library(devtools)

install_github("Rdatatable/data.table", build_vignettes = FALSE)

setwd("C:/Users/jeffthatcher/Cloud Drive/RRepos/GetCleanData")

library(data.table)

library(dplyr)

library(tidyr)

df <- read.csv("./data/unCleanData.csv")

library(reshape2)

melt(setDT(DT), id=1L, measure=lapply(c("^Group", "^Error"), grep, names(dt)),

variable.name="Group", value.name = c("Measure", "Error"))

library(dplyr)

df <- data.frame(Timepoint=c(0L, 7L, 14L, 21L, 28L), Group1=c(50L, 60L, 66L, 88L, 90L),

Error_Group1=c(3, 4, 6, 8, 2), Group2=c(30L, 60L, 90L, 120L, 150L),

Error_Group2=c(10L, 14L, 16L, 13L, 25L), Group3=c(44L, 78L, 64L, 88L, 91L),

Error_Group3=c(2L, 13L, 16L, 4L, 9L))

df <- lapply(1:3, function(x){

temp <- df %>% select(Timepoint, ends_with(as.character(x))) %>% mutate(Group=x)

names(temp) <- c("Timepoint", "Measure", "Error", "Group")

temp <- temp %>% select(Timepoint, Group, Measure, Error)

})

df <- do.call(rbind, df)

library(dplyr); library(tidyr)

df <- df %>% gather(temp, Timepoint)

names(df) <- c("Timepoint", "temp", "values")

df <- df %>% mutate(Group = sub("\\D+", "", temp), temp=sub("\\d", "", temp)) %>%

spread(temp, values)

names(df) <- c("Timepoint", "Group", "Error", "Measure")

df %>%

# 1. Pivot the table

gather (g, m, -Timepoint) %>%

# 2. Get the final Group ID in mGroup

separate (g, c("Measure", "mGroup"), -2) %>%

# 3. Spread the actual Error and Measure in two columns

spread (Measure, m) %>%

# 4. Assign the correct names to final columns

select (Timepoint, Group = mGroup, Measure = Group, Error = Error_Group) %>%

# 5. Sort as requested

arrange (Group, Timepoint)