I'm trying to plot a time series with ggplot but the data gets offset by two hours for some reason.
> test <- structure(list(interval = structure(c(1465423500, 1465423800,
1465424100, 1465424400, 1465424700, 1465425000, 1465425300, 1465425600,
1465425900, 1465426200, 1465426500, 1465426800, 1465427100), class = c("POSIXct",
"POSIXt"), tzone = ""), mean = c(0.339622641509434, 0.132075471698113,
0.150943396226415, 0.0754716981132075, 2.09433962264151, 0.528301886792453,
0.867924528301887, 0, 1.47169811320755, 0.30188679245283, 0.132075471698113,
0.320754716981132, 0.679245283018868)), .Names = c("interval",
"mean"), class = c("tbl_df", "data.frame"), row.names = c(NA,
-13L))
> test
Source: local data frame [13 x 2]
interval mean
(time) (dbl)
1 2016-06-09 00:05:00 0.3396226 # First value: 5 minutes past midnight
2 2016-06-09 00:10:00 0.1320755
3 2016-06-09 00:15:00 0.1509434
4 2016-06-09 00:20:00 0.0754717
5 2016-06-09 00:25:00 2.0943396
6 2016-06-09 00:30:00 0.5283019
7 2016-06-09 00:35:00 0.8679245
8 2016-06-09 00:40:00 0.0000000
9 2016-06-09 00:45:00 1.4716981
10 2016-06-09 00:50:00 0.3018868
11 2016-06-09 00:55:00 0.1320755
12 2016-06-09 01:00:00 0.3207547
13 2016-06-09 01:05:00 0.6792453
This works fine:
g <- ggplot(interval.steps, aes(interval, mean))
g + geom_line()
But this doesn't:
g <- ggplot(interval.steps, aes(interval, mean))
g + geom_line() +
scale_x_datetime(date_labels = '%H:%M') # offsets times by -2 hours
What am I doing wrong? Thanks in advance.
One particular type of time series plots is time series boxplot. A time series boxplot is a useful way to visualize your dataset when you have multiple data points in a specific time interval. For example, you collect the temperature of a location every hourly, over a period of one month.
A time series dataset is a collection of data that are time-indexed and collected over a period of time. Using a time series, you can plot interesting visualizations that illustrate the change in values of the subject under study over a period of time. One particular type of time series plots is time series boxplot.
Time Series using Axes of type date Time series can be represented using either plotly.express functions (px.line, px.scatter, px.bar etc) or plotly.graph_objects charts objects (go.Scatter, go.Bar etc). For more examples of such charts, see the documentation of line and scatter plots or bar charts.
Time series can be represented using either plotly.express functions (px.line, px.scatter, px.bar etc) or plotly.graph_objects charts objects (go.Scatter, go.Bar etc). For more examples of such charts, see the documentation of line and scatter plots or bar charts.
It looks like scale_x_datetime
is changing the timezone of interval
from your local timezone to UTC. The function below should resolve the problem.
# Source: http://stackoverflow.com/a/11002253/496488
# Put in your local timezone. I've inserted mine just for illustration.
date_format_tz <- function(format = "%H:%M", tz = "America/Los_Angeles") {
function(x) format(x, format, tz=tz)
}
g <- ggplot(interval.steps, aes(interval, mean))
g + geom_line() +
scale_x_datetime(labels = date_format_tz())
Eipi10's answer above is a good workaround. However, I wanted to avoid hardcoding a time zone setting into my program in order to make it reproducible in any locale. The way to achieve this is very simple, just leave out the tz
parameter:
# Generator function to create 'hh:mm' labels for the x axis
# without explicit 'tz' specification
date_format <- function(format = "%H:%M") {
function(x) format(x, format)
}
The advantage of this method is that it works regardless of the time zone parameter of the original variable and the current locale.
For example if your time values were read in with something like this:as.POSIXct(interval, format = '%H:%M', tz = 'Pacific/Honolulu')
, the graph will still be plotted with the correct X axis labels, even if you're in, say, Zimbabwe.
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