def uniform_draw_feat_class(data_df, target_name, draw_size):
    """ Sample out 1 particular class out of the full data uniformly in a predefined sample size,
    segregate pandas dataframe into their respective target classes. """
    target_class_dfs = {}
    n_classes = data_df[target_name].unique()
    for unique_class in n_classes:
        class_i_df = data_df[data_df[target_name] == unique_class]
        class_i_df = class_i_df.reset_index().drop(columns=['index'])
        target_class_dfs[unique_class] = class_i_df
    uniform_class_sample_draws = {}
    for unique_class in n_classes:
        unif_samples = target_class_dfs[unique_class].sample(n=draw_size,
            replace=True)
        uniform_class_sample_draws[unique_class] = unif_samples
    return uniform_class_sample_draws
