# making table data sets
library(dplyr)
library(tidyr)
library(data.table)
library(MorpheusData)
#############benchmark 1
dat <- read.table(text=
"
Color Type W1 W2 W3 W4
red Outdoor 2 3 4 5
red Indoor 5 6 7 8
blue Both 6 7 8 9
green Indoor 8 9 10 11
blue Indoor 11 12 13 14
blue Both 12 13 14 15
red Indoor 14 15 16 17
red Outdoor 14 15 16 17
yellow Outdoor 12 13 14 15
green Indoor 2 3 4 5
", header=T)
write.csv(dat, "data-raw/r82_input1.csv", row.names=FALSE)
df_out <- read.table(text=
"
Color Week Count
blue W1 2
blue W2 2
blue W3 2
blue W4 2
green W4 1
red W1 2
red W2 2
red W3 2
red W4 2
yellow W1 1
yellow W2 1
yellow W3 1
yellow W4 1
", header=T)
##df_out = dat %>% gather(var, val, -1) %>% filter(val!=0) %>% select(-3)
#%>% arrange(order_id)
write.csv(df_out, "data-raw/r82_output1.csv", row.names=FALSE)
r82_output1 <- read.csv("data-raw/r82_output1.csv", check.names = FALSE)
fctr.cols <- sapply(r82_output1, is.factor)
int.cols <- sapply(r82_output1, is.integer)
r82_output1[, fctr.cols] <- sapply(r82_output1[, fctr.cols], as.character)
r82_output1[, int.cols] <- sapply(r82_output1[, int.cols], as.numeric)
save(r82_output1, file = "data/r82_output1.rdata")
r82_input1 <- read.csv("data-raw/r82_input1.csv", check.names = FALSE)
fctr.cols <- sapply(r82_input1, is.factor)
int.cols <- sapply(r82_input1, is.integer)
r82_input1[, fctr.cols] <- sapply(r82_input1[, fctr.cols], as.character)
r82_input1[, int.cols] <- sapply(r82_input1[, int.cols], as.numeric)
save(r82_input1, file = "data/r82_input1.rdata")
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