Calculate percentages based on grouping variable - r

Question

I would like to calculate the percentage of people reported doing some work per day. For example I would like to know the percentage of people reported doing some work on Monday from the entire sample.
I used the following code to calculate this, but I am not sure about my result.
df1 <- structure(list(id = c(12L, 123L, 10L), t1_1 = c(0L, 0L, 1L),
t1_2 = c(1L, 0L, 1L), t1_3 = c(1L, 0L, 1L), t2_1 = c(0L,
1L, 1L), t2_2 = c(1L, 1L, 1L), t2_3 = c(0L, 1L, 1L), t3_1 = c(1L,
0L, 1L), t3_2 = c(0L, 0L, 1L), t3_3 = c(1L, 0L, 1L), t4_1 = c(0L,
1L, 1L), t4_2 = c(1L, 1L, 1L), t4_3 = c(0L, 1L, 1L), t5_1 = c(0L,
1L, 1L), t5_2 = c(1L, 1L, 1L), t5_3 = c(0L, 1L, 1L), t6_1 = c(1L,
0L, 1L), t6_2 = c(1L, 0L, 1L), t6_3 = c(1L, 0L, 1L), t7_1 = c(0L,
1L, 1L), t7_2 = c(0L, 1L, 1L), t7_3 = c(1L, 1L, 1L)),
class = "data.frame", row.names = c(NA, -3L))
Variable description t1 - Monday (t1_1, t1_2, t1_3 - are time steps that measured if work was done during Monday); t2 - Tuesday; t3 - Wednesday; t4 - Thursday; t5 - Friday; t6 - Saturda and t7- Sunday; id is an identification number
df2 <- reshape2::melt(df1, id.vars = "id")
df2$variable <- as.character(df2$variable)
df2$day <- sapply(strsplit(df2$variable, "_"), `[`, 1)
df2$day <- factor(df2$day, levels = variable)
df3<-df2 %>%
group_by (day) %>%
mutate (percent = (value/sum(value) *100))
ggplot(df3, aes(day, group = value)) +
geom_bar(aes(y = ..prop.., fill = factor(..x..)), stat="count") +
scale_fill_discrete(name="Days", labels=c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday")) +
scale_y_continuous(labels=scales::percent, limits=c(0,1)) +
ylab("relative frequencies") +
theme_bw()
Result:

Answer 1

library(dplyr)
df1 <- structure(
list(id = c(12L, 123L, 10L),
t1_1 = c(0L, 0L, 1L), t1_2 = c(1L, 0L, 1L), t1_3 = c(1L, 0L, 1L),
t2_1 = c(0L, 1L, 1L), t2_2 = c(1L, 1L, 1L), t2_3 = c(0L, 1L, 1L),
t3_1 = c(1L, 0L, 1L), t3_2 = c(0L, 0L, 1L), t3_3 = c(1L, 0L, 1L),
t4_1 = c(0L, 1L, 1L), t4_2 = c(1L, 1L, 1L), t4_3 = c(0L, 1L, 1L),
t5_1 = c(0L, 1L, 1L), t5_2 = c(1L, 1L, 1L), t5_3 = c(0L, 1L, 1L),
t6_1 = c(1L, 0L, 1L), t6_2 = c(1L, 0L, 1L), t6_3 = c(1L, 0L, 1L),
t7_1 = c(0L, 1L, 1L), t7_2 = c(0L, 1L, 1L), t7_3 = c(1L, 1L, 1L)),
class = "data.frame", row.names = c(NA, -3L))
df2 <- reshape2::melt(df1, id.vars = "id")
df2$variable <- as.character(df2$variable)
df2$day <- sapply(strsplit(df2$variable, "_"), `[`, 1)
df3 <- df2 %>%
group_by(id, day) %>%
summarize(count = sum(value)) %>%
group_by(id) %>%
mutate(percent = count / sum(count)) %>%
arrange(day, id)
> df3
# A tibble: 21 x 4
# Groups: id [3]
id day count percent
<int> <chr> <int> <dbl>
1 10 t1 3 0.143
2 12 t1 2 0.182
3 123 t1 0 0
4 10 t2 3 0.143
5 12 t2 1 0.0909
6 123 t2 3 0.25
...
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