python assign value to pandas df if falls between range of dates in another df

Question

What is the best way to create a new column and assign a value if date falls between two dates in another dataframe ?

e.g.

dataframe A    
date             


        

Answer 1

This is an example of something that's really straightforward to do in one step in sql, but not so much in Pandas. So with the proviso that I don't love this approach, here it is.

1. do a full cartesian join
2. filter down to desired rows & columns.

_

# First Full Outer Join Dataframes 
# (Requires a Common Column in Pandas Unlike SQL)
df_A['fake key'] = 1
df_B['fake key'] = 1
outer_join = pd.merge(df_A, df_B, how='outer', on='fake key')

# Now Filter Back down to Desired Rows/Columns
desired_rows    = outer_join.query('date < end and date > start')
desired_columns = ['date', 'values', 'id']

final = desired_rows[desired_columns]
final

output:

        date values  id
0 2017-05-16      x  34
5 2017-04-12      y  32

The things that make this answer somewhat unsatisfying to me are:

1. The first step of a full cartesian join doesn't scale well at all to large data
2. The cartesian join requires a common column, so in this case first creating that fake key column (see this github issue