How do I get dataframe row-selections from a user?

At the moment, st.dataframe and st.data_editor do not natively support passing user-selected rows to the Python backend. We are working to support this in the future. For now, if you need to get row-selections from a user, you can accomplish this by adding an extra Checkbox column) to your dataframe and using st.data_editor. You can use this extra column to collect a user's selection(s).

Example

In the following example, we define a function which accepts a dataframe and returns the rows selected by a user. Within the function, the dataframe is copied to prevent mutating it. We insert a temporary "Select" column into the copied dataframe before passing the copied data into st.data_editor. We have disabled editing for all other columns, but you can make them editable if desired. After filtering the dataframe and dropping the temporary column, our function returns the selected rows.

import streamlit as st
import numpy as np
import pandas as pd

df = pd.DataFrame(
    {
        "Animal": ["Lion", "Elephant", "Giraffe", "Monkey", "Zebra"],
        "Habitat": ["Savanna", "Forest", "Savanna", "Forest", "Savanna"],
        "Lifespan (years)": [15, 60, 25, 20, 25],
        "Average weight (kg)": [190, 5000, 800, 10, 350],
    }
)

def dataframe_with_selections(df):
    df_with_selections = df.copy()
    df_with_selections.insert(0, "Select", False)

    # Get dataframe row-selections from user with st.data_editor
    edited_df = st.data_editor(
        df_with_selections,
        hide_index=True,
        column_config={"Select": st.column_config.CheckboxColumn(required=True)},
        disabled=df.columns,
    )

    # Filter the dataframe using the temporary column, then drop the column
    selected_rows = edited_df[edited_df.Select]
    return selected_rows.drop('Select', axis=1)


selection = dataframe_with_selections(df)
st.write("Your selection:")
st.write(selection)

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