Streamlit Altair

Streamlit Altair is an incredibly powerful library that allows developers to create stunning visualizations with just a few lines of code. Altair is a declarative visualization library for creating interactive visualizations in Python.

Key Features

• Easy-to-use, declarative syntax for visualizing data
• Interactive charts that allow for exploration of data
• Customizable, with a wide range of customization options available
• Supports a variety of data types, including data frames and CSV files
• Seamless integration with Streamlit, allowing for easy deployment and sharing

Getting Started

To get started with Streamlit Altair, you'll need to install the library:

!pip install streamlit-altair

Once you've installed the library, you can create your first visualization:

import altair as alt
from vega_datasets import data

source = data.cars()

brush = alt.selection(type='interval')

points = alt.Chart(source).mark_point().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color=alt.condition(brush, 'Origin', alt.value('lightgray'))
).add_selection(
    brush
)

bars = alt.Chart(source).mark_bar().encode(
    y='Origin',
    color='Origin',
    x='count(Origin)'
).transform_filter(
    brush
)

points & bars

Conclusion

Streamlit Altair is a powerful library that allows you to create stunning visualizations with just a few lines of code. It's easy to use, customizable, and integrates seamlessly with Streamlit for easy deployment and sharing. Give it a try and see what you can create!