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I have a dataset that looks like this:

  Distance  Mean    SD Median    VI Vegetation.Index       Direction  X X.1 X.2 X.3
1      10m 0.525 0.082  0.530  NDVI             NDVI Whole Landscape NA  NA  NA  NA
2      25m 0.517 0.085  0.523  NDVI             NDVI Whole Landscape NA  NA  NA  NA
3      50m 0.509 0.086  0.514  NDVI             NDVI Whole Landscape NA  NA  NA  NA
4     100m 0.494 0.090  0.497  NDVI             NDVI Whole Landscape NA  NA  NA  NA
5      10m 0.545 0.076  0.551 NDVIe             NDVI            East NA  NA  NA  NA
6      25m 0.542 0.078  0.549 NDVIe             NDVI            East NA  NA  NA  NA


> dput(droplevels(head(data)))
structure(list(Distance = structure(c(2L, 3L, 4L, 1L, 2L, 3L), .Label = c("100m", 
"10m", "25m", "50m"), class = "factor"), Mean = c(0.525, 0.517, 
0.509, 0.494, 0.545, 0.542), SD = c(0.082, 0.085, 0.086, 0.09, 
0.076, 0.078), Median = c(0.53, 0.523, 0.514, 0.497, 0.551, 0.549
), VI = structure(c(1L, 1L, 1L, 1L, 2L, 2L), .Label = c("NDVI", 
"NDVIe"), class = "factor"), Vegetation.Index = structure(c(1L, 
1L, 1L, 1L, 1L, 1L), .Label = "NDVI", class = "factor"), Direction = structure(c(2L, 
2L, 2L, 2L, 1L, 1L), .Label = c("East", "Whole Landscape"), class = "factor"), 
X = c(NA, NA, NA, NA, NA, NA), X.1 = c(NA, NA, NA, NA, NA, 
NA), X.2 = c(NA, NA, NA, NA, NA, NA), X.3 = c(NA, NA, NA, 
NA, NA, NA)), .Names = c("Distance", "Mean", "SD", "Median", 
"VI", "Vegetation.Index", "Direction", "X", "X.1", "X.2", "X.3"
), row.names = c(NA, 6L), class = "data.frame")

I would like to create a barplot facet grid with a categorical variable on the x-axis (Distance), continuous variable on the y-axis (vegetation index) and two bars (mean and median vegeation index values) for each barplot. The bar plots facet by 'Direction' and 'Vegetation Index'.

I have done this with one type of measure (mean), pictured below.

enter image description here

Here is the code I have now:

 p = ggplot(data,aes(x=Distance,y=Mean,fill=Distance)) + geom_bar(stat =
    'identity',position='dodge')+ facet_grid(Direction~Vegetation.Index)+ 
    coord_cartesian(ylim=c(0.2,0.95)) + geom_errorbar(data = data,
    aes(ymin=Mean-SD,ymax=Mean+SD),width=0.5)

But I also want a bar for median beside it.

Like this but for all the bar plots in the facet grid.

I found some threads of people wanting to do this exact or similar thing, and found them to be fairly useful:

This

Or this

However, my data looks very different from theirs (I think) and changing it in any way messes up what I already have. From what I understand I have to use group='Mean+Median'.

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    Please make a reproducible example (click link for many tips). Do not share images of data. Instead (a) use built-in data that looks like your data, (b) share short code to simulate sample data, or (c) use dput() to reproducibly share your data (or maybe a subset of your data). Commented Nov 14, 2016 at 19:15
  • Also, please be clearer about your desired output. "multiple continuous variables along the x-axis" doesn't make much sense, especially for a barplot. The x-axis of a bar plot is categorical, not continuous. Do you mean that you want the type of measure along the x-axis, for example one bar for median, one bar for mean? Commented Nov 14, 2016 at 19:20
  • With your clarification, it does appear that your first question link is a nearly-exact duplicate. You will need to convert your data to a long format where you have a single "measure" column that takes values either "mean" or "median" and a single "value" column that takes the numeric values of the mean or median. You can use melt just like in this answer to do that. Commented Nov 14, 2016 at 20:59
  • You will have better luck working with ggplot if you can adjust your thinking about your variables. The only continuous variable in the bar plot is the y-axis. You want the continuous values on the y-axis, and you want the categorical measure (mean or median) on the x-axis. I will happily demonstrate in an answer if you share your data reproducibly as requested above. Without specific data shared in a usable way, I would instead recommend closing your question as a duplicate of the one you linked. Commented Nov 14, 2016 at 21:01
  • Thank you so much Gregor for the comments and suggestions! I posted a sample of my data along with the dput() you suggested. I hope that is reproducible. Commented Nov 14, 2016 at 21:09

1 Answer 1

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2

Using your sample data, we first convert it to long format. I use tidyr::gather here, but reshape2::melt (or data.table::melt) work similarly.

library(tidyr)
dfl = gather(df, key = measure, value = value, Mean, Median)

dodge_width = 0.8
ggplot(dfl,
       aes(x = measure, y = value, fill = Distance, group = Distance)) +
    geom_bar(stat = 'identity',
             position = position_dodge(dodge_width),
             width = dodge_width) +
    facet_grid(Direction ~ Vegetation.Index) + 
    coord_cartesian(ylim = c(0.2, 0.95)) + 
    geom_errorbar(
        aes(ymin = value - SD, ymax = value + SD),
        width=0.5,
        position = position_dodge(dodge_width)
    )

enter image description here

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3 Comments

Amazing. You have been extremely helpful. Thank you so much! this also pinpointed exactly where my attempt went wrong. I'm quite new to R so syntax is a bit unwieldy at the moment. Thanks again!!
Glad you found it helpful! If you plan on using ggplot much, I'd strongly recommend reading the Tidy Data paper - 95% of new user struggles with ggplot are getting data in the correct format, and the tidy data paper helps describe the goals. And next time you ask a question on SO, you'll know to share data reproducibly from the start :)
I will definitely give that a read! Ditto on sharing data. Thanks again!

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