def _estimates_from_one_grid(field_df):
    """Given a dataframe with all var draws for a single field, return
    one var table with mean and standard deviation."""
    # Exclude mulstd to get just the grid values.
    exclude_mulstd = field_df[~field_df.var_type.str.startswith("mulstd")]
    grid_df = exclude_mulstd.set_index("fit_var_id")
    # Gives grid with one age-time for each var_id.
    with_at = grid_df[["age", "time"]].groupby(level=0).mean()
    var_only = grid_df[["fit_var_value"]].groupby(level=0)
    with_mean = var_only.mean().rename(columns={"fit_var_value": "mean"})
    with_std = var_only.std().rename(columns={"fit_var_value": "std"})
    # This makes columns: ["age", "time", "mean", "std"]
    return with_at.join(with_mean).join(with_std)