboard and is designed to equip you with the knowledge to explore the documentation further.

If you want a more complete tutorial exploring more of the available features, please see the Explore Vizro tutorial.

Let's get started!

1. Install Vizro and its dependencies

If you haven't already installed Vizro, follow the installation guide to do so inside a virtual environment.

If you consider yourself a beginner to python and/or virtual environments, there is also a section that avoids any use of terminals and relies only upon a graphical user interface.

2. Open a Jupyter notebook

A good way to initially explore Vizro is from inside a Jupyter notebook. If you haven't used one of these before, you may need to install the Jupyter package:

pip install jupyter

From the terminal window, with the virtual environment you installed Vizro in active, start a new notebook as follows:

jupyter notebook

The command opens a browser tab and you can navigate to your preferred folder for this new project. Create a new notebook Python 3 (ipykernel) notebook from the "New" dropdown.

Beginners/Code novices

If you followed the beginners steps in the the installation guide, you should already be set, and you can continue below.

Confirm that Vizro is installed by typing the following into a cell in the notebook and running it.

import vizro

print(vizro.__version__)

You should see a return output of the form 0.1.0.

3. Create your first dashboard

You can now paste the below example into a jupyter notebook cell (or a python script), run it, and see the results.

Dashboard Configuration Syntaxes

import vizro.plotly.express as px
from vizro import Vizro
import vizro.models as vm

df = px.data.iris()

page = vm.Page(
    title="My first dashboard",
    components=[
        vm.Graph(id="scatter_chart", figure=px.scatter(df, x="sepal_length", y="petal_width", color="species")),
        vm.Graph(id="hist_chart", figure=px.histogram(df, x="sepal_width", color="species")),
    ],
    controls=[
        vm.Filter(column="species", selector=vm.Dropdown(value=["ALL"])),
    ],
)

dashboard = vm.Dashboard(pages=[page])

Vizro().build(dashboard).run()

Dashboard

After running the dashboard, you can access the dashboard by typing localhost:8050 in the browser of your choice.

4. Explore further

You are now ready to explore our documentation further, as you can now easily evaluate all examples.

One place to start would be the more complete Explore Vizro tutorial.