# making table data sets
library(dplyr)
library(tidyr)
library(data.table)
library(MorpheusData)
#############benchmark 1
dat <- read.table(text=
"
rowname CA DATE_1 TIME_1 ENTRIES_1 DATE_2 TIME_2 ENTRIES_2 DATE_3 TIME_3 ENTRIES_3
1 A002 07-27-13 00:10:00 4209603 07-27-13 08:00:00 4209663 07-27-17 18:00:00 1209663
2 A002 07-28-13 08:20:00 4210490 07-28-13 16:40:00 4210775 07-28-17 06:00:00 1210775
3 A002 07-29-13 16:20:00 4211586 07-30-13 00:00:00 4212845 07-30-17 10:00:00 1212845
", header=T)
write.csv(dat, "data-raw/r89_input1.csv", row.names=FALSE)
df_out <- read.table(text=
"
rowname CA col2 DATE ENTRIES TIME
2 A002 1 07-28-13 4210490 08:20:00
2 A002 2 07-28-13 4210775 16:40:00
2 A002 3 07-28-17 1210775 06:00:00
3 A002 1 07-29-13 4211586 16:20:00
3 A002 2 07-30-13 4212845 00:00:00
3 A002 3 07-30-17 1212845 10:00:00
", header=T)
##df_out = dat %>% gather(var, val, -1) %>% filter(val!=0) %>% select(-3)
#%>% arrange(order_id)
write.csv(df_out, "data-raw/r89_output1.csv", row.names=FALSE)
r89_output1 <- read.csv("data-raw/r89_output1.csv", check.names = FALSE)
fctr.cols <- sapply(r89_output1, is.factor)
int.cols <- sapply(r89_output1, is.integer)
r89_output1[, fctr.cols] <- sapply(r89_output1[, fctr.cols], as.character)
r89_output1[, int.cols] <- sapply(r89_output1[, int.cols], as.numeric)
save(r89_output1, file = "data/r89_output1.rdata")
r89_input1 <- read.csv("data-raw/r89_input1.csv", check.names = FALSE)
fctr.cols <- sapply(r89_input1, is.factor)
int.cols <- sapply(r89_input1, is.integer)
r89_input1[, fctr.cols] <- sapply(r89_input1[, fctr.cols], as.character)
r89_input1[, int.cols] <- sapply(r89_input1[, int.cols], as.numeric)
save(r89_input1, file = "data/r89_input1.rdata")
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