将刻痕频率分配给facet_grid中的离散数据轴

Question

I'm having some trouble setting readable tick marks on my axes. The problem is that my data are at different magnitudes, so I'm not really sure how to go about it.

My data include ~400 different products, with 3/4 variables each, from two machines. I've pre-processed it into a data.table and used gather to convert it to long form- that part is fine.

Overview: Data is discrete, each X_________ on the x-axis represents a separate reading, and its relative values from machine 1/2 - the idea is to compare the two. The graphical format is perfect for my needs, I would just like to set the ticks at say, every 10 products on the x-axes, and at reasonable values on the y-axis.

• Y_1: from 150 to 250
• Y_2: from say, 1.5* to 2.5
• Y_3: from say, 0.8* to 2.3
• Y_4: from say, 0.4* to 1.5

*Bottom value, rounded down

Here's the code I'm using so far

var.Parameter <- c("Var1", "Var2", "Var3", "Var4")

MProduct$Parameter <- factor(MProduct$Parameter,
                          labels = var.Parameter)
labels_x <- MProduct$Lot[seq(0, 1626, by= 20)]
labels_y <- MProduct$Value[seq(0, 1626, by= 15)]


plot.MProduct <- ggplot(MProduct, aes(x = Lot,
                                y = Value,
                                colour = V4)) +
  facet_grid(Parameter ~.,
            scales = "free_y") + 
  scale_x_discrete(breaks=labels_x) +
  scale_y_discrete(breaks=labels_y) +
  geom_point() +
  labs(title = "Product: Select  Trends | 2018",
       x = "Time (s)",
       y = "Value") +
  theme(axis.text.x = element_text (angle = 90,
                                    hjust = 1,
                                    vjust = 0.5)) 
 # ggsave("MProduct.png")
plot.MProduct

Anyone knows how to possibly render this graph more readable? Setting labels/breaks manually greatly limits flexibility and readability - there should be an option to set it to every X ticks, right? Same with y.

I need to apply this as a function to multiple datasets, so I'm not very happy about having to specify the column length of the "gathered" dataset every time either, which, in this case is 1626.

Since I'm here, I would also like to take the opportunity to ask about this code:

var.Parameter <- c("Var1", "Var2", "Var3", "Var4")

More often than not, I need to label my data in a specific order, which is not necessarily alphabetical. R, however, defaults to some kind of odd behaviour whereupon I have to plot and verify that the labels are indeed where they should be. Any clue how I could force them to be presented in order? As it is, my solution is to keep shifting their position in that line of code until it produces the graph correctly.

Many thanks.

Answer 1

Okay. I'm going to ignore the y axis labels because the defaults seem to work just fine as long as you don't try to overwrite them with your custom labels_y thing. Just let the defaults do their work. For the X axis, we'll give a couple options:

(A) label every N products on X-axis. Looking at ?scale_x_discrete , we can set the labels to a function that takes all the level of the factor and returns the labels we want. So we'll write a function al that returns a function that returns every Nth label:

every_n_labeler = function(n = 3) {
  function (x) {
    ind = ((1:length(x)) - 1) %% n == 0
    x[!ind] = ""
    return(x)
  }
}

Now let's use that as the labeler:

ggplot(df, aes(x = Lot,
               y = Value,
               colour = Machine)) +
  facet_grid(Parameter ~ .,
             scales = "free_y") +
  geom_point() +
  scale_x_discrete(labels = every_n_labeler(3)) +
  labs(title = "Product: Select  Trends | 2018",
       x = "Time (s)",
       y = "Value") +
  theme(axis.text.x = element_text (
    angle = 90,
    hjust = 1,
    vjust = 0.5
  )) 

You can change the every_n_labeler(3) to (10) to make it every 10th label.

(B) Maybe more appropriate, it seems like your x-axis is actually numeric, it just happens to have "X" in front of it, let's convert it to numeric and let the defaults do the labeling work:

df$time = as.numeric(gsub(pattern = "X", replacement = "", x = df$Lot))

ggplot(df, aes(x = time,
               y = Value,
               colour = Machine)) +
  facet_grid(Parameter ~ .,
             scales = "free_y") +
  geom_point() +
  labs(title = "Product: Select  Trends | 2018",
       x = "Time (s)",
       y = "Value") +
  theme(axis.text.x = element_text (
    angle = 90,
    hjust = 1,
    vjust = 0.5
  )) 

With your full x range, I imagine that would look nice.

(C) But who wants to read those 9-digit numbers? You're labeling the x-axis a "Time (s)", which makes me think it's actual a time , measured in seconds from some start time. I'll make up that your start time is 2010-01-01 and covert these seconds to actual times, and then we get a nice date-time scale:

ggplot(df_s, aes(x = as.POSIXct(time, origin = "2010-01-01"),
               y = Value,
               colour = Machine)) +
  facet_grid(Parameter ~ .,
             scales = "free_y") +
  geom_point() +
  labs(title = "Product: Select  Trends | 2018",
       x = "Time (s)",
       y = "Value") +
  theme(axis.text.x = element_text (
    angle = 90,
    hjust = 1,
    vjust = 0.5
  )) 

If this is the real meaning behind your data, then using a date-time axis is a big step up for readability. (Again, notice that we are not specifying the breaks, the defaults work quite well.)

---

Using this data (I subset your sample data down to 2 facets and used dput to make it copy/pasteable):

df = structure(list(Lot = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 
4L, 1L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 1L, 2L, 3L, 4L, 1L, 
2L, 3L, 4L, 1L), .Label = c("X180106482", "X180126485", "X180306523", 
"X180526326"), class = "factor"), Value = c(201, 156, 253, 211, 
178, 202.5, 203.4, 204.3, 205.2, 2.02, 2.17, 1.23, 1.28, 1.54, 
1.28, 1.45, 1.61, 2.35, 1.34, 1.36, 1.67, 2.01, 2.06, 2.07, 2.19, 
1.44, 2.19), Parameter = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L), .Label = c("Var 1", "Var 2", "Var 3", "Var 4"
), class = "factor"), Machine = structure(c(2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Machine 1", "Machine 2"), class = "factor"), 
    time = c(180106482, 180126485, 180306523, 180526326, 180106482, 
    180126485, 180306523, 180526326, 180106482, 180106482, 180126485, 
    180306523, 180526326, 180106482, 180126485, 180306523, 180526326, 
    180106482, 180106482, 180126485, 180306523, 180526326, 180106482, 
    180126485, 180306523, 180526326, 180106482)), row.names = c(NA, 
-27L), class = "data.frame")