Aesthetics Must Either Be Length One, or the Same Length as the Dataproblems

Aesthetics must either be length one, or the same length as the data

Ben's comment got me thinking about variable names, and I realized there were no specified variables in outliers (the original data frame, ratios3, and outliers both have many variables). I simply needed to specify the same variables:

  geom_point(data = outliers, aes(`CPI-U 2015 (Official)`, `PCE1 2015`), 
      colour = "red", shape=1) +

R - Aesthetics must be either length 1 or the same as the data

If you subset anything, subset everything.

ggplot(data = elect[26:43,], aes(x = year, y = austria_rad_right)) +
  geom_line() +
  xlab("Year") +
  ylab("Radical Right Vote Share") +
  ggtitle("Austria Radical Right Support Over Time") + 
  theme_gray() +
  theme(panel.grid = element_blank())

What you're doing with your code of aes(x = austria_year, y = austria_rad_right) is similar to plot(21:23, 1:10) (which fails). Okay, so the first few points are 21,1, 22,2, and 23,3, but what do ,4, ,5, and beyond pair with?

Layer-specific data subset

Occasionally there is a need to show different portions of the data in different layers. For instance, points from all data and lines from a subset. For that, we can take advantage of data= arguments to individual layers.

ggplot(mtcars, aes(mpg, cyl)) +
  geom_point() +
  geom_path(data = ~ .[with(., ave(cyl, cyl, FUN = seq_along) < 2),],
            color = "red")

I'm using the rlang-style ~ tilde function, where the . is replaced by the data provided in the main ggplot(.) call. Why is this useful? Because often one can change the data in the first line and forget to update it in the remaining data-dependent layers; in this fashion, the subset of data used for the layer is dynamic.

This would apply to your case if you intend to show a layer from all data and then only a subset of it for another layer.

Perhaps this:

ggplot(data = elect, aes(x = year, y = austria_rad_right)) +
  geom_point(color = "gray") +
  geom_line(data = ~ .[26:43,]) +
  xlab("Year") +
  ylab("Radical Right Vote Share") +
  ggtitle("Austria Radical Right Support Over Time") + 
  theme_gray() +
  theme(panel.grid = element_blank())

Admittedly I'd prefer a better method of subsetting the data, perhaps something like

  geom_line(data = ~ subset(., country == "Austria")) +

(R) Error: Aesthetics must be either length 1 or the same as the data (6): x and y

library(gganimate)

# add an id row so that gganimate knows which line in the first 
#   frame matches the ones in the 2nd
Lines_frame = rbind(LINES, LINES_1) %>%
  group_by(ind) %>% mutate(id = row_number()) %>% ungroup()

ggplot(data=mtcars, aes(x=wt, y=mpg)) + geom_point() +
  geom_segment(aes(x=Startx,y=Starty,xend=Endx,yend=Endy, group = id),
               data=Lines_frame)+
  coord_cartesian(ylim=c(9,36),xlim = c(1.5,6.2)) +
  transition_reveal(ind)

There are a few transition options. For instance, you could alternate back and forth between the two states with transition_states and make the movement tween with a bounce, because why not:

# wrapping in `animate()` to access its parameters, like frames per second (fps)
animate(
  ggplot(data=mtcars, aes(x=wt, y=mpg)) + geom_point()+
  geom_segment(aes(x=Startx,y=Starty,xend=Endx,yend=Endy),
               data=Lines_frame)+
  coord_cartesian(ylim=c(9,36),xlim = c(1.5,6.2)) +
  transition_states(ind, state_length = 0.2) + 
  ease_aes('bounce-in'),
  fps = 20, nframes = 200, height = 400, width = 600)

Aesthetics must either be length one, or the same length as the dataProblems

The problem is that skew isn't being subsetted in colour=factor(skew), so it's the wrong length. Since subset(skew, product == 'p1') is the same as subset(skew, product == 'p3'), in this case it doesn't matter which subset is used. So you can solve your problem with:

p1 <- ggplot(df, aes(x=subset(price, product=='p1'),
                     y=subset(price, product=='p3'),
                     colour=factor(subset(skew, product == 'p1')))) +
              geom_point(size=2, shape=19)

Note that most R users would write this as the more concise:

p1 <- ggplot(df, aes(x=price[product=='p1'],
                     y=price[product=='p3'],
                     colour=factor(skew[product == 'p1']))) +
              geom_point(size=2, shape=19)

ggplot: Error: Aesthetics must be either length 1 or the same as the data (10): x, y, group

Your data is of length 10, while your y aesthetic in geom_line is of length 11.

seq(0, 1 , by = 0.1)
[1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Try seq(0,0.9,by=0.1) or seq(0.1,1,by=0.1)

Error: Aesthetics must be either length 1 or the same as the data (121): yintercept

The issue is that you map c(sig, -1*sig) on yintercept which will not work as the length of c(sig, -1*sig) is two times the length of your df gacf.df. That's what the error message is telling you. There are two options to achieve your desired result:

1. If you add sig as a variable you have to add the horizontal lines via two calls of geom_hline.

2. The approach below instead makes sig a scalar. In that case you don't have to wrap yintercept = c(sig, -1*sig) inside aes() :

correlogram <- function(x, type = "correlation"){
  gacf = acf(x, plot=FALSE, lag.max=120, type = type)
  gacf.df = with(gacf, data.frame(lag, acf))
  #gacf.df$sig = qnorm((1 + 0.95)/2)/sqrt(length(x))
  
  sig = qnorm((1 + 0.95)/2)/sqrt(length(x))
  q <- ggplot(data = gacf.df, mapping = aes(x = lag, y = acf))
  q <- q + xlim(c(0,120)) + theme_bw()
  q <- q + geom_hline(aes(yintercept = 0))
  q <- q + geom_segment(mapping = aes(xend = lag), yend = 0, lwd = 1)
  # q <- q + geom_hline(aes(yintercept = sig), linetype = 2, colour = "#e51843")
  # q <- q + geom_hline(aes(yintercept = -1*sig), linetype = 2, colour = "#e51843")
  q <- q + geom_hline(yintercept = c(sig, -1*sig), linetype = 2, colour = "#e51843")
  if(type == "partial"){
    q <- q + ylab(expression(alpha[k]))
  } else {
    q <- q + ylab(expression(rho[k]))
  }
  q <- q + xlab("lag k")
}

library(gridExtra)
library(ggplot2)
library(grid)

set.seed(42)

prp <- data.frame(Log.prp.Standardized = rnorm(100))

q1 <- correlogram(prp$Log.prp.Standardized) + xlab(" ") + ggtitle("Total and Partial Correlograms")
q2 <- correlogram(prp$Log.prp.Standardized, type = "partial") 
grid.arrange (q1, q2, nrow = 2)

^{Created on 2021-02-18 by the reprex package (v1.0.0)}

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