使用cut函数时breaks参数出错

Question

I'm learning R and I need to create a two way table from the data below:

> head(datanet)
   Date & Time [Local]  distance travelled
1:    18/06/2018 03:08  15.959366
2:    18/06/2018 03:12  22.535566
3:    18/06/2018 03:16  12.036834
4:    18/06/2018 03:20  18.738134
5:    18/06/2018 03:24  26.781879
6:    18/06/2018 03:28  8.341659

My desired output should look like the table below, having an hour column entry representing the time of the day (24 entries for the 24 hours of the day) and several dist_tra on yyyy-mm-dd entries with the average hourly distance travelled per day for each hour of the day. Like so:

head(dist.byHour[1:3])
  hour dist_tra on 06/07/2018  dist_tra on 06/08/2018
1:   00              25.834355              29.388140
2:   01                     NA               8.329956
3:   02                     NA              31.506390
4:   03              33.464954              20.995957
5:   04               6.406513              17.035749
6:   05              28.254438              38.803171

By looking online and talking to some collegues I got the script below. However, I'm having an undesired error message when using cut() :

library(tidyverse)

datanet$datehour <- cut(datanet[[1]], breaks = "hours")

dist.byHour <- aggregate(meters ~ datehour, datanet, mean, na.rm = TRUE)
dist.byHour$datehour <- as.POSIXct(dist.byHour$datehour)
dist.byHour$hour <- format(dist.byHour$datehour, "%H")
dist.byHour$datehour <- as.Date(dist.byHour$datehour)
dist.byHour <- dist.byHour[c(3, 1, 2)]

dist.byHour <- dist.byHour %>%
  spread(datehour, -hour)

names(dist.byHour)[-1] <- paste("dist_tra on", names(dist.byHour)[-1])

The error being:

> datanet$datehour <- cut(datanet[[1]], breaks = "hours")
Error in cut.default(datanet[[1]], breaks = "hours") : 
  'x' must be numeric

Any ideas on how to fix this? This is an important assignment I'm working on so any help would be very appreciated!

Answer 1

Actually there's no need to use cut, you can just use groups:

library(lubridate)
library(tidyverse)

# sample data
date <- c("18/06/2018 03:08", "18/06/2018 03:12", "18/06/2018 04:20", "19/06/2018 03:16", "19/06/2018 03:20", "19/06/2018 04:20")
distance <- c(15.959366,  22.535566, 12.036834,  18.738134, 12.036834, 22.535566)

df <- data.frame(date, distance)

df %>% 
  mutate(date = dmy_hm(date)) %>% #coerce to date object
  group_by(day = date(date), hour = hour(date)) %>% # group by day and hour
  summarise(dist = mean(distance)) %>% # average distance traveled in that hour
  spread(day, dist) # re-arrange dataframe