Fastest way to merge pandas dataframe on ranges

Question

I have a dataframe A

    ip_address
0   13
1   5
2   20
3   11
.. ........

and another dataframe B

Answer 1

IntervalIndex is as of pandas 0.20.0 and the solution by @JohnGalt using it is excellent.

Prior to that version, this solution would work which expands the ip addresses by country for the complete range.

df_ip = pd.concat([pd.DataFrame(
    {'ip_address': range(row['lowerbound_ip_address'], row['upperbound_ip_address'] + 1), 
     'country': row['country']}) 
    for _, row in dfb.iterrows()]).set_index('ip_address')
>>> dfa.set_index('ip_address').join(df_ip)
              country
ip_address           
13              China
5           Australia
20              China
11              China