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# Copied from https://github.com/domoritz/streamlit-vega-lite | |
import altair as alt | |
import streamlit as st | |
import pandas as pd | |
import numpy as np | |
from streamlit_vega_lite import vega_lite_component, altair_component | |
hist_data = pd.DataFrame(np.random.normal(42, 10, (200, 1)), columns=["x"]) | |
def altair_histogram(): | |
brushed = alt.selection_interval(encodings=["x"], name="brushed") | |
return ( | |
alt.Chart(hist_data) | |
.mark_bar() | |
.encode(alt.X("x:Q", bin=True), y="count()") | |
.add_selection(brushed) | |
) | |
event_dict = altair_component(altair_chart=altair_histogram()) | |
r = event_dict.get("x") | |
if r: | |
filtered = hist_data[(hist_data.x >= r[0]) & (hist_data.x < r[1])] | |
st.write(filtered) | |