Unable to calculate correct median value in R

I'm currently importing data from a SQLite database into R so that I can bin the values that are contained within it, specifically values within the range of 100 to 150. I'm trying to bin the values into bins of 0.001 before the median of the values is taken, so for example:-

> head(mzDiff150)
  abs(diffs)
1   100.0008
2   100.0158
3   100.0212
4   100.0233
5   100.0327
6   100.0364

These values that make up the head of my data should be binned into bins of 0.001 as so:-

(100,100.001] (100.001,100.002] (100.002,100.003] 
    100.0008               N/A               N/A          etc     

So from looking at my data I shouldn't have values in a lot of bins, i.e. a lot of N/As, which is fine. However, I get the following results:-

(100,100.001] (100.001,100.002] (100.002,100.003] (100.003,100.004] (100.004,100.005] (100.005,100.006] 
     100.0005          100.0015          100.0025          100.0035          100.0045          100.0055 

which I don't get as there shouldn't be any values that fall within those bin ranges. The data is all sorted as well. This is the code that I perform:-

> library(DBI)
> con <- dbConnect(RSQLite::SQLite(), dbname = "diffs.sqlite")
> tables <- dbListTables(con)
> mzDiff150 <- dbGetQuery(conn = con, statement = paste("SELECT `abs(diffs)` FROM mzdiff where `abs(diffs)` <= 150 and `abs(diffs)` > 100 ", sep = ","))
> bin <- seq(100, 150, by = 0.001)
> binnedData <- tapply(mzDiff150[, 1], cut(mzDiff150[, 1], breaks = bin), median)

I feel like the mistake is obvious but I can't see where it is. Can anyone see where I'm going wrong?

Thanks