问题
I have animal tracking data with position, date and time.
I need to plot the data, time of day vs date/day, but I am struggling with getting the time and date in right format with the POSIX command. Here's my script up to the point where I have tried various ways using POSIX:
library(chron)
dtimes <- as.character(df$TimeWhen)
dtparts <- t(as.data.frame((strsplit(dtimes,'T'))))
rownames(dtparts) <- NULL
colnames(dtparts) <- c("Date","Time")
...
I need a column with dates and one with h:m:s in the right time formats in order to plot them against each other. The two columns in the dparts table are not in a recognizable time format. Should be simple, I know, but there's something here I don't get...
DPUTof some of my df:
structure(list(Lat = c(71.05946, 71.05946, 71.05946, 71.05946,
71.05946, 69.29127, 69.29127, 69.22796, 69.22796, 69.31701, 69.22796,
69.31701, 69.31701, 69.31701, 69.31701, 69.31701, 69.32129, 69.31983,
69.31983, 69.31983, 69.31983, 69.31983, 69.31366, 69.31366, 69.31366,
69.31366, 69.18893, 69.18893, 69.18893, 69.17569, 69.17569, 69.17569,
69.17569, 69.1555, 69.07846, 69.07564, 69.07846, 69.10216, 69.10216,
68.67609, 68.67609, 68.67609, 68.66437, 68.58191, 68.58191, 68.58191,
68.58787, 68.58787, 68.58787, 68.61008, 68.61008, 68.6273, 68.6273,
68.6273, 68.6273, 68.53913, 68.54474, 68.54474, 68.6173, 68.6173,
68.5852, 68.55022, 68.55022, 68.55022, 68.56043, 68.56043, 68.56043,
68.52243, 68.52243, 68.41181, 68.18226, 68.27806, 68.27806, 68.27806,
68.27806, 68.27806, 68.25424, 68.24761, 68.25424, 68.24761, 68.26075,
68.26075, 68.25436, 68.25436, 68.25436, 68.25882, 68.25882, 68.25358,
68.25882, 68.25358, 68.25358, 68.24089, 68.38403, 68.39622, 68.39622,
68.39622, 68.39622, 68.37399, 68.40941, 68.40941, 68.40941, 68.40941,
68.37438, 68.40941, 68.40941, 68.40941, 68.37438, 68.37438, 68.58219,
69.01418, 68.42632, 68.42632, 69.02445, 69.02445, 69.02445, 69.02445,
69.07674, 69.07674, 69.07674), Long = c(25.7908, 25.7908, 25.7908,
25.7908, 25.7908, 16.0598, 16.0598, 15.65899, 15.65899, 16.05636,
15.65899, 16.05636, 16.05636, 16.05636, 16.05636, 16.05636, 16.05741,
16.1268, 16.1268, 16.1268, 16.1268, 16.1268, 16.13471, 16.13471,
16.13471, 16.13471, 16.17577, 16.17577, 16.17577, 15.7561, 15.7561,
15.7561, 15.7561, 15.77912, 15.39518, 15.40282, 15.39518, 15.02001,
15.02001, 13.87795, 13.87795, 13.87795, 13.8701, 13.793, 13.793,
13.793, 13.87167, 13.87167, 13.87167, 13.87077, 13.87077, 13.74609,
13.74609, 13.74609, 13.74609, 13.50139, 13.50402, 13.50402, 13.53906,
13.53906, 13.45174, 13.30427, 13.30427, 13.30427, 13.33807, 13.33807,
13.33807, 13.08382, 13.08382, 12.97972, 12.59982, 11.19096, 11.19096,
11.19096, 11.19096, 11.19096, 11.08302, 11.12658, 11.08302, 11.12658,
11.08545, 11.08545, 11.06807, 11.06807, 11.06807, 10.89586, 10.89586,
10.93601, 10.89586, 10.93601, 10.93601, 11.00023, 9.6183, 9.49806,
9.49806, 9.49806, 9.49806, 9.48007, 9.47633, 9.47633, 9.47633,
9.47633, 9.4306, 9.47633, 9.47633, 9.47633, 9.4306, 9.4306, 7.1224,
8.58967, 7.2006, 7.2006, 8.57089, 8.57089, 8.57089, 8.57089,
8.52519, 8.52519, 8.52519), TimeWhen = structure(c(1L, 1L, 1L,
1L, 1L, 2L, 2L, 3L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 6L, 6L,
6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 10L,
11L, 11L, 11L, 12L, 12L, 13L, 13L, 13L, 14L, 15L, 15L, 15L, 16L,
16L, 16L, 17L, 17L, 18L, 18L, 18L, 18L, 19L, 20L, 20L, 21L, 21L,
