Hi all, I ended up combining 85 different excel sheets of data and turned them into a dataframe. I listed the code below on how I exactly did that. The difficulty here is that I do not know how to further process the data for analysis/plotting as each of the 85 rows now have many observations in the form of elements (e.g. 1 observation or row actually has 21 elements or data). I have listed sample row 1 under my code as an example. There end up being 7 different elements under each of the columns (the columns being: "Block", "X.Correct", "meanRT"). I have recently started to learn R, so any help would be appreciated!
install.packages("openxlsx")
library("openxlsx")
#Finding all excel files I need
list<-list.files(pattern="*individualtemp.xlsx",recursive = TRUE)
#Choosing specific excel sheet and data cells
raw_list<-lapply(list,read.xlsx,sheet="E-Prime_Results",rows=5:12,cols=1:3)
#Turning list into df
my_df<-data.frame(t(sapply(raw_list,c)))
#Example row of data
my_df[2, ]
Block X.Correct meanRT
[2] 1, 2, 3, 4, 5, 6, 7 0.875, 0.975, 1.000, 0.975, 0.975, 0.975, 0.975 1166.9429, 801.9487, 806.1000, 758.4615, 654.1282, 601.2051, 592.8974