Assuming you have numpy import numpy as np, then you can do:
n_rows = len(df.index)
filter = np.full(n_rows, True)

filter = (
    filter
    & (df['Owner'].isin(owner_filter))
    & (df['Country'].isin(country_filter))
    & (df['Client'].isin(client_filter))
)

and then your filtered df will be df[filter].
One thing that’s different in the code I currently have is in generating the unique set of options for each filter - I had to do unique().tolist().