22L, 23L, 23L, 23L, 24L, 24L, 24L, 25L, 25L, 26L, 27L, 28L, 28L,
28L, 28L, 28L, 30L, 29L, 30L, 29L, 31L, 31L, 32L, 32L, 32L, 33L,
33L, 34L, 33L, 34L, 34L, 35L, 36L, 37L, 37L, 37L, 37L, 37L, 38L,
38L, 38L, 38L, 39L, 38L, 38L, 38L, 39L, 39L, 40L, 41L, 41L, 41L,
42L, 42L, 42L, 42L, 43L, 43L, 43L), .Label = c("2017-07-16T15:13:50",
"2017-07-16T15:37:55", "2017-07-16T16:21:29", "2017-07-16T16:24:44",
"2017-07-16T16:53:58", "2017-07-16T17:15:02", "2017-07-16T18:00:24",
"2017-07-17T03:55:34", "2017-07-17T04:29:40", "2017-07-17T04:53:00",
"2017-07-17T09:36:13", "2017-07-18T03:17:54", "2017-07-18T04:23:26",
"2017-07-18T04:26:44", "2017-07-18T05:59:29", "2017-07-18T06:02:41",
"2017-07-18T06:10:32", "2017-07-18T06:36:17", "2017-07-18T07:39:46",
"2017-07-18T07:43:26", "2017-07-18T07:48:25", "2017-07-18T09:19:02",
"2017-07-18T09:28:46", "2017-07-18T10:00:38", "2017-07-18T11:00:03",
"2017-07-18T11:03:49", "2017-07-19T04:08:44", "2017-07-19T04:24:14",
"2017-07-19T05:45:59", "2017-07-19T05:47:37", "2017-07-19T05:56:30",
"2017-07-19T06:05:26", "2017-07-19T07:24:12", "2017-07-19T07:24:44",
"2017-07-19T07:51:08", "2017-07-20T07:22:15", "2017-07-20T08:42:35",
"2017-07-20T08:56:43", "2017-07-20T09:01:53", "2017-07-21T03:08:33",
"2017-07-21T03:31:17", "2017-07-21T03:46:05", "2017-07-21T05:03:12"),
class = "factor")), .Names = c("Lat", "Long", "TimeWhen"), row.names =
c(NA,-119L), class = "data.frame")
回答1:
The OP has requested:
I need a column with dates and one with h:m:s in the right time formats in order to plot them against each other.
If the right format is meant that date and time are formatted as character strings this may lead to unexpected results when plotted because character variables will be plotted on discrete axes.
So I suggest to make sure that both date and time of day are treated as continuous variables.
With base R and help of the lubridate package:
library(lubridate)
# coerce character string to POSIXct
df$TimeWhen <- ymd_hms(df$TimeWhen)
# create Date column
df$date <- as.Date(df$TimeWhen)
Now, there are two possibilities to turn create the hour or time of the day as continuous variables:
- as numeric variable, or
- as POSIXct variable where alle timestamps are moved/mapped/shifted onto on reference day
.
# create hour of day as numeric value between 0 and 24
df$hour.of.day <- hour(df$TimeWhen) + minute(df$TimeWhen)/60 + second(df$TimeWhen)/(60*60)
# shift time of day to a single reference date
df$time.of.day <- as.POSIXct(min(df$date)) +
(df$TimeWhen - floor_date(df$TimeWhen, unit = "day") )
This will make a difference when plotted:
library(ggplot2)
# y-axis formatted as numeric variable
ggplot(df) + aes(date, hour.of.day) + geom_point()
# y-axis formatted using hh:mm format
ggplot(df) + aes(date, time.of.day) + geom_point()
Note the different formatting of the y-axis.
回答2:
Using dplyr and stringr:
library(dplyr)
df %>%
mutate(TimeWhenClean = stringr::str_replace(x$TimeWhen, "T", " "),
date = strftime(TimeWhenClean, format = "%F") %>% as.Date,
time = strftime(TimeWhenClean, format = "%T")) %>%
select(-TimeWhenClean)
This will take your df, add a tmp variable that replaces the T by a space so the datetime variabel is in the standard ISO format. With strftime we can easily extract the date part and the time part (the former is converted to date). And we abandon the tmp variable.
来源：https://stackoverflow.com/questions/45962190/converting-date-and-time-with-posix