问为什么group_by -> filter ->汇总在R中比pandas快？

EN

df = data.frame(col_a = sample(letters[1:3],20,T),
           col_b = sample(1:2,20,T),
             col_c = sample(letters[1:2],20,T),
             col_d = sample(c(4,2),20,T)
             )

microbenchmark::microbenchmark(
a = df %>% 
  group_by(col_a, col_b) %>% 
  summarise(
    a = sum(col_c == 'a'),
    b = sum(col_c == 'b'),
    c = a/b
  ) %>% 
  ungroup()
)

df = pd.DataFrame({
    'col_a': np.random.choice(['a','b','c'],N),
    'col_b': np.random.choice([1,2],N),
    'col_c': np.random.choice(['a', 'b'],N),
    'col_d': np.random.choice(['4', '2'],N),
})
%%timeit 
df1 = df.groupby(['col_a', 'col_b']).agg({
    'col_c':[
        ('a',lambda x: (x=='a').sum()),
        ('b',lambda x: (x=='b').sum())
    ]}).reset_index()
df1['rat'] = df1.col_c.a/df1.col_c.b