streamlit-advanced-dataframe

Streamlit's st.dataframe with advanced features using TanStack Table.

Installation

pip install streamlit-advanced-dataframe

Usage

import pandas as pd
from streamlit_advanced_dataframe import advanced_dataframe

df = pd.DataFrame({
    "name": ["Alice", "Bob", "Charlie"],
    "age": [25, 30, 35],
    "city": ["Tokyo", "Osaka", "Kyoto"]
})

# Basic usage
advanced_dataframe(data=df, height=400, key="my_table")

# Single row selection
selected = advanced_dataframe(
    data=df,
    selection_mode="single-row",
    key="selectable_table"
)
if selected:
    st.write(f"Selected rows: {selected}")  # Returns list[int]

# Multi-row selection
selected = advanced_dataframe(
    data=df,
    selection_mode="multi-row",
    key="multi_selectable_table"
)
if selected:
    st.dataframe(df.iloc[selected])  # Show selected rows

# Filter columns
advanced_dataframe(
    data=df,
    filterable_columns=["name", "age", "city"],
    show_row_count=True,
    key="filterable_table"
)

# Header groups
advanced_dataframe(
    data=df,
    header_groups=[
        {"header": "Personal Info", "columns": ["name", "age"]},
        {"header": "Location", "columns": ["city"]}
    ],
    key="grouped_table"
)

# Column config (prefix/suffix)
df_sales = pd.DataFrame({
    "product": ["Product A", "Product B"],
    "price": [1000, 2000],
    "discount": [10, 20]
})
advanced_dataframe(
    data=df_sales,
    column_config={
        "price": {"prefix": "$"},
        "discount": {"suffix": "%"}
    },
    key="config_table"
)

Parameters

Returns

list[int] - List of selected row indices (0-based). Returns an empty list [] when no rows are selected or selection_mode is None.