'Stacking multiple plots, vertically with the same x axis but different Y axes in R

I have a data.frame with multiple time series vectors against a date:time vector. I would like to plot all of the relevant vectors, vertically stacked on separate graphs with the same X axis but unique Y axes. A graph similar to this one: enter image description here

my data looks like this:

 dt <- structure(list(DEPTH = c(156, 156.5, 157.4, 158.15, 158.8, 159.2, 
159.75, 160.35, 160.85, 161.1, 161.6, 162.05, 162.5, 162.65, 
163.15, 163.45, 163.55, 163.8, 163.65, 163.75, 163.8, 163.8, 
163.75, 164.45, 164.8, 165.35, 165.65, 165.75, 166.1, 166.75, 
167, 167.2, 167.65, 168, 168.8, 169.3, 169.7, 170.2, 170.65, 
170.9, 171.45, 171.65, 172, 172.1, 172.25, 173, 173.4, 173.9, 
174.2, 174.6, 175, 175.25, 175.45, 175.9, 176.25, 176.7, 177, 
177.15, 177.5, 178, 178.5, 179.05, 179.2, 180.7, 181.05, 181.25, 
181.5, 181.7, 182.1, 182.3, 182.35, 182.75, 183.1, 183.65, 184.3, 
184.6, 185.1, 185.15, 185.3, 185.15, 185.25, 185.3, 185.15), 
    Smooth.Vert.Speed = c(-0.550000000000011, -0.5, -0.900000000000006, 
    -0.75, -0.650000000000006, -0.399999999999977, -0.550000000000011, 
    -0.599999999999994, -0.5, -0.25, -0.5, -0.450000000000017, 
    -0.449999999999989, -0.150000000000006, -0.5, -0.299999999999983, 
    -0.100000000000023, -0.25, 0.150000000000006, -0.0999999999999943, 
    -0.0500000000000114, 0, 0.0500000000000114, -0.699999999999989, 
    -0.350000000000023, -0.549999999999983, -0.300000000000011, 
    -0.0999999999999943, -0.349999999999994, -0.650000000000006, 
    -0.25, -0.199999999999989, -0.450000000000017, -0.349999999999994, 
    -0.800000000000011, -0.5, -0.399999999999977, -0.5, -0.450000000000017, 
    -0.25, -0.549999999999983, -0.200000000000017, -0.349999999999994, 
    -0.0999999999999943, -0.150000000000006, -0.75, -0.400000000000006, 
    -0.5, -0.299999999999983, -0.400000000000006, -0.400000000000006, 
    -0.25, -0.199999999999989, -0.450000000000017, -0.349999999999994, 
    -0.449999999999989, -0.300000000000011, -0.150000000000006, 
    -0.349999999999994, -0.5, -0.5, -0.550000000000011, -0.149999999999977, 
    -1.5, -0.350000000000023, -0.199999999999989, -0.25, -0.199999999999989, 
    -0.400000000000006, -0.200000000000017, -0.049999999999983, 
    -0.400000000000006, -0.349999999999994, -0.550000000000011, 
    -0.650000000000006, -0.299999999999983, -0.5, -0.0500000000000114, 
    -0.150000000000006, 0.150000000000006, -0.0999999999999943, 
    -0.0500000000000114, 0.150000000000006), DIVE_SURF = c("dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21", "dive21", "dive21", 
    "dive21", "dive21", "dive21", "dive21"), X = c(2050L, 2062L, 
    2026L, 2078L, 2058L, 2076L, 2050L, 2068L, 2060L, 2078L, 2058L, 
    2088L, 2080L, 2065L, 2088L, 2076L, 2084L, 2105L, 2084L, 2102L, 
    2123L, 2096L, 2074L, 2054L, 2090L, 2089L, 2080L, 2078L, 2068L, 
    2092L, 2084L, 2082L, 2094L, 2056L, 2062L, 2067L, 2082L, 2084L, 
    2091L, 2058L, 2076L, 2098L, 2104L, 2090L, 2058L, 2050L, 2080L, 
    2074L, 2074L, 2082L, 2070L, 2088L, 2062L, 2062L, 2082L, 2086L, 
    2070L, 2081L, 2092L, 2058L, 2060L, 2076L, 2094L, 2083L, 2072L, 
    2107L, 2104L, 2066L, 2110L, 2104L, 2072L, 2076L, 2065L, 2042L, 
    2066L, 2093L, 2080L, 2083L, 2108L, 2107L, 2086L, 2096L, 2126L
    ), Y = c(2036L, 2000L, 2049L, 1966L, 2042L, 2078L, 2072L, 
    2055L, 2036L, 2128L, 2044L, 2112L, 2066L, 2051L, 2102L, 2060L, 
    2054L, 2043L, 2034L, 2086L, 1980L, 2076L, 2003L, 2033L, 2107L, 
    1992L, 2028L, 2027L, 2024L, 2005L, 2050L, 2010L, 1944L, 2010L, 
    2046L, 2020L, 2088L, 2086L, 2034L, 2066L, 2060L, 2152L, 2044L, 
    2078L, 2040L, 2067L, 2080L, 2072L, 2073L, 2028L, 2066L, 2082L, 
    2030L, 2042L, 1990L, 2076L, 2054L, 2064L, 2016L, 2048L, 2029L, 
    2008L, 2090L, 2038L, 2026L, 2096L, 2002L, 2025L, 2001L, 2098L, 
    2061L, 2022L, 2054L, 2064L, 2043L, 2090L, 2042L, 2086L, 2073L, 
    2066L, 2040L, 2081L, 2087L), Z = c(2488L, 2484L, 2490L, 2486L, 
    2488L, 2492L, 2498L, 2490L, 2492L, 2484L, 2491L, 2494L, 2497L, 
    2493L, 2488L, 2493L, 2494L, 2484L, 2486L, 2487L, 2478L, 2490L, 
    2478L, 2493L, 2490L, 2486L, 2488L, 2486L, 2488L, 2482L, 2488L, 
    2480L, 2480L, 2488L, 2490L, 2490L, 2490L, 2489L, 2492L, 2490L, 
    2486L, 2480L, 2488L, 2491L, 2486L, 2488L, 2488L, 2494L, 2490L, 
    2488L, 2492L, 2498L, 2484L, 2491L, 2480L, 2491L, 2497L, 2487L, 
    2482L, 2490L, 2490L, 2478L, 2488L, 2492L, 2492L, 2482L, 2484L, 
    2489L, 2482L, 2484L, 2485L, 2492L, 2488L, 2493L, 2487L, 2490L, 
    2492L, 2488L, 2490L, 2487L, 2484L, 2486L, 2478L)), .Names = c("DEPTH", 
"Smooth.Vert.Speed", "DIVE_SURF", "X", "Y", "Z"), row.names = 7222:7304, class = "data.frame")

