def consolidate_shares(df):
    if df.empty:
        raise ValueError("Empty dataframe provided")
    
    # Pre-calculate sums to avoid redundant computation
    block_sums = df.sum()
    total_sum = block_sums.sum()
    
    if total_sum == 0:
        raise ValueError("No shares found in any block")
    
    consolidated = pd.DataFrame()
    for block in df.columns:
        block_sum = block_sums[block]
        if block_sum == 0:
            continue
        
        # Calculate weighted ownership for this block
        consolidated[block] = (df[block] / block_sum) * block_sum
    
    # Calculate final weighted average
    consolidated["total"] = consolidated.sum(axis=1) / total_sum
    return consolidated