saving figures like a loop until end of a data frame - r

I have a data like this and I want to save figures one after another by
df<- structure(list(x = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L), rn = structure(c(1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L), .Label = c("AAAAA",
"BBBBB", "CCCCC", "DDDDD"), class = "factor"), key = structure(c(2L,
4L, 3L, 1L, 2L, 4L, 3L, 1L, 2L, 4L, 3L, 1L, 2L, 4L, 3L, 1L), .Label = c("WSAfrica",
"Wscanada", "WSInida", "WSUSA"), class = "factor"), Median = c(0.000621,
0.000777, 0.000574, 0.000537, 0.000381, 0.00177, 0.002, 0.000457,
0.00247, 0.00199, 0.00287, 0.00224, 5.94e-05, 4.12e-05, 4.44e-05,
5.68e-05), SD = c(0.000127453, 0.000107802, 0.001048659, 9.32e-05,
9.23e-05, 0.000120554, 0.000914697, 0.000167046, 0.000125033,
0.000410528, 0.000450444, 0.000310483, 5.91e-06, 8.98e-06, 1.11e-05,
1.16e-05)), class = "data.frame", row.names = c(NA, -16L))
I tried the following function but I get an error saying that
Error in UseMethod("grid.draw") : no applicable method for
'grid.draw' applied to an object of class "function"
d_ply(df, .(rn),
function(x) (ggplot(x, aes(x = x, y = Median))+
geom_point() +
scale_x_discrete(limit = c("Wscanada", "WSUSA", "WSInida","WSAfrica")) +
geom_errorbar(aes(ymin = Median-SD, ymax = Median+SD))+
ggsave(., filename = paste0("", x$rn[1],".pdf"))))


You're already adding the plot to ggsave, no need to use the . for the first argument:
d_ply(df, .(rn),
function(x) (ggplot(x, aes(x = x, y = Median))+
geom_point() +
scale_x_discrete(limit = c("Wscanada", "WSUSA", "WSInida","WSAfrica")) +
geom_errorbar(aes(ymin = Median-SD, ymax = Median+SD))+
ggsave(filename = paste0("", x$rn[1],".pdf"))))

Related

Creating a box and whisker plot with ggplot() troubleshooting

UPDATED:
Data has now been updated to full chemistry values as opposed to mean values.
I am attempting to create a box and whisker plot in r, on a very small dataset. My data is not behaving itself or I am missing some glaringly obvious error.
This is the code i have for making said plot
library(ggplot2)
Methanogenesis_Data=read.csv("CO2-CH4 Rates.csv")
attach(Methanogenesis_Data)
summary(Methanogenesis_Data)
str(Methanogenesis_Data)
boxplot(CH4rate~Patch+Temperature, data = Methanogenesis_Data,
xlab="Patch", ylab="CH4 Production")
cols<-c("red", "blue")
From this small dataset.
structure(list(Patch = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Gravel", "Macrophytes",
"Marginal"), class = "factor"), Temperature = structure(c(2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("Cold",
"Warm"), class = "factor"), CH4rate = c(0.001262595, 0.00138508,
0.001675944, 0.001592354, 0.002169233, 0.001772964, 0.002156633,
0.002864403, 0.002301383, 0.002561042, 0.005189598, 0.004557227,
0.008484851, 0.006867866, 0.007438633, 0.005405327, 0.006381582,
0.008860084, 0.007615417, 0.007705906, 0.009198508, 0.00705233,
0.007943024, 0.008319768, 0.010362114, 0.007822153, 0.010339339,
0.009252302, 0.008249555, 0.008197657), CO2rate = c(0.002274825,
0.002484866, 0.003020209, 0.00289133, 0.003927232, 0.003219346,
0.003922613, 0.005217026, 0.00418674, 0.00466427, 0.009427322,
0.008236453, 0.015339532, 0.012494729, 0.013531303, 0.009839847,
0.011624428, 0.016136746, 0.0138831, 0.014051034, 0.016753211,
0.012780956, 0.01445912, 0.01515584, 0.01883252, 0.014249452,
0.018849478, 0.016863299, 0.015045964, 0.014941168)), .Names = c("Patch",
"Temperature", "CH4rate", "CO2rate"), class = "data.frame", row.names =
c(NA,
-30L))
The plot I get as output is good, however I would like the Variables on the X axis to simply display "Gravel" "Macrophytes" "Marginal" as opposed to each of those variables with Warm and Cold. Thanks for any assistance
THIS IS WHAT I AM TRYING TO ACHEIVE -----> Exact Boxplot I want to create

