Perhaps you are looking for pandas.cut:
import pandas as pd
import numpy as np
df = pd.DataFrame(np.arange(50), columns=['filtercol'])
filter_values = [0, 5, 17, 33]
out = pd.cut(df.filtercol, bins=filter_values)
counts = pd.value_counts(out)
# counts is a Series
print(counts)
yields
(17, 33] 16
(5, 17] 12
(0, 5] 5
To reorder the result so the bin ranges appear in order, you could use
counts.sort_index()
which yields
(0, 5] 5
(5, 17] 12
(17, 33] 16
Thanks to nivniv and InLaw for this improvement.
See also Discretization and quantiling.