How to rearrange legend order in ggplot-CodePudding

I am plotting the graph in ggplot. Everything was fine but now I have a problem with the legend. i want to rearrange the legend. The legend that I am getting now is

0-63

100-200

200-400

63-100

what I want is. I want to move the last value to the 2nd position. It should be like that

0-63

63-100

100-200

200-400

my code is below

my data look like this but up to 1000 rows

time  less63  63_100    100_200   200_400
06:01   0       4        3           1
06:02   2       6        6           5
06:03   4       8        8           6
06:04   6       9        7           8
06:05   7       10       8           7
06:06   3       11       3           7
06:07   6       7        2           2
06:08   7       3        0           3





ggplot(df) 
      geom_area(aes(x=time,y=less63,fill="0-63"),alpha=0.5) 
      geom_area(aes(x=time,y=63_100,fill="63-100"),alpha=0.5) 
      geom_area(aes(x=time,y=100_200,fill="100-200"),alpha=0.5) 
      geom_area(aes(x=time,y=200_400,fill="200-400"),alpha=0.5) 
      scale_colour_manual(name="Legend", values = c("0-63" = "red","63-100" = "green","100-200" = "black","200-400" = "blue"))

I shall be really thankful in this regard

CodePudding user response：

The first thing you want to do here is put your data into

Update: Overlapping Plot

The OP indicated they were creating an overlapping plot. By default, the position of the layers mapped to fill in geom_are() is set to "stacked", which means the y values are stacked on top of one another. This makes it easy to view and see the way the areas change over the x axis. However, OP wanted to prepare a plot where the y values are... the value. This would be position="identity" and creates overlapping areas. You can see the direct effect here:

ggplot(df, aes(x=time, y=val, fill=ranges))  
  geom_area(alpha=0.2, position="identity")  
  scale_x_time(labels = scales::time_format(format = "%M:%S"))  
  scale_fill_manual(name="Legend", values = c("0-63" = "red","63-100" = "green","100-200" = "black","200-400" = "blue"))

You can see that even cutting down the alpha= value, this is going to be hard to discern what's going on. If you want to see this information more clearly, I would recommend using horizontally-placed facets as a better viewing option:

ggplot(df, aes(x=time, y=val, fill=ranges))  
  geom_area(alpha=0.2, position="identity")  
  scale_x_time(labels = scales::time_format(format = "%M:%S"))  
  scale_fill_manual(name="Legend", values = c("0-63" = "red","63-100" = "green","100-200" = "black","200-400" = "blue"))  
  facet_grid(ranges ~ .)

CodePudding user response：

I suggest using tidyr::pivot_longer() on your data so that it looks like this.

time variable value 1 06:01 less63 0 2 06:01 63_100 4

etc...

Then use ordered() to set "variable" as an ordered factor. Then use geom_area(aes(x = time, y = variable, full = variable)

CodePudding user response：

Bring your data in long format with pivot_longer
transform name to factor (level and label it)
In ggplot use fill and group

Custom OP:

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

df %>% 
  pivot_longer(
    -time
  ) %>% 
  mutate(name = factor(name, levels = c("less63", "X63_100", "X100_200", "X200_400"),
                       labels = c("0-63","63-100","100-200","200-400"))) %>% 
  ggplot(aes(x=factor(time), y=value, fill=name, group=name)) 
  geom_area(position = "identity", alpha=0.5)  
  scale_fill_manual(name="Legend", values = c("0-63" = "red","63-100" = "green","100-200" = "black","200-400" = "blue"))

General approach:

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

df %>% 
  pivot_longer(
    -time
  ) %>% 
  mutate(name = factor(name, levels = c("less63", "X63_100", "X100_200", "X200_400"))) %>% 
  ggplot(aes(x=time, y=value, fill=name, group=name)) 
  geom_area()