R - Cutting a data frame by two columns

Question

I am trying to categorise location points according to their distance and bearing from the first point in a data frame. This code is working, however it only checks the distances from df$dist column.

df$circle_id = cut(df$dist, seq(0,41000000,1000), labels=FALSE, include.lowest=TRUE)

What I want to do is also check if the bearing of points is the same, and only then they can be put in the same category. Bearings are stored in df$bearing.

Simply put, I need to combine these two operations into one:

df$circle_id = cut(df$dist, seq(0,41000000,1000), include.lowest=TRUE)
df$circle_id = cut(df$bearing, seq(-180,180,10), labels=FALSE, include.lowest=TRUE)

Sample data frame:

 latitude longitude sensor_time circle_id segment_id  weight        dist    bearing
1 48.15144  17.07569  1447149703         1          1      2    0.000000 -180.00000
3 48.15404  17.07452  1447149743         3          1      1  302.422843  163.22826
4 48.15277  17.07514  1447149762         2          1      1  153.179367  164.50437
5 48.15208  17.07538  1447149771         1          1      1   74.666669  161.91792
6 48.15461  17.07560  1447149773         3          1      3  353.106770  178.87100
9 48.15139  17.07562  1447149811         1          1      2    7.828957   43.83916

Any help is appreciated, thank you

Answer 1

When you set the labels parameter to FALSE, the cut-function will return integers. An example:

> x <- sample(1:10)
> cut(x, seq(0,10,2))
 [1] (6,8]  (8,10] (2,4]  (4,6]  (2,4]  (0,2]  (8,10] (0,2]  (6,8]  (4,6] 
Levels: (0,2] (2,4] (4,6] (6,8] (8,10]
> cut(x, seq(0,10,2), labels = FALSE)
 [1] 4 5 2 3 2 1 5 1 4 3

Answer 2

I have made the two cuts sequentially and then ordered by cut1, cut2, setting labels=FALSE.