ggplot2 - Vertical profile in r plot() -

i building vertical profile plot of water columns. issue dots connected on x observations, , not y observations. under ggplot, know geom_path can this, can't use ggplot want add several x axis. therefore using plot(). here tried:

storfjorden <- read.delim("c:/users/carvi/desktop/storfjorden.txt") smoof=smooth.spline(storfjorden$fluorescence,storfjorden$depth,spar=0.50) plot(storfjorden$fluorescence,storfjorden$depth,ylim=c(80,0),type="n") lines(smoof) 

resulting plot

as see, dots connected through x observations. observe vertical profile, see them connected through y observations. tried ordering them depth (using order()) , didn't affect result. has clue?

if, alternative, have idea how plot different lines different axis on single plot (temperature, salinity, fluorescence), may use geom_path (). thank you!

**an emerging question have may answer, there way in ggplot make geom_smooth(), observations connected in order appear instead of x axis?

ggplot(melteddf,aes(y=depth,x=value))+geom_path()+facet_wrap +(~variable,nrow=1,scales="free‌​_x")+scale_y_reverse‌​() +geom_smooth(span=‌​0.5,se=false)  

i tried using smooth.spline, didn't recognize object in geom_path. thanks!

there reason ggplot2 makes difficult plot multiple x-axes on single plot -- leads difficult read (or worse, misleading) graphs. if have motivating example why example not fall 1 of categories, might allow more know more details. below, however, 2 workarounds might help.

here quick mwe address question -- might more helpful if gave looks actual data, @ least gets things on different scales (though, no structure, plots rather messy).

note using dplyr several manipulations , reshape2 melt data long format easier plotting.

library(dplyr) library(reshape2)  df <-   data.frame(     depth = runif(20, 0, 100) %>% round %>% sort     , measurea = rnorm(20, 10, 3)       , measureb = rnorm(20, 50, 10)     , measurec = rnorm(20, 1000, 30)   )   melteddf <-   df %>%   melt(id.vars = "depth") 

the first option use facets plot data next each other:

melteddf %>%   ggplot(aes(y = depth              , x = value)) +   geom_path() +   facet_wrap(~variable              , nrow = 1              , scales = "free_x") +   scale_y_reverse() 

the second standardize data, plot that. here, using z-score, though if have reason use else (e.g. scaled center @ "appropriate" amount of whatever variable using) change formula:

melteddf %>%   group_by(variable) %>%   mutate(standardized = (value - mean(value)) / sd(value)  ) %>%   ggplot(aes(y = depth              , x = standardized              , col = variable)) +   geom_path() +   scale_y_reverse() 

if need plot multiple sites, here sample data sites:

df <-   data.frame(     depth = runif(60, 0, 100) %>% round %>% sort     , measurea = rnorm(60, 10, 3)       , measureb = rnorm(60, 50, 10)     , measurec = rnorm(60, 1000, 30)     , site = sample(letters[1:3], 60, true)   )   melteddf <-   df %>%   melt(id.vars = c("site", "depth")) 

you can either use facet_grid (my preference):

melteddf %>%   ggplot(aes(y = depth              , x = value)) +   geom_path() +   facet_grid(site~variable              , scales = "free_x") +   scale_y_reverse() 

or add facet_wrap standardized plot:

melteddf %>%   ggplot(aes(y = depth              , x = value)) +   geom_path() +   facet_grid(site~variable              , scales = "free_x") +   scale_y_reverse()