1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
| > df <- data.frame(lieu=c("Paris","Paris","Paris","Paris","Paris",
+ "Londres","Londres","Londres","Londres","Londres",
+ "Moscou","Paris"),
+ temperature=c(20,21,11,11,12,16,15,8,9,8,12,0),
+ datetime.txt=c("10/06/2017 12:30:00",
+ "10/06/2017 13:00:00",
+ "14/10/2017 16:00:00",
+ "14/10/2017 16:30:00",
+ "14/10/2017 17:00:00",
+ "10/06/2017 12:30:00",
+ "10/06/2017 13:00:00",
+ "14/10/2017 16:00:00",
+ "14/10/2017 16:30:00",
+ "14/10/2017 17:00:00",
+ "10/06/2017 12:30:00",
+ "10/01/2017 12:00:00"))
> df$datetime <- strptime(df$date,"%d/%m/%Y %H:%M:%S")
> str(df)
'data.frame': 12 obs. of 4 variables:
$ lieu : Factor w/ 3 levels "Londres","Moscou",..: 3 3 3 3 3 1 1 1 1 1 ...
$ temperature : num 20 21 11 11 12 16 15 8 9 8 ...
$ datetime.txt: Factor w/ 6 levels "10/01/2017 12:00:00",..: 2 3 4 5 6 2 3 4 5 6 ...
$ datetime : POSIXlt, format: "2017-06-10 12:30:00" "2017-06-10 13:00:00" ...
> df
lieu temperature datetime.txt datetime
1 Paris 20 10/06/2017 12:30:00 2017-06-10 12:30:00
2 Paris 21 10/06/2017 13:00:00 2017-06-10 13:00:00
3 Paris 11 14/10/2017 16:00:00 2017-10-14 16:00:00
4 Paris 11 14/10/2017 16:30:00 2017-10-14 16:30:00
5 Paris 12 14/10/2017 17:00:00 2017-10-14 17:00:00
6 Londres 16 10/06/2017 12:30:00 2017-06-10 12:30:00
7 Londres 15 10/06/2017 13:00:00 2017-06-10 13:00:00
8 Londres 8 14/10/2017 16:00:00 2017-10-14 16:00:00
9 Londres 9 14/10/2017 16:30:00 2017-10-14 16:30:00
10 Londres 8 14/10/2017 17:00:00 2017-10-14 17:00:00
11 Moscou 12 10/06/2017 12:30:00 2017-06-10 12:30:00
12 Paris 0 10/01/2017 12:00:00 2017-01-10 12:00:00 |
Partager