import polars as pl
import pandas as pd
from typing import Union, Optional, List
import io

def education_access_analysis(
    data: Union[str, pd.DataFrame, pl.DataFrame, io.BytesIO],
    enrollment_col: Optional[str] = None,
    attendance_col: Optional[str] = None,
    population_school_age_col: Optional[str] = None
) -> pl.DataFrame:
    """
    Education Access Analysis
    =========================

    What
    ----
    Compute access indicators (enrollment, attendance) vs school-age population.

    When
    ----
    Education monitoring and planning.

    Why
    ---
    Find coverage gaps for children and youth.

    Parameters
    ----------
    data : str | pd.DataFrame | pl.DataFrame | io.BytesIO
        Input dataset.
    enrollment_col : str | None
        Enrollment count.
    attendance_col : str | None
        Attendance count.
    population_school_age_col : str | None
        School-age population.

    Returns
    -------
    pl.DataFrame
        Placeholder rates and gaps.
    """
    if isinstance(data, str):
        df = pl.read_csv(data)
    elif isinstance(data, io.BytesIO):
        df = pl.read_csv(data)
    elif isinstance(data, pd.DataFrame):
        df = pl.from_pandas(data)
    elif isinstance(data, pl.DataFrame):
        df = data
    else:
        raise TypeError("Unsupported data type")
    return df.with_columns([
        pl.lit(0.0).alias("enrollment_rate_placeholder"),
        pl.lit(0.0).alias("attendance_rate_placeholder"),
    ])
