# after reading from URL using drop-down menus, readr version: salary <- as.data.frame(salary) # this coerces the "tibble" format to a regular R data frame # reading in without drop-down menus salary <- read.table("http://faculty.washington.edu/kenrice/rintro/salary.txt" , header=TRUE) ?read.table # then look in Help window myfile <- file.choose() # a function with no arguments salary <- read.table(myfile, header=TRUE) salary <- read.table(file.choose(), header=TRUE) table(salary$deg) table(salary$gender, salary$deg) table(salary$deg == "Prof") (salary$deg == "Prof")[1:10] salary$deg[1:10] + 4.2 # watch for warnings oldprofdata <- subset(salary, rank=="Full" & year<83) table(oldprofdata$gender) summary(oldprofdata$rank) table(oldprofdata$rank) salary$f.rank <- as.factor(salary$rank) table( subset(salary, f.rank=="Full" & year < 83)$f.rank) oldprofdata <- droplevels(oldprofdata) # overwrites original version levels(oldprofdata$field) levels(oldprofdata$field) <- c("Arts","Other","Law'n'Med") with(salary, table(gender, rank)) with( subset(salary, rank=="Full" & year<83), table(gender, rank)) letters %in% c("t","i","m") (1:26)[letters %in% c("t","i","m")] mean(salary$salary) mean(salary$salary, na.rm=TRUE) # na.rm's default is FALSE, in many functions library("readr") # loads a package - more on this later saltib <- read_csv("http://faculty.washington.edu/kenrice/rintro/salary.csv") saltib[1:2,1:4] saldf <- as.data.frame(saltib) saldf[ 1:2,1:4]