如果您已经拥有两个数据帧，您应该能够将它们合并到一个新的数据帧中并过滤/子集结果.

If you have already got to the point where you have the two dataframes you should be able to merge them into a new dataframe and filter/subset the result.

set.seed(1234) # for reproducibility

# "The written data table is a list containing an index, an easting,
# a northing and the predicted rainfall value"
# Create a simple data frame containing made-up data
mydf1 <- data.frame(index = 1:10,
                    easting = c(1, 1, 3, 4, 5, 5, 5, 5, 6, 6),
                    northing = c(12, 13, 13, 13, 14, 14, 15, 17, 18, 20),
                    predicted = runif(10, 500, 1000))

# "...comparing the data to another file that contains the same grid
# and the average yearly rainfall"
# Second data frame is similar, but has rainfall instead of predicted
mydf2 <- data.frame(index = 1:10,
                    easting = c(1, 1, 3, 4, 5, 5, 5, 5, 6, 6),
                    northing = c(12, 13, 13, 13, 14, 14, 15, 17, 18, 20),
                    rainfall = c(runif(9, 500, 1000), -9999))

# If data frames are of same size and have mostly common columns,
# merging them probably makes it easy to manipulate the data
mydf.merged <- merge(mydf1, mydf2)

# Finally, filter the merged data frame so that it only contains
# rainfall values that are not the -9999 value that denotes sea
mydf.final <- mydf.merged[mydf.merged$rainfall > -9999, ]

这是第一个数据框:

> mydf1
   index easting northing predicted
1      1       1       12  556.8517
2      2       1       13  811.1497
3      3       3       13  804.6374
4      4       4       13  811.6897
5      5       5       14  930.4577
6      6       5       14  820.1553
7      7       5       15  504.7479
8      8       5       17  616.2753
9      9       6       18  833.0419
10    10       6       20  757.1256
> 

这是第二个数据框:

> mydf2
   index easting northing   rainfall
1      1       1       12   846.7956
2      2       1       13   772.4874
3      3       3       13   641.3668
4      4       4       13   961.7167
5      5       5       14   646.1579
6      6       5       14   918.6478
7      7       5       15   643.1116
8      8       5       17   633.4104
9      9       6       18   593.3614
10    10       6       20 -9999.0000
> 

合并数据框:

> mydf.merged
   index easting northing predicted   rainfall
1      1       1       12  556.8517   846.7956
2     10       6       20  757.1256 -9999.0000
3      2       1       13  811.1497   772.4874
4      3       3       13  804.6374   641.3668
5      4       4       13  811.6897   961.7167
6      5       5       14  930.4577   646.1579
7      6       5       14  820.1553   918.6478
8      7       5       15  504.7479   643.1116
9      8       5       17  616.2753   633.4104
10     9       6       18  833.0419   593.3614
> 

删除了 -9999 行的最终数据框:

Final dataframe with -9999 row removed:

> mydf.final
   index easting northing predicted rainfall
1      1       1       12  556.8517 846.7956
3      2       1       13  811.1497 772.4874
4      3       3       13  804.6374 641.3668
5      4       4       13  811.6897 961.7167
6      5       5       14  930.4577 646.1579
7      6       5       14  820.1553 918.6478
8      7       5       15  504.7479 643.1116
9      8       5       17  616.2753 633.4104
10     9       6       18  833.0419 593.3614
>