# making table data sets
library(dplyr)
library(tidyr)
library(data.table)
library(MorpheusData)
#############benchmark 1
dat <- read.table(text=
"
name1 con1_1 con1_2 con1_3 con2_1 con2_2 con2_3
a 23 33 22 23 40 40
b 25 34 22 22 50 40
c 28 29 22 30 60 40
", header=T)
write.csv(dat, "data-raw/r90_input1.csv", row.names=FALSE)
df_out <- read.table(text=
"
name1 con1 con2
a 26.0 34.3333333333333
b 27.0 37.3333333333333
c 26.3333333333333 43.3333333333333
", header=T)
##df_out = dat %>% gather(var, val, -1) %>% filter(val!=0) %>% select(-3)
#%>% arrange(order_id)
write.csv(df_out, "data-raw/r90_output1.csv", row.names=FALSE)
r90_output1 <- read.csv("data-raw/r90_output1.csv", check.names = FALSE)
fctr.cols <- sapply(r90_output1, is.factor)
int.cols <- sapply(r90_output1, is.integer)
r90_output1[, fctr.cols] <- sapply(r90_output1[, fctr.cols], as.character)
r90_output1[, int.cols] <- sapply(r90_output1[, int.cols], as.numeric)
save(r90_output1, file = "data/r90_output1.rdata")
r90_input1 <- read.csv("data-raw/r90_input1.csv", check.names = FALSE)
fctr.cols <- sapply(r90_input1, is.factor)
int.cols <- sapply(r90_input1, is.integer)
r90_input1[, fctr.cols] <- sapply(r90_input1[, fctr.cols], as.character)
r90_input1[, int.cols] <- sapply(r90_input1[, int.cols], as.numeric)
save(r90_input1, file = "data/r90_input1.rdata")
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