Following your update with an example graph :
I have also included the formating for the legend position. If you want to edit the y axis label to include subscript I would suggest you read over this. I have included a blank title for relabelling.
test <- structure(list(Patch = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Gravel", "Macrophytes",
"Marginal"), class = "factor"), Temperature = structure(c(2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("Cold",
"Warm"), class = "factor"), CH4rate = c(0.001262595, 0.00138508,
0.001675944, 0.001592354, 0.002169233, 0.001772964, 0.002156633,
0.002864403, 0.002301383, 0.002561042, 0.005189598, 0.004557227,
0.008484851, 0.006867866, 0.007438633, 0.005405327, 0.006381582,
0.008860084, 0.007615417, 0.007705906, 0.009198508, 0.00705233,
0.007943024, 0.008319768, 0.010362114, 0.007822153, 0.010339339,
0.009252302, 0.008249555, 0.008197657), CO2rate = c(0.002274825,
0.002484866, 0.003020209, 0.00289133, 0.003927232, 0.003219346,
0.003922613, 0.005217026, 0.00418674, 0.00466427, 0.009427322,
0.008236453, 0.015339532, 0.012494729, 0.013531303, 0.009839847,
0.011624428, 0.016136746, 0.0138831, 0.014051034, 0.016753211,
0.012780956, 0.01445912, 0.01515584, 0.01883252, 0.014249452,
0.018849478, 0.016863299, 0.015045964, 0.014941168)), .Names = c("Patch",
"Temperature", "CH4rate", "CO2rate"), class = "data.frame", row.names =
c(NA,
-30L))
Now I will create two data sets one for each graph just for simplicity you could leave them combined and facet but for formatting purposes this might be easier.
CH4rate <- test %>%
gather("id", "value", 3:4) %>%
filter(id == "CH4rate")
CO2rate <- test %>%
gather("id", "value", 3:4) %>%
filter(id == "CO2rate")
First plot:
ggplot(CH4rate) +
geom_boxplot(mapping = aes(x = Patch, y = value, fill=factor(Temperature, levels = c("Warm", "Cold")))) +
theme(legend.position = c(0.15, 0.9), panel.background = element_rect(fill = "white", colour = "grey50")) +
labs(title = "Title of graph", x="Patch Type", y = "CH4rate") +
scale_fill_manual(name = "", values = c("orange", "light blue")
, labels = c("Cold" = "Incubated at 10˙C", "Warm" = "Incubated at 26˙C"))
Second plot:
ggplot(CO2rate) +
geom_boxplot(mapping = aes(x = Patch, y = value, fill=factor(Temperature, levels = c("Warm", "Cold")))) +
theme(legend.position = c(0.15, 0.9), panel.background = element_rect(fill = "white", colour = "grey50")) +
labs(title = "Title of graph", x="Patch Type", y = "CO2rate") +
scale_fill_manual(name = "", values = c("orange", "light blue")
, labels = c("Cold" = "Incubated at 10˙C", "Warm" = "Incubated at 26˙C"))

ggplot2: Multiple trend lines in a faceted plot

I'm trying to add two trend lines to the data plotted in my faceted plot for two different depths (Road=color). Geom_smooth works to generate the first plot(pred_new2) with trend line, but as soon as I add facet_wrap - the plot is generated, but without any trend lines/smoothing and without any error.
pred_new$Site <- factor(pred_new$Site,
levels = c("A", "B", "C", "D", "E", "F", "G", "H", "I"))
pred_new2 <- ggplot(pred_new, aes(x = No_cars, y = Site, color = Road)) +
geom_point() +
geom_smooth(aes(x = No_cars, y = Site, color = Road), method = "lm")
pred_new3 <- pred_new2 +
geom_errorbarh(aes(xmin = No_cars - standerror, xmax = No_cars + standerror))
pred_new4 <- pred_new3 +
facet_wrap(~ Days, scales = "free_x") +
ylab("Site") +
xlab("No_cars") +
theme_classic()
pred_new4
Any help would be greatly appreciated.
pred_new = structure(list(Site = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L),
.Label = c("A", "B", "C", "D", "E", "F", "G", "H", "I"),
class = "factor"),
Days = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L),
.Label = c("Thursday", "Tuesday", "Wednesday"),
class = "factor"),
Road = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L),
.Label = c("east", "west"),
class = "factor"),
No_cars = c(15.266427, 8.323348, 8.368608, 9.747807, 7.976356, 8.5684, 6.604537,
3.812109, 6.719904, 4.799487, 4.996091, 4.796, 4.991479, 4.525789,
5.115136, 4.939559, 4.783792, 4.185007, 3.857553, 3.095228, 2.890727,
3.132784, 3.352974, 3.42561, 2.900284, 2.35416, 2.889976, 17.266427,
10.323348, 10.368608, 11.747807, 9.976356, 10.5684, 8.604537, 5.812109,
8.719904, 6.799487, 6.996091, 6.796, 6.991479, 6.525789, 7.115136,
6.939559, 6.783792, 6.185007, 5.857553, 5.095228, 4.890727, 5.132784,
5.352974, 5.42561, 4.900284, 4.35416, 4.889976),
standerror = c(1.7108483, 0.8175014, 0.6365042, 0.7171749, 0.9978123, 0.9881427,
0.9215597, 0.6365042, 1.6303975, 0.404129, 0.1934362, 0.1503158,
0.1694848, 0.2362161, 0.2337497, 0.2180687, 0.1604379, 0.3902528,
0.3276444, 0.1568268, 0.1218673, 0.1374084, 0.1915103, 0.1895107,
0.1767974, 0.1300738, 0.3163943, 1.7108483, 0.8175014, 0.6365042,
0.7171749, 0.9978123, 0.9881427, 0.9215597, 0.6365042, 1.6303975,
0.404129, 0.1934362, 0.1503158, 0.1694848, 0.2362161, 0.2337497,
0.2180687, 0.1604379, 0.3902528, 0.3276444, 0.1568268, 0.1218673,
0.1374084, 0.1915103, 0.1895107, 0.1767974, 0.1300738, 0.3163943)),
row.names = c(NA, -54L), class = "data.frame")

