# making table data sets
library(dplyr)
library(tidyr)
library(MorpheusData)
#############benchmark 64
dat <- read.table(text=
"
year roleInDebate Clarity_1 Effort_1 Clarity_2 Effort_2 Clarity_3 Effort_3
2006 x 3 5 10 4 5 7
2009 y 2 8 3 1 6 8
2013 r 7 10 7 4 5 2
2020 q 4 4 2 9 2 8
2004 b 8 8 3 4 9 5
", header=T)
write.csv(dat, "data-raw/r61_input1.csv", row.names=FALSE)
df_out = dat %>%
gather(var, val, -year, -roleInDebate) %>%
separate(var, c('skill', 'person')) %>%
spread(skill, val)
write.csv(df_out, "data-raw/r61_output1.csv", row.names=FALSE)
r61_output1 <- read.csv("data-raw/r61_output1.csv", check.names = FALSE)
fctr.cols <- sapply(r61_output1, is.factor)
int.cols <- sapply(r61_output1, is.integer)
r61_output1[, fctr.cols] <- sapply(r61_output1[, fctr.cols], as.character)
r61_output1[, int.cols] <- sapply(r61_output1[, int.cols], as.numeric)
save(r61_output1, file = "data/r61_output1.rdata")
r61_input1 <- read.csv("data-raw/r61_input1.csv", check.names = FALSE)
fctr.cols <- sapply(r61_input1, is.factor)
int.cols <- sapply(r61_input1, is.integer)
r61_input1[, fctr.cols] <- sapply(r61_input1[, fctr.cols], as.character)
r61_input1[, int.cols] <- sapply(r61_input1[, int.cols], as.numeric)
save(r61_input1, file = "data/r61_input1.rdata")
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