Testes: Streamlit com Altair e Vega Datasets

altair.py

# Antes de rodar:

# pip install streamlit altair vega_datasets
# streamlit run altair.py

import streamlit as st
import altair as alt
from vega_datasets import data

cars = data.cars()

"""
# Teste de Datasets Altair com Streamlit
"""

st.markdown('## HP x Milhas por galão x Cilindros')
hp_ml_cyl = alt.Chart(cars).mark_point().properties(width=600, height=400).encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
    color='Cylinders:O'
)
st.write(hp_ml_cyl)

st.markdown('---')

st.markdown('## HP x Milhas por galão x Origem')
hp_ml_origin = alt.Chart(cars).mark_point().properties(width=600, height=400).encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
    color='Origin:N'
)
st.write(hp_ml_origin)

st.markdown('---')

st.markdown('## HP x Milhas por galão x Origem com seletor')

st.markdown('Clique e arraste nos gráficos, para destacar a seleção.')

selection = alt.selection_interval()

chart = alt.Chart(cars).mark_point().properties(width=270, height=270).encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
    color=alt.condition(selection,
                        'Origin:N',
                        alt.value('gray'))
).add_selection(
    selection
)

hist = alt.Chart(cars).mark_bar().encode(
    alt.X('count()', title='Quantidade de Carros'),
    alt.Y('Origin', title='País de Origem'),
    color='Origin'
).transform_filter(
    selection
).properties(width=600)

st.write((chart | chart.encode(x='Acceleration:Q')) & hist)

"""
## Referências
- Grammar of Graphics: https://towardsdatascience.com/a-comprehensive-guide-to-the-grammar-of-graphics-for-effective-visualization-of-multi-dimensional-1f92b4ed4149?gi=b36667dc3c1d
- Altair: https://altair-viz.github.io/index.html
"""