and I am looking to plot DEPTH, X, Y and Z on separate graphs with a common X axis.

r plot data-visualization

Solution 1:^[1]

If you want to be old-fashioned you can use lattice. Unlike @aaronwolen I assumed there was a missing time variable in the data set, so I made one up:

dt$time <- seq(nrow(dt))
library(reshape2)
mm <- melt(subset(dt,select=c(time,DEPTH,X,Y,Z)),id.var="time")
library(lattice)
xyplot(value~time|variable,data=mm,type="l",
       scales=list(y=list(relation="free")),
       layout=c(1,4))

enter image description here

Solution 2:^[2]

I agree with @PaulHiemstra, ggplot2 is the way to go.

Assuming Smooth.Vert.Speed is the common x-axis variable against which you want to plot DEPTH, X, Y and Z...

library(ggplot2)
library(reshape2)

# Add time variable as per @BenBolker's suggestion
dt$time <- seq(nrow(dt))

# Use melt to reshape data so values and variables are in separate columns
dt.df <- melt(dt, measure.vars = c("DEPTH", "X", "Y", "Z"))

ggplot(dt.df, aes(x = time, y = value)) +
  geom_line(aes(color = variable)) +
  facet_grid(variable ~ ., scales = "free_y") +
  # Suppress the legend since color isn't actually providing any information
  opts(legend.position = "none")

Plotting multiple y-variables against a common x-variable

Solution 3:^[3]

Just to be different, let me mention a solution involving neither lattice nor ggplot2 -- I posted this to Romain's R Graph Gallery a few years back as entry 65 with the code here. It just stacks the graphs up, using par() settings to keep them stacked.

Note that the vertical sizes are different by choice, they could easily be of the same height as well.

enter image description here

Solution 4:^[4]

I've actually figured out another interesting way of doing this with the zoo library:

library(zoo)
z <- with(dt, zoo(cbind(DEPTH, X, Y, Z),as.POSIXct(time))) 
plot.zoo(z,  ylab=c("Depth (m)", "Pitch Angle (degrees)", "Swaying Acceleration (m/s^2)", "Heaving Acceleration (m/s^2)"), col=c("black", "blue", "darkred", "darkgreen"), 
     xlab = c("Time"), lwd=2, ylim=list((rev(range(dt$DEPTH))), c(-90,90), c(-10,10), c(-10,10)))

So within a zoo plot you can create new axis labels as a list form and all plots can have different colours.

Solution 5:^[5]

Please read this example:

Generate example data:

dt = read_table("Time        A       B       C       D
10:12:54    2376.2  1.462   3.462   48
10:12:55    2410    1.462   3.462   48
10:12:56    2400    1.462   3.462   48
10:12:57    2409    1.462   3.462   48.6
10:12:58    2400    1.462   3.462   48.6
10:12:59    2385.1  1.462   3.462   46.6
10:13:00    2400    1.462   3.462   46.6
10:13:01    2410    1.462   3.462   46.6
10:13:02    2400    1.462   3.462   46.6
10:13:03    2106    1.463   3.463   46.6
10:13:04    2406    1.463   3.463   44.8
10:13:05    2376.2  1.463   3.463   44.8
10:13:06    2406    1.463   3.463   44.8
10:13:07    2400    1.463   3.463   44.8")
dt$Time=as.POSIXct(dt$Time)

If you want to plot it quickly, try this:

library(foqat)
geom_ts_batch(dt, panelgap=4)

If you want to plot it with more degree of freedom, try this:

library(foqat)
library(patchwork)
blankx=theme(axis.title.x=element_blank(),axis.text.x=element_blank(),axis.ticks.x=element_blank())
p2=geom_ts(dt, yl=2, llist=2, lcc="blue", yllab="A")+blankx
p3=geom_ts(dt, yl=3, llist=3, lcc="red", yllab="B")+blankx
p4=geom_ts(dt, yl=4, llist=4, lcc="green", yllab="C")+blankx
p5=geom_ts(dt, yl=5, llist=5, lcc="grey", yllab="D", xlab="Time")
p2/p3/p4/p5

Sources

This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.

Source: Stack Overflow

Solution	Source
Solution 1	Ben Bolker
Solution 2
Solution 3	Dirk Eddelbuettel
Solution 4
Solution 5

'Stacking multiple plots, vertically with the same x axis but different Y axes in R

Solution 1:[1]

Solution 2:[2]

Solution 3:[3]

Solution 4:[4]

Solution 5:[5]