Select specific rows based on previous row value (in the same column)

Question

I\'ve been trying to figure a way to script this through R, but just can\'t get it. I have a dataset like this:

Trial  Type Correct Latency     
1       55          


        

Answer 1

For the fourth example, you could use which() in combination with lag() from dplyr, to attain the indices that meet your criteria. Then you can use these to subset the data.frame.

# Get indices of rows that meet condition
ind2 <- which(df$Type==20 & dplyr::lag(df$Type)==40)
# Get indices of rows before the ones that meet condition
ind1 <- which(df$Type==20 & dplyr::lag(df$Type)==40)-1

# Subset data
> df[c(ind1,ind2)]
   Trial Type Correct Latency
1:    28   40       1     500
2:    29   20       1     230

Answer 2

Here is an example code if you always want to delete the first trials of your data.

var1 <- c(1,2,1,2,1,2,1,2,1,2)
var2 <- c(1,1,1,2,2,2,2,3,3,3)

dat <- data.frame(var1, var2)

var1 var2
1     1    1
2     2    1
3     1    1
4     2    2
5     1    2
6     2    2
7     1    2
8     2    3
9     1    3
10    2    3

#delete only this line directly
filter(dat,lag(var2)==var2)

var1 var2
1     1    1
2     2    1
3     1    1
6     2    2
7     1    2
10    2    3

#delete the first 2 trials
#make a list of all rows where var2[n-1]!=var2[n] --> using lag from dplyr
drops <- c(1,2,which(lag(dat$var2)!=dat$var2), which(lag(dat$var2)!=dat$var2)+1)
if (!identical(drops,numeric(0))) { dat <- dat[-drops,] }

var1 var2
3     1    1
6     2    2
7     1    2
10    2    3