Load the file, which I've put in the top-level R folder for now.
load("sampDat.dat")
summary(subS$userid)
## 701 702 704 705 706
## 750 449 750 750 748
## 707 709 710 711L 712L
## 730 746 748 697 749
## 713L 714L 715L 716L 717L
## 749 749 750 748 750
## 718L 719L 720L 721 722
## 750 750 750 748 750
## 723L 724L 725 726 727
## 750 750 748 750 744
## exp1_hl28_006 exp1_hl28_010 exp1_hl28_014 exp1_hl28_018 exp1_hl28_022
## 277 300 300 296 300
## exp1_hk82_005 exp1_hl82_009 exp1_hl82_013 exp1_hl82_017 exp1_hl82_021
## 300 300 300 298 299
## exp1_hr28_004 exp1_hr28_016 exp1_hr28_020 exp1_hr28_024 exp1_hr82_003
## 300 294 300 300 299
## exp1_hr82_007 exp1_hr82_011 exp1_hr82_015 exp1_hr82_019 exp1_hr82_023
## 300 299 299 298 300
## mss003 mss007 mss009 mss011 mss015
## 299 299 299 300 296
## mss017 mss019 mss021 mss002 mss004
## 300 299 296 300 298
## mss006 mss008 mss010 mss012 mss014
## 292 299 299 298 296
## mss016 mss018
## 300 294
Load stringr library to work with text more easily.
Use str_detect function to get logical vector indicating which rows have “exp” appearing somewhere in the userid column.
Use subset function to extract just these rows from subS.
library(stringr)
exp1 <- subset(subS, str_detect(subS$userid, "exp"))
Load ggplot2 library for plotting.
Make ggplot object with x=trialnum and y=angdiff from data=exp1.
Add stat_summary layer to get it to plot the mean y-values at each x-value instead of just plotting y, by setting fun.y = “mean”.
Set geom=“point” inside stat_summary, so it knows what kind of graph you want to make with those means.
library(ggplot2)
diffPlot = ggplot(exp1, aes(trialnum, angdiff)) + stat_summary(fun.y = "mean",
geom = "point")
diffPlot