Selecting rows based on criteria from another dataframe

Question

I have two DataFrames with different numbers of rows and columns, but which have at least one column containing some common information. Specifically, StationCode is always a LocationCode :

dataframe1.head()

   DistanceToPrev LineCode  SeqNum StationCode           StationName  RailTime
0               0       RD       1         A15           Shady Grove         0
1           14151       RD       2         A14             Rockville         4
2           10586       RD       3         A13             Twinbrook         3
3            5895       RD       4         A12           White Flint         3
4            7309       RD       5         A11  Grosvenor-Strathmore         3
5           11821       RD       6         A10        Medical Center         3
6            5530       RD       7         A09              Bethesda         2
7            9095       RD       8         A08    Friendship Heights         3
8            4135       RD       9         A07         Tenleytown-AU         2
9            5841       RD      10         A06          Van Ness-UDC         2

dataframe2.head()

     Car Destination DestinationCode DestinationName Group Line LocationCode                LocationName  Min
0     8    Glenmont             B11        Glenmont     1   RD          A01                Metro Center  BRD
28    8    Glenmont             B11        Glenmont     1   RD          B01        Gallery Pl-Chinatown  ARR
35    6    Glenmont             B11        Glenmont     1   RD          A14                   Rockville    1
45    8    Glenmont             B11        Glenmont     1   RD          B02            Judiciary Square    2
62    6    Glenmont             B11        Glenmont     1   RD          B07                      Takoma    3
80    6    Glenmont             B11        Glenmont     1   RD          A13                   Twinbrook    4
82    8    Glenmont             B11        Glenmont     1   RD          B03               Union Station    4
95    6    Glenmont             B11        Glenmont     1   RD          B08               Silver Spring    5
114   8    Glenmont             B11        Glenmont     1   RD          B35              NoMa-Gallaudet    6
129   6    Glenmont             B11        Glenmont     1   RD          A12                 White Flint    7
143   8    Glenmont             B11        Glenmont     1   RD          B04  Rhode Island Ave-Brentwood    8

I want to get only the rows in dataframe2 whose Min column has a value less than RailTime column in dataframe1 for the same StationCode that matches the LocationCode .

For example the row labeled 80 in dataframe2 has LocationCode A13 and Min 4. In dataframe1 StationCode A13 has RailTime 4, so that row should be ex cluded from dataframe2 .

On the contrary, the row labeled 35 in dataframe2 has LocationCode A14 and a Min value of 1, which is less than the RailTime value for A14 from dataframe1 , so it should be in cluded.

Answer 1

Simple solution would be:

df2 = df2.merge(df1[['StationCode', 'RailTime']], left_on='LocationCode', right_on='StationCode')
df2 = df2[df2.Min<df2.RailTime]