How to manage date format for graphical purpose?

Question

I’m trying to do a graphic with data that I send you a quick subset. The graphic I would like to have has on y axis the captors ("capteur") sorted by the number of data they have ("n") with a x axis showing atleast each month filled by values which are temperature values.

I’m struggling with the x axis which is the date. I don't know which format (date, POSIXct, factor ?) is the best to manage x axis. My goal is to have this format "day/month/year" (as exemple : "13/08/21") but as it should make the x axis unreadable, I would aslo be able to change it into month/year format ("08/21") (I should manage to do it myself just by deleting the first 3 characters ?)

example<-temp_plot%>%
  filter(capteur=="59-15-s." | capteur=="59-52-s." | capteur=="59-04-s." )
  select(1,5,8)
temp_plot<-example
dput(temp_plot)

> dput(example)
structure(list(capteur = structure(c(253L, 313L, 253L, 313L, 
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))), row.names = c(NA, -647L), class = "data.frame")

#creating a variable to sort my captor ("capteur") from the one with the most data to the one with the less
temp_plot<-temp_plot%>%
  group_by(capteur)%>%
  mutate(n=n())

# Order my data to the way I want 
temp_plot$capteur <- factor(temp_plot$capteur, levels=rev(unique(temp_plot$capteur)), ordered=TRUE)

#Changing into the date format I want 
temp_plot$date<-strftime(temp_plot$date,"%d/%m/%Y")
class(temp_plot$date)

temp_plot%>%
  ggplot(aes(x=date,y=reorder(capteur,n),fill=value))+
  geom_tile() + 
  scale_fill_distiller(palette="Spectral")+
  theme(axis.text.x = element_text(angle=45, hjust = 1))+
  theme_classic()

Do you think you can help me on this one ? Im not really use with graphics and date format.

Thank you

look at `scale_x_date` argument `date_label` – Richard Telford Aug 03 '21 at 14:16 — Richard Telford, Aug 03 '21 at 14:16

Ray · Answer 1 · 2021-08-03T16:12:16.797

Salut Germain, @RichardTelford gave you basically the answer already.

There are different philosophies, but I recommend to stick to the object-type and only coerce to other types as the last resort. Thus, as you work with dates, stick to dates or datetimes. The benefit of sticking to the correct types is that you can build on things like natural ordering, formatting, etc.
Again - only revert to other types, if you need to "hack" your desired result.

If we "rewind" to the following step:

temp_plot<-temp_plot%>%
  group_by(capteur)%>%
  mutate(n=n())

You are creating a long dataframe of the following form:

temp_plot
# A tibble: 647 x 4
# Groups:   capteur [3]
   capteur  value date                    n
   <fct>    <dbl> <dttm>              <int>
 1 59-15-s.  4.10 2021-01-01 00:00:00   267
 2 59-52-s.  4.83 2021-01-01 00:00:00   260
 3 59-15-s.  3.05 2021-01-02 00:00:00   267
 4 59-52-s.  2.84 2021-01-02 00:00:00   260
 5 59-15-s.  3.58 2021-01-03 00:00:00   267
 6 59-52-s.  4.42 2021-01-03 00:00:00   260
 7 59-15-s.  2.84 2021-01-04 00:00:00   267
 8 59-52-s.  3.58 2021-01-04 00:00:00   260
 9 59-15-s.  2.73 2021-01-05 00:00:00   267
10 59-52-s.  2.94 2021-01-05 00:00:00   260

From this you can derive that your "date" column is actually a datetime type. {ggplot2} offers many type oriented scales. Here we have to use the scale_x_datetime() call.

Note: I skip the theme() part, to focus on the scale bit. You can add that later again.

temp_plot %>% 
    ggplot(aes(x=date,y=reorder(capteur,n),fill=value))+
    geom_tile() + 
    scale_fill_distiller(palette="Spectral") +
#---------- define the type-correct scale 
    scale_x_datetime()

This yields "out of the box":

In the next step you can now define the "breaks" and "labels". Note: the label work is easy because we have "date/datetimes", if you would have coerced the type, this would require providing a vector of your desired values.
Here we can now make use of the build-in label formats. Read up on the different options.

temp_plot %>% 
    ggplot(aes(x=date,y=reorder(capteur,n),fill=value))+
    geom_tile() + 
    scale_fill_distiller(palette="Spectral") +
    scale_x_datetime(
          date_breaks = "2 months"  # the "major" breaks of your x-axis
        , date_labels = "%b %y"     # formatting, here shortened Month and Year
    )

As an exercise, you may want to look into changing your date column into a date-object and work with scale_x_date(). The principles will be the same. However, I recommend to stay away from making it a factor or character and try to emulate the same output. Good luck.

Again, kudos to Richard Telford who pointed out the answer already! This shows you the application of it.

How to manage date format for graphical purpose?

1 Answers1