def create_dicts_w_info(df, x_label, column_label):
    """
    This function is used to create a dictionary that can be easily converted to a
    graphical representation based on the values for a particular dataframe
    
    Parameters
    ----------
    df (dataframe): dataframe that contains the information to be converted
    
    x_label (string): the column of the dataframe whose rows will then be converted
        to they keys of a dictionary
    
    column_label (string): the column that contains the data quality metric being
        investigated
    
    Returns
    -------
    data_qual_info (dictionary): has the following structure
        
        keys: the column for a particular dataframe that represents the elements that
            whose data quality is being compared (e.g. HPOs, different measurement/unit
            combinations)
        
        values: the data quality metric being compared
    """
    rows = df[x_label].unique().tolist()

    data_qual_info = {}

    for row in rows:
        sample_df = df.loc[df[x_label] == row]

        data = sample_df.iloc[0][column_label]

        data_qual_info[row] = data

    return data_qual_info