streamlit_rendering.py

import streamlit as st


def filter_dataframe(
    dfs,
    filter_columns,
    key_prefix="filter_dataframe",
    header=None,
):
    """
    Create cascading selectboxes in two rows to filter a DataFrame.

    Args:
        dfs (pd.DataFrame): DataFrame to filter, OR a list of frames to filter.
        filter_columns (list): Columns to filter on.

    Returns:
        pd.DataFrame: Filtered DataFrame.
    """
    keys = [
        f"{key_prefix}_{i}" for i in range(len(filter_columns))
    ]  ## so that we can have multiple layers of filter on same page

    dfs = ensure_list(dfs)
    df = dfs[0]

    selected_values = {}

    if header:
        st.markdown(header)
    cols1 = st.columns(len(filter_columns))
    for i, col_name in enumerate(filter_columns):
        unique_values = df[col_name].dropna().unique()
        selected_value = cols1[i].selectbox(
            col_name, options=sorted(unique_values), key=keys[i], index=0
        )
        selected_values[col_name] = selected_value
        dfs = [df[df[col_name] == selected_value] for df in dfs]
        df = dfs[0]

    return (
        (dfs[0], selected_values)
        if len(dfs) == 1
        else [(df, selected_values) for df in dfs]
    )


def ensure_list(x):
    return x if isinstance(x, list) else [x]