def sep_nondummies(data):
    """
    Finds the features that are:
        1. have nominal values
        2. have more than 2 distinct values so it needs to be dummified

    Args:
        data: DataFrame containing the dataset

    Returns:
        nominal: Array-like structure that contains the nominal features
        continuous: Array-like structure that contains the names of all the continuous features
    """
    nominal = []
    continuous=[]
    for col in data.columns:
        distinct = data[col].dropna().nunique()
        if distinct > 10:
            continuous.append(col)  
        elif distinct > 2:  
            nominal.append(col) 
    return [nominal, continuous]