import numpy as np
import pandas as pd

uniques = [[1, 3], [5, 9]]
df_values = [[2,5,7,1,3,6,0,5],
            [1,3,4,5,6,7,8,9],
            [3,9,9,9,9,9,9,9],
            [1,3,4,5,6,7,8,9]]


df = pd.DataFrame([])
for combi in uniques:
    a, b = combi[0], combi[1]
    x = len([1 for row in df_values if a in row and b in row])
    res = pd.DataFrame([a, b, x])
    df = pd.concat([df, res], axis=0, ignore_index=True)

print(df)

Please note, that numpy.isin may come up with different results.