def similarity(v1_df, v2_df):
    v1_value = v1_df.values[0]
    v2_value = v2_df.values[0]
    print('v1_value', v1_value)
    print('v2_value', v2_value)
    s1 = pd.Series(list(v1_value))
    s2 = pd.Series(list(v2_value))
    res = s1.corr(s2)
    print(res)
    corr = pearson_product_moment_correlation_coefficien(v1_value, v2_value)
    print('pearson_product_moment_correlation_coefficien', corr)
    corr = spearman_rank_correlation_coefficient(v1_value, v2_value)
    print('spearman_rank_correlation_coefficient', corr)
    corr = kendalltau_rank_correlation_coefficient(v1_value, v2_value)
    print('kendalltau_rank_correlation_coefficient', corr)
    e_distance = euclidean_distance(v1_value, v2_value)
    print('e_distance', e_distance)
    return cos_similarity(v1_value, v2_value)
def similarity(v1_df, v2_df):
    v1_value = v1_df.values[0]
    v2_value = v2_df.values[0]
    print('v1_value', v1_value)
    print('v2_value', v2_value)
    s1 = pd.Series(list(v1_value))
    s2 = pd.Series(list(v2_value))
    res = s1.corr(s2)
    print(res)
    corr = pearson_product_moment_correlation_coefficien(v1_value, v2_value)
    print('pearson_product_moment_correlation_coefficien', corr)
    corr = spearman_rank_correlation_coefficient(v1_value, v2_value)
    print('spearman_rank_correlation_coefficient', corr)
    corr = kendalltau_rank_correlation_coefficient(v1_value, v2_value)
    print('kendalltau_rank_correlation_coefficient', corr)
    e_distance = euclidean_distance(v1_value, v2_value)
    print('e_distance', e_distance)
    return cos_similarity(v1_value, v2_value)