Ggplot2 Line Plot Order

ggplot2 line plot order

geom_path() will join points in the original order, so you can order your data in the way you want it joined, and then just do + geom_path(). Here's some dummy data:

dat <- data.frame(x = sample(1:10), y = sample(1:10), order = sample(1:10))
ggplot(dat[order(dat$order),], aes(x, y)) + geom_point() + geom_text(aes(y = y + 0.25,label = order)) +
  geom_path()

How can I define line plotting order in ggplot2 for grouped lines?

One way would be to subset your data when you draw lines. You want to draw lines for the false group first, then the true group.

ggplot(data = df, aes(x = x, y = y, colour = flag,
       group = group)) +
geom_line(data = subset(df, flag == "false"), size = 3) +
geom_line(data = subset(df, flag == "true"), size = 3)

Arrange line plot by order of the variables in data frame

Use geom_path, this will sort by occurrence in your data frame.

I'd advise keep dates actually stored as dates. The problem is that your factor/character order is defined by the day. By converting this into dates, and converting this into a character with as.character(lubridate::dmy(day)), the order will be "correct".

# devtools::install_github("alistaire47/read.so")
library(tidyverse)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
dataset_lago <- read.so::read_md("| Depth     | P_Total        | day |
| -------- | -------------- | --------------  | 
| 0    | 401.27    | 26_05_11 |
| 2    | 206.24    | 26_05_11 |
| 4.8   | 163.79    | 26_05_11 |        
| 0     | 255.92    | 12_01_12 |                
| 2     | 167.72    | 12_01_12|
| 5     | 300.29    | 12_01_12 | ")

dataset_lago %>%
  mutate(day = dmy(day)) %>%
ggplot(mapping= aes(x = P_Total, y= Depth))+
  geom_path(aes(P_Total, colour= as.character(day)))+
  scale_y_reverse()+
  theme(plot.title = element_text(hjust = 0.5))+
  labs(x = "P_Total", y = "Depth") +
  theme_minimal()

^{Created on 2021-01-23 by the reprex package (v0.3.0)}

ggplot geom_line: Change order of plotting

I found the solution in the process of writing the question, and I thought I might share this, since it could be helpfull for other people :°).

It seems like we can refactor the leves according to a different column like this:

df$ID <- as.factor(df$ID)
df$System <- as.factor(df$System)

df$ID <- factor(df$ID, 
               levels = c(c(unique(as.factor(df$ID[c(which(df$System == 'a'))]))),
                          c(unique(as.factor(df$ID[c(which(df$System == 'b'))]))),
                          c(unique(as.factor(df$ID[c(which(df$System == 'c'))]))),
                          c(unique(as.factor(df$ID[c(which(df$System == 'd'))])))
                          )
               )

Executing this, we're looking for those row'swhich are part of group a. Then we take the line number to get the ID's of those samples and pass them as an unique (there are multiple samples with the same name) vector to the levels parameter. We repeat that for each group.

This results in this plot (take the code from the question):

Now the lines in the largest group a are plotted first

Change the overlaying order of lines in ggplot

So actually the last level of col is on the top. So you need to change the order of the factor and reverse the colors as red is automatically mapped to the first level (used standard colors to illustrate the problem):

pl_data$col <- factor(pl_data$col, c("r", "g", "b"))
ggplot(pl_data, aes(x = x, y = y, color = col)) +
    geom_line(size = 3) + 
    scale_color_manual(values = c(r = "blue", g = "green", b = "red"))

## with standard colors of ggplot2, function taken from:
## http://stackoverflow.com/questions/8197559/emulate-ggplot2-default-color-palette

ggplotColours <- function(n = 6, h = c(0, 360) + 15) {
  if ((diff(h) %% 360) < 1) h[2] <- h[2] - 360/n
  hcl(h = (seq(h[1], h[2], length = n)), c = 100, l = 65)
}
pal <- setNames(ggplotColours(3), c("b", "g", "r"))
ggplot(pl_data, aes(x = x, y = y, color = col)) +
    geom_line(size = 3) + 
    scale_color_manual(values = pal, breaks = c("b", "g", "r"))

ggplot - line ordering, one line on top of the other

Change the factor level order. Don't forget to change the group too.

See this related thread, why I used scales::hue() etc

library(tidyverse)

forecast <- c(2,2,1,2,2,3,2,3,3,3,3)
actual <- c(2,2,1,2,2,3,2,3,2,2,1)

my_df <- data.frame(forecast = forecast, actual = actual, seq_order = 1:11) 
my_df <-gather(my_df, line_type, value, -seq_order) %>% mutate(type = factor(line_type, levels = c('forecast','actual')))

ggplot(data=my_df, aes(x=seq_order, y = value, 
                       colour = type, group = type)) +
  geom_line()+
  theme(legend.position="bottom") +
  scale_color_manual(values = rev(scales::hue_pal()(2)))

^{Created on 2020-03-24 by the reprex package (v0.3.0)}

Method of ordering groups in ggplot line plot

The issue is that the order by which geom_line connects the points is determined by the value on the x-axis. To solve this issue simply swap x and y and make use of coord_flip.

As no sample dataset was provided I use an example dataset based on mtcars to illustrate the issue and the solution. In my example data make is your vars, value your EI1 and name your groups:

library(ggplot2)
library(dplyr)
library(tidyr)
library(forcats)

example_data <- mtcars %>%
  mutate(make = row.names(.)) %>%
  select(make, hp, mpg) %>% 
  mutate(make = fct_reorder(make, hp)) %>% 
  pivot_longer(-make)

Mapping make on x and value on y results in an unordered line plot as in you example. The reason is that the order by which the points get connected is determined by value:

example_data %>% 
  ggplot(aes(x = value, y = make, color = name, group = name)) + 
  geom_line() + 
  geom_point() +
  xlab("EI1 (Expected Influence with Neighbor)") +
  ylab("Variables")

In contrast, swapping x and y, i.e. mapping make on x and value on y, and making use of coord_flip gives a nice ordererd line plot as the order by which the points get connected is now determined by make (of course we also have to swap xlab and ylab):

example_data %>% 
  ggplot(aes(x = make, y = value, color = name, group = name)) + 
  geom_line() + 
  geom_point() +
  coord_flip() +
  ylab("EI1 (Expected Influence with Neighbor)") +
  xlab("Variables")

Make a ggplot line plot where lines follow row order

Using your data,

ggplot(DF, aes(x=X,y=Y))+geom_point()+geom_path()

Produces this, which sounds like what you are asking(??)

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