I guess that you swap the axes. To include trend you need numeric values for Site, so I include as.numeric(Site) in ggplot.
library(ggplot2)
ggplot(pred_new, aes(x = as.numeric(Site), y = No_cars, color = Road)) +
geom_point() +
geom_smooth(method = "lm") +
geom_errorbar(aes(ymin = No_cars - standerror, ymax = No_cars + standerror)) +
xlab("Site") +
# this will recode your x-axis
scale_x_continuous(breaks = 1:9, labels = LETTERS[1:9]) +
facet_wrap(~ Days, scales = "free_x") +
theme_classic() +
# you can swap x and y axes with coord_flip()
coord_flip()
Is this desired output?
In case you really want Site on the y-axis, you can simply flip x and y axes:
ggplot(pred_new, aes(y = as.numeric(Site), x = No_cars, color = Road)) +
geom_point() +
geom_smooth(method = "lm") +
geom_errorbarh(aes(xmin = No_cars - standerror, xmax = No_cars + standerror)) +
ylab("Site") +
# this will recode your y-axis
scale_y_continuous(breaks = 1:9, labels = LETTERS[1:9]) +
facet_wrap(~ Days, scales = "free_x") +
theme_classic()

How can I save / generated multiple single graphs from faceted graphs at once?

I have a dataset of >100 different samples. Samples are from different genotypes (e.g. X, Y, Z) and 4 different time points (T0,1,2,3) with 3 biological replicates (R1,2,3). I'm measuring values for 50 different genes (in rows; A,B..)
longdata <- structure(list(Gene = 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), .Label = c("A", "B"), class = "factor"), Genotype = structure(c(1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 3L, 3L, 3L, 3L), .Label = c("X", "Y", "Z"), class = "factor"),
Time = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L,
3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L), .Label = c("T0",
"T1", "T2", "T3"), class = "factor"), Ave = c(1.32606106633333,
1.499956424, 1.118528738, 1.025082136, 0.424537206666667,
0.723243112666667, 0.335509156333333, 0.328275209, 0.788329993666667,
1.125292329, 2.357924224, 0.678921448, 0.222768019, 0.293117217,
0.548228048, 0.841192647333333, 3.144197864, 0.576764958333333,
1.32037215366667, 1.15039119233333, 1.03539976366667, 1.00032109266667,
0.740699933666667, 0.687992671666667), SE = c(0.119785209010494,
0.168580466330281, 0.264739468221289, 0.124588107424543,
0.194995686650518, 0.0392007703821249, 0.06203362889702,
0.0482287534807508, 0.396968455138007, 0.0903480171168777,
0.717823561374135, 0.164024037188693, 0.0078580995264886,
0.0980939303386436, 0.233081861930954, 0.0870744069976396,
0.324195222544884, 0.434640930315622, 0.0658409437053185,
0.135850334794207, 0.175517934316736, 0.123213160632528,
0.133598346586129, 0.203707785326976)), .Names = c("Gene",
"Genotype", "Time", "Ave", "SE"), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -24L))
How can I modify this syntax to generate each graph separately and save them as JPG/PNG files?
longdata %>% ggplot(aes(x = Time, y = Ave, fill = Genotype)) + geom_bar(position = position_dodge(), stat = "identity") + geom_errorbar(aes(ymin = Ave - SE, ymax = Ave + SE), width = 0.1, position = position_dodge(0.9)) + facet_wrap(~ Gene)

You can put ggplot and ggsave within a loop.
lapply(sort(unique(longdata$Gene)), function(i){
ggplot(longdata[longdata$Gene == i, ], aes(x = Time, y = Ave, fill = Genotype)) + geom_bar(position = position_dodge(), stat = "identity") + geom_errorbar(aes(ymin = Ave - SE, ymax = Ave + SE), width = 0.1, position = position_dodge(0.9))
ggsave(filename = paste0(i, ".png"))
})
This loop gets the unique elements of Gene, sorts them, create a plot, then save the result.

