plotting daily rainfall data using geom_step

Question

I have some rainfall data collected continuously from which I have calculated daily totals. Here is some toy data:

Date <- c(seq(as.Date("2016-07-01"), by = "1 day", length.out = 10))
rain_mm <- c(3,6,8,12,0,0,34,23,5,1)
rain_data <- data.frame(Date, rain_mm)

I can plot this data as follows:

ggplot(rain_data, aes(Date, rain_mm)) +
  geom_bar(stat = "identity") +
  scale_x_date(date_labels = "%d")

Which gives the following:

This seems fine. It is clear how much rainfall there was on a certain day. However, it could also be interpreted that between midday of one day and midday of the next, a certain amount of rain fell, which is wrong. This is especially a problem if the graph is combined with other plots of related continuous variables over the same period.

To get round this issue I could use geom_step as follows:

library(ggplot)
ggplot(rain_data, aes(Date, rain_mm)) +
  geom_step() +
  scale_x_date(date_labels = "%d")

Which gives:

This is a better way to display the data, and now scale_x_date appears to be a continuous axis. However, it would be nice to get the area below the steps filled but cant seem to find a straight forward way of doing this.

Q1: How can I fill beneath the geom_step? Is it possible?

It may also be useful to convert Date into POSIXct to facilitate identical x-axis in multi-plot figures as discussed in this SO question here. I can do this as follows:

library(dplyr)
rain_data_POSIX <- rain_data %>% mutate(Date = as.POSIXct(Date))

                  Date rain_mm
1  2016-07-01 01:00:00       3
2  2016-07-02 01:00:00       6
3  2016-07-03 01:00:00       8
4  2016-07-04 01:00:00      12
5  2016-07-05 01:00:00       0
6  2016-07-06 01:00:00       0
7  2016-07-07 01:00:00      34
8  2016-07-08 01:00:00      23
9  2016-07-09 01:00:00       5
10 2016-07-10 01:00:00       1

However, this gives a time of 01:00 for each date. I would rather have 00:00. Can I change this in the as.POSIXct function call, or do I have to do it afterwards using a separate function? I think it is something to do with tz = "" but cant figure it out.

How can I convert from class Date to POSIXct so that the time generated is 00:00?

Thanks

Answer 1

For your first question, you can work off this example. First, create a time-lagged version of your data:

rain_tl <- mutate( rain_data, rain_mm = lag( rain_mm ) )

Then combine this time-lagged version with the original data, and re-sort by date:

rain_all <- bind_rows( old = rain_data, new = rain_tl, .id="source" ) %>%
    arrange( Date, source ) 

(Note the newly created source column is used to break ties, correctly interlacing the original data with the time-lagged version):

> head( rain_all )
  source       Date rain_mm
1    new 2016-07-01      NA
2    old 2016-07-01       3
3    new 2016-07-02       3
4    old 2016-07-02       6
5    new 2016-07-03       6
6    old 2016-07-03       8    

You can now use the joint matrix to "fill" your steps:

ggplot(rain_data, aes(Date, rain_mm)) +
  geom_step() +
  geom_ribbon( data = rain_all, aes( ymin = 0, ymax = rain_mm ),
             fill="tomato", alpha=0.5 ):

This produces the following plot:

---

For your second question, the problem is that as.POSIX.ct does not pass additional arguments to the converter, so specifying the tz argument does nothing.

You basically have two options:

1) Reformat the output to what you want: format( as.POSIXct( Date ), "%F 00:00" ), which returns a vector of type character. If you want to preserve the object type as POSIXct, you can instead...

2) Cast your Date vector to character prior to passing it to as.POSIX.ct: as.POSIXct( as.character(Date) ), but this will leave off the time entirely, which may be what you want anyway.

Answer 2

If you would like to avoid the hack, you can customize the position in the geom_bar expression.

I found good results with:

ggplot(rain_data, aes(Date, rain_mm)) +
  geom_bar(stat = "identity", position = position_nudge(x = 0.51), width = 0.99) +
  scale_x_date(date_labels = "%d")