standard deviation bars shuffle between the factor levels and facets in ggplot2

Question

data<-sample_data
Temperature<-as.factor(data$Temperature)
#to change the orientation of the factor levels
data$ZT<-factor(data$ZT, levels = c( "T0",  "T2",  "T4",  "T6",  "T8",  "T10", "T12", "T14", "T16", "T18", "T20", "T22") )
ZT<-data$ZT
#to change the orientation of the factor levels
data$Genotype<-factor(data$Genotype, levels =c("Scarlett","S42-IL107","S42-IL176"))
Genotype<-data$Genotype
co1 <-data$co1
SD<-data$co1_sd

    ggplot(data, aes(x= ZT,y=co1, group=Temperature, shape=Temperature, colour=Temperature)) +
      geom_errorbar(aes(ymin=co1-SD, ymax=co1+SD), width=.7, size=.7)+
      geom_line(aes(colour=Temperature), size=1.1)+
      geom_point(aes(shape=Temperature),size=4)+
      scale_color_manual(values=c("turquoise3","indianred2"))+
      ylab("HvCO1 normalised expression")+
      xlab(NULL)+
      facet_wrap(~ Genotype,)

I am using this script to create facetted plot in ggplot2, sometimes script works fine but often it happens that data points get shuffled between the factor levels on one facet or between the facets. at the moment standard error bars are shuffled instead of data points. can somebody tell me why is this occurring?

here i compared this with excel graph on the same data. error bars of facet 2 and three.

structure(list(Genotype = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L), .Label = c("S42-IL107", "S42-IL176", "Scarlett"), class = "factor"), 
    Temperature = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L), .Label = c("20°C", "28°C"), class = "factor"), 
    ZT = structure(c(1L, 7L, 10L, 11L, 12L, 2L, 3L, 4L, 5L, 6L, 
    8L, 9L, 1L, 7L, 10L, 11L, 12L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 
    1L, 7L, 10L, 11L, 12L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 5L, 6L, 
    8L, 9L, 1L, 7L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 7L, 10L, 11L, 
    12L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 1L, 7L, 10L, 11L, 12L, 2L, 
    3L, 4L, 5L, 6L, 8L, 9L), .Label = c("T0", "T10", "T12", "T14", 
    "T16", "T18", "T2", "T20", "T22", "T4", "T6", "T8"), class = "factor"), 
    co1 = c(0.004047961, 0.002880266, 0.001519785, 0.000667166, 
    0.000722255, 0.001466025, 0.004227897, 0.005888254, 0.007957774, 
    0.007576948, 0.005425386, 0.006893992, 0.005856547, 0.002997377, 
    0.001162904, 0.000576041, 0.000504455, 0.000508026, 0.001192632, 
    0.002094363, 0.005691455, 0.005918894, 0.007556918, 0.007736937, 
    0.007104176, 0.00584571, 0.002929043, 0.001618641, 0.002028418, 
    0.003404469, 0.010245418, 0.011297415, 0.009594296, 0.010923272, 
    0.01016621, 0.006077751, 0.005442749, 0.005538876, 0.006345497, 
    0.005632192, 0.007438102, 0.005501253, 0.002168485, 0.00111058, 
    0.000951645, 0.001391862, 0.001377207, 0.003435266, 0.00514792, 
    0.004080233, 0.002140552, 0.001426237, 0.002272299, 0.004213762, 
    0.008400302, 0.008992385, 0.006691724, 0.008404276, 0.007611373, 
    0.005460758, 0.001109314, 0.000732904, 0.000268885, 0.000244801, 
    0.000280516, 0.00077615, 0.001283453, 0.003493581, 0.004653499, 
    0.002507832, 0.002864612, 0.001727669), co1_sd = c(0.00029648, 
    0.000613192, 0.000221025, 0.000224196, 0.000223837, 0.00044702, 
    0.000706827, 0.001155351, 0.000232335, 0.00032364, 0.000602965, 
    0.001063606, 0.000923741, 0.000410751, 0.000150132, 0.000303137, 
    0.000104852, 0.000114863, 0.000569747, 0.00063052, 0.003203487, 
    0.001025025, 0.00301162, 0.003984255, 0.001973626, 0.001211777, 
    0.000226229, 0.000558652, 0.000615758, 0.000770557, 0.000956524, 
    0.001361853, 0.001474607, 0.002037219, 0.001628115, 0.002383452, 
    0.000147587, 0.000699657, 0.001651883, 0.00174892, 0.001190546, 
    0.000660793, 0.000635082, 0.000207585, 0.000226194, 0.000328652, 
    0.000640193, 0.001926859, 0.00069947, 0.000505254, 0.000178241, 
    0.000205647, 0.000348112, 0.000289324, 0.003999638, 0.001073981, 
    0.000260649, 0.001288045, 0.001187429, 0.000991558, 9.29063e-05, 
    4.65434e-05, 2.95757e-05, 5.16943e-05, 0.000144199, 0.000470742, 
    0.000250978, 0.000972389, 0.00049583, 0.000280404, 0.000529082, 
    0.000287902)), .Names = c("Genotype", "Temperature", "ZT", 
"co1", "co1_sd"), class = "data.frame", row.names = c(NA, -72L
))

please add the data so that we can reproduce the problem with your code — erc, Jun 17 '16 at 11:20
can I attach the data file somewhere here because I want to know what exactly the problem is in my data — ashar14, Jun 17 '16 at 11:50
you can add the output of `dput(yourdata)` to your question (if it's a lot of data a subset with which the error can be reproduced is enough), see [here](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) for help. — erc, Jun 17 '16 at 11:55
Thanks. I added the sample data and the complete script how I am using it. — ashar14, Jun 17 '16 at 12:06
Can you add an image of the plot you get? Looks fine to me when I run your code. — erc, Jun 17 '16 at 12:20
ggplot2 is made to work with tidy data, so work with the variables within your dataset. In your case, you made `SD` as a vector outside of your dataset so things were no longer mapped properly. Just use the `co1_sd` that is already in your dataset for your error bars; i.e., `ymin = co1-co1_sd`, etc. — aosmith, Jun 17 '16 at 13:55

standard deviation bars shuffle between the factor levels and facets in ggplot2

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