How to find percentile and then group in R - r

Question

I have a data frame like below (df).
day area hour time count
___ ____ _____ ___ ____
1 1 0 1 10
1 1 0 2 12
1 1 0 3 8
1 1 0 4 12
1 1 0 5 15
1 1 0 6 18
1 1 1 1 10
1 1 1 2 12
1 1 1 3 8
1 1 1 4 12
1 1 1 5 15
1 1 1 6 18
1 1 1 7 12
1 1 1 8 15
1 1 1 9 18
1 1 2 1 10
1 1 2 2 18
1 1 2 3 19
.....
2 1 0 1 18
2 1 0 2 12
2 1 0 3 18
2 1 0 4 12
2 1 1 1 8
2 1 1 2 12
2 1 1 3 18
2 1 1 4 10
2 1 1 5 15
2 1 1 6 18
2 1 1 7 12
2 1 1 8 15
2 1 1 9 18
2 1 2 1 10
2 1 2 2 18
2 1 2 3 19
2 1 2 4 9
2 1 2 5 18
2 1 2 6 9
.....
30 99 23 1 9
30 99 23 2 8
30 99 23 3 9
30 99 23 4 19
30 99 23 5 18
30 99 23 6 9
30 99 23 7 19
30 99 23 8 8
30 99 23 9 19
Here I have the data for 30 days for 87 areas (1 to 82 and then I have 90,93,95,97,99) and 24 hours (0 to 23) per day.So the data is about the time taken to cross the area and how many have crossed.
For example:
day area hour time count
___ ____ _____ ___ ____
1 1 0 1 10
1 1 0 2 12
1 1 0 3 8
1 1 0 4 12
1 1 0 5 15
1 1 0 6 18
This gives me the On day 1 on hour 0 the time taken to cross the area 1
time count cumulative_count
___ ___ ________________
1 10 10
2 12 22
3 8 30
4 12 42
5 15 57
6 18 75
10 vehicles crossed the area in 1 minute.
12 vehicles crossed the area in 2 minutes.
8 vehicles crossed the area in 3 minutes.
12 vehicles crossed the area in 4 minutes.
15 vehicles crossed the area in 5 minutes.
18 vehicles crossed the area in 6 minutes.
From this I want to calculate How much time it took for 80% of the vehicles to cross area 1 in day 1 hour 0.So total vehicles=(10+12+8+12+15+18)=75.So 80% of 75 is 60.So time taken for 80% of the vehicles(80% of 75 which is 60) to pass the area 1 at day 1 hour 0 will be between 5 and 6(will be nearer to 5). So the result will be like:
day area hour time_taken_for_80%vehicles_to_pass
___ ____ ____ ___________________________________
1 1 0 5.33(approximately)
1 1 1 7.30
1 1 2 2.16
....
30 1 23 3.13
1 2 0 ---
1 2 1 ---
1 2 2 ---
1 2 3 ---
.......
30 99 21 ---
30 99 22 ---
30 99 23 ---
I know to I have to take quantile and then group by the area and day and hour.So I tried with
library(dplyr)
grp <- group_by(df, day,area,hour,quantile(df$count,0.8))
But it does not work.Any help is appreciated

Answer 1

My solution calculates the percentage of vehicles that crossed the area, for each time. Then gets the first time the percentage is above 80%:
str <- 'day area hour time count
1 1 0 1 10
1 1 0 2 12
1 1 0 3 8
1 1 0 4 12
1 1 0 5 15
1 1 0 6 18
1 1 1 1 10
1 1 1 2 12
1 1 1 3 8
1 1 1 4 12
1 1 1 5 15
1 1 1 6 18
1 1 1 7 12
1 1 1 8 15
1 1 1 9 18
1 1 2 1 10
1 1 2 2 18
1 1 2 3 19'
file <- textConnection(str)
df <- read.table(file, header = T)
df
library(dplyr)
df %>% group_by(day, area, hour) %>%
mutate(cumcount = cumsum(count),
p = cumcount/max(cumcount)) %>%
filter(p > 0.8) %>%
summarise(time = min(time))
result:
day area hour time
<int> <int> <int> <int>
1 1 1 0 6
2 1 1 1 8
3 1 1 2 3
Or with a linear estimation of the time when 80% is reached:
df %>% group_by(day, area, hour) %>%
mutate(cumcount = cumsum(count),
p = cumcount/max(cumcount),
g = +(p > 0.8),
order = (g*2-1)*time) %>%
group_by(day, area, hour,g) %>%
filter(row_number((g*2-1)*time)==1) %>%
group_by(day, area, hour) %>%
summarise(time = min(time)+(0.8-min(p))/(max(p)-min(p)))
result:
day area hour time
<int> <int> <int> <dbl>
1 1 1 0 5.166667
2 1 1 1 7.600000
3 1 1 2 2.505263
or get the same result using lag and lead
df %>% group_by(day, area, hour) %>%
arrange(hour) %>%
mutate(cumcount = cumsum(count),
p = cumcount/max(cumcount)) %>%
filter((p >= 0.8&lag(p)<0.8)|(p < 0.8&lead(p)>=0.8)) %>%
summarise(time = min(time)+(0.8-min(p))/(max(p)-min(p)))