S11.R

In fredfeng/MorpheusData: Data sets for Morpheus

# making table data sets
library(dplyr)
library(tidyr)
library(MorpheusData)

#############benchmark 43
enrolled <- read.table(text=
"S_key C_name
S1 class2
S2 class1
S4 class2
S4 class4
S5 class4
S7 class5
S7 class1
S8 class4
S10 class5", header=T)

student <- read.table(text=
"S_key S_name
S1 SN1
S2 SN2
S3 SN3
S4 SN4
S5 SN5
S6 SN6
S7 SN7
S8 SN8
S9 SN9
S10 SN10", header=T)

# write.csv(enrolled, "sql/enrolled.csv", row.names=FALSE)
# write.csv(student, "sql/student.csv", row.names=FALSE)

# enrolled <- read.csv("sql/enrolled.csv", check.names = FALSE)
# fctr.cols <- sapply(enrolled, is.factor)
# int.cols <- sapply(enrolled, is.integer)
# enrolled[, fctr.cols] <- sapply(enrolled[, fctr.cols], as.character)
# enrolled[, int.cols] <- sapply(enrolled[, int.cols], as.numeric)
# save(enrolled, file = "sql/enrolled.rdata")

# student <- read.csv("sql/student.csv", check.names = FALSE)
# fctr.cols <- sapply(student, is.factor)
# int.cols <- sapply(student, is.integer)
# student[, fctr.cols] <- sapply(student[, fctr.cols], as.character)
# student[, int.cols] <- sapply(student[, int.cols], as.numeric)
# save(student, file = "sql/student.rdata")

# 5.1.11
#full_join(enrolled,student) %>% filter(is.na(C_name)) %>% select(S_name)


input=inner_join(enrolled,student)
write.csv(input, "data-raw/s11_input1.csv", row.names=FALSE)
s11_input1 <- read.csv("data-raw/s11_input1.csv", check.names = FALSE)
fctr.cols <- sapply(s11_input1, is.factor)
int.cols <- sapply(s11_input1, is.integer)
s11_input1[, fctr.cols] <- sapply(s11_input1[, fctr.cols], as.character)
s11_input1[, int.cols] <- sapply(s11_input1[, int.cols], as.numeric)
save(s11_input1, file = "data/s11_input1.rdata")


write.csv(student, "data-raw/s11_input2.csv", row.names=FALSE)
s11_input2 <- read.csv("data-raw/s11_input2.csv", check.names = FALSE)
fctr.cols <- sapply(s11_input2, is.factor)
int.cols <- sapply(s11_input2, is.integer)
s11_input2[, fctr.cols] <- sapply(s11_input2[, fctr.cols], as.character)
s11_input2[, int.cols] <- sapply(s11_input2[, int.cols], as.numeric)
save(s11_input2, file = "data/s11_input2.rdata")



df1=inner_join(enrolled,student) %>% select(S_name)
df2=select(student, S_name)
output=setdiff(df2,df1)
write.csv(output, "data-raw/s11_output1.csv", row.names=FALSE)
s11_output1 <- read.csv("data-raw/s11_output1.csv", check.names = FALSE)
fctr.cols <- sapply(s11_output1, is.factor)
int.cols <- sapply(s11_output1, is.integer)
s11_output1[, fctr.cols] <- sapply(s11_output1[, fctr.cols], as.character)
s11_output1[, int.cols] <- sapply(s11_output1[, int.cols], as.numeric)
save(s11_output1, file = "data/s11_output1.rdata")

# does not use full_join or filter by is.na but uses setdiff
df1=inner_join(enrolled,student) %>% select(S_name)
df2=select(student, S_name)
setdiff(df2,df1)

#anti_join(student,enrolled) %>% select(S_name)