I have following data frame oridf
:
test_name gp1_0month gp2_0month gp1_1month gp2_1month gp1_3month gp2_3month
Test_1 136 137 152 143 156 150
Test_2 130 129 81 78 86 80
Test_3 129 128 68 68 74 71
Test_4 40 40 45 43 47 46
Test_5 203 201 141 134 149 142
Test_6 170 166 134 116 139 125
oridf <- structure(list(test_name = structure(1:6, .Label = c("Test_1",
"Test_2", "Test_3", "Test_4", "Test_5", "Test_6"), class = "factor"),
gp1_0month = c(136L, 130L, 129L, 40L, 203L, 170L), gp2_0month = c(137L,
129L, 128L, 40L, 201L, 166L), gp1_1month = c(152L, 81L, 68L,
45L, 141L, 134L), gp2_1month = c(143L, 78L, 68L, 43L, 134L,
116L), gp1_3month = c(156L, 86L, 74L, 47L, 149L, 139L), gp2_3month = c(150L,
80L, 71L, 46L, 142L, 125L)), .Names = c("test_name", "gp1_0month",
"gp2_0month", "gp1_1month", "gp2_1month", "gp1_3month", "gp2_3month"
), class = "data.frame", row.names = c(NA, -6L))
I need to convert it to following format:
test_name month group value
Test_1 0 gp1 136
Test_1 0 gp2 137
Test_1 1 gp1 152
Test_1 1 gp2 143
.....
Hence, conversion would involve splitting of gp1
and 0month
, etc. from columns 2:7 of the original data frame oridf
so that I can plot it with following command:
qplot(data=newdf, x=month, y=value, geom=c("point","line"), color=test_name, linetype=group)
How can I convert these data? I tried the melt
command, but I cannot combine it with the strsplit
command.
First I would use melt like you had done.
library(reshape2)
mm <- melt(oridf)
then there is also a colsplit
function you can use in the reshape2
library as well. Here we use it on the variable column to split at the underscore and the "m" in month (ignoring the rest)
info <- colsplit(mm$variable, "(_|m)", c("group","month", "xx"))[,-3]
Then we can recombine the data
newdf <- cbind(mm[,1, drop=F], info, mm[,3, drop=F])
# head(newdf)
# test_name group month value
# 1 Test_1 gp1 0 136
# 2 Test_2 gp1 0 130
# 3 Test_3 gp1 0 129
# 4 Test_4 gp1 0 40
# 5 Test_5 gp1 0 203
# 6 Test_6 gp1 0 170
And we can plot it using the qplot
command you supplied above
Use gather
from the tidyr package to convert from wide to long and then use separate
from the same package to separate the group_month
column into group
and month
columns. Finally using mutate
from dplyr smf extract_numeric
from tidyr extract the numeric part of month
.
library(dplyr)
# devtools::install_github("hadley/tidyr")
library(tidyr)
newdf <- oridf %>%
gather(group_month, value, -test_name) %>%
separate(group_month, into = c("group", "month")) %>%
mutate(month = extract_numeric(month))
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