Merge pandas dataframes where one value is between two others

Question

I need to merge two pandas dataframes on an identifier and a condition where a date in one dataframe is between two dates in the other dataframe.

Dataframe A has a date ("fdate") and an ID ("cusip"):

I need to merge this with this dataframe B:

on A.cusip==B.ncusip and A.fdate is between B.namedt and B.nameenddt.

In SQL this would be trivial, but the only way I can see how to do this in pandas is to first merge unconditionally on the identifier, and then filter on the date condition:

df = pd.merge(A, B, how='inner', left_on='cusip', right_on='ncusip')
df = df[(df['fdate']>=df['namedt']) & (df['fdate']<=df['nameenddt'])]

Is this really the best way to do this? It seems that it would be much better if one could filter within the merge so as to avoid having a potentially very large dataframe after the merge but before the filter has completed.

Answer 1

As you say, this is pretty easy in SQL, so why not do it in SQL?

import pandas as pd
import sqlite3

#We'll use firelynx's tables:
presidents = pd.DataFrame({"name": ["Bush", "Obama", "Trump"],
                           "president_id":[43, 44, 45]})
terms = pd.DataFrame({'start_date': pd.date_range('2001-01-20', periods=5, freq='48M'),
                      'end_date': pd.date_range('2005-01-21', periods=5, freq='48M'),
                      'president_id': [43, 43, 44, 44, 45]})
war_declarations = pd.DataFrame({"date": [datetime(2001, 9, 14), datetime(2003, 3, 3)],
                                 "name": ["War in Afghanistan", "Iraq War"]})
#Make the db in memory
conn = sqlite3.connect(':memory:')
#write the tables
terms.to_sql('terms', conn, index=False)
presidents.to_sql('presidents', conn, index=False)
war_declarations.to_sql('wars', conn, index=False)

qry = '''
    select  
        start_date PresTermStart,
        end_date PresTermEnd,
        wars.date WarStart,
        presidents.name Pres
    from
        terms join wars on
        date between start_date and end_date join presidents on
        terms.president_id = presidents.president_id
    '''
df = pd.read_sql_query(qry, conn)

df:

         PresTermStart          PresTermEnd             WarStart  Pres
0  2001-01-31 00:00:00  2005-01-31 00:00:00  2001-09-14 00:00:00  Bush
1  2001-01-31 00:00:00  2005-01-31 00:00:00  2003-03-03 00:00:00  Bush