Order geom_lines from the highest to the lowest in each facet

I have a factor comp_id that has 4 levels (comp1 to comp4). I want to order each level from the highest to the lowest in a geom_line plot.
I got this plot
using this script
library(data.table)
library(ggplot2)
dat <- as.data.table(df)
dat[, ord := sprintf("%02i", frank(dat, comp_id, -value, ties.method = "first"))]
ggplot(dat, aes(x = ord, y = value , group = comp_id , colour = comp_id))+
geom_line()+
facet_wrap(~comp_id, ncol = 1, scales = "free_x", labeller = label_parsed, drop = TRUE)+
theme(axis.text.x=element_text(angle=35, vjust=1, hjust=1,
))
to replace x axis labels
+scale_x_discrete(labels = dat[, setNames(as.character(predictor), ord)])
As you can see, it worked fine for all levels except comp3 where variables ordered (100 to 105) were plotted at the start of facet where they were supposed to be plotted at the end. I wonder what went wrong. Any suggestions will be appreciated.
DATA
> dput(df)
structure(list(predictor = c("c_C2", "c_C3", "c_C4", "d_D2",
"d_D3", "d_D4", "d_D5", "h_BF", "h_BFI", "h_ER", "h_f", "h_PET",
"h_QuFl", "h_Ra", "l_Da", "l_NaCo", "l_ShBe", "m_a", "m_DrDe",
"m_ElRa", "m_MeElm", "m_MeSlPe", "Mr_Co", "Mr_GRAv", "Mr_GREy",
"Mr_Mu", "Mr_Sa", "s_SaLo", "s_SiLo", "s_sSiLo", "s_Stl", "Sr_Li",
"Sr_SaCoCoTe", "Sr_SaLoSi", "Sr_SaMubcl", "c_C2", "c_C3", "c_C4",
"d_D2", "d_D3", "d_D4", "d_D5", "h_BF", "h_BFI", "h_ER", "h_f",
"h_PET", "h_QuFl", "h_Ra", "l_Da", "l_NaCo", "l_ShBe", "m_a",
"m_DrDe", "m_ElRa", "m_MeElm", "m_MeSlPe", "Mr_Co", "Mr_GRAv",
"Mr_GREy", "Mr_Mu", "Mr_Sa", "s_SaLo", "s_SiLo", "s_sSiLo", "s_Stl",
"Sr_Li", "Sr_SaCoCoTe", "Sr_SaLoSi", "Sr_SaMubcl", "c_C2", "c_C3",
"c_C4", "d_D2", "d_D3", "d_D4", "d_D5", "h_BF", "h_BFI", "h_ER",
"h_f", "h_PET", "h_QuFl", "h_Ra", "l_Da", "l_NaCo", "l_ShBe",
"m_a", "m_DrDe", "m_ElRa", "m_MeElm", "m_MeSlPe", "Mr_Co", "Mr_GRAv",
"Mr_GREy", "Mr_Mu", "Mr_Sa", "s_SaLo", "s_SiLo", "s_sSiLo", "s_Stl",
"Sr_Li", "Sr_SaCoCoTe", "Sr_SaLoSi", "Sr_SaMubcl", "c_C2", "c_C3",
"c_C4", "d_D2", "d_D3", "d_D4", "d_D5", "h_BF", "h_BFI", "h_ER",
"h_f", "h_PET", "h_QuFl", "h_Ra", "l_Da", "l_NaCo", "l_ShBe",
"m_a", "m_DrDe", "m_ElRa", "m_MeElm", "m_MeSlPe", "Mr_Co", "Mr_GRAv",
"Mr_GREy", "Mr_Mu", "Mr_Sa", "s_SaLo", "s_SiLo", "s_sSiLo", "s_Stl",
"Sr_Li", "Sr_SaCoCoTe", "Sr_SaLoSi", "Sr_SaMubcl"), comp_id = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("comp1",
"comp2", "comp3", "comp4"), class = "factor"), value = c(0.0633325075111356,
-0.0193713154441617, 0.000785081075580719, 0.287610195287972,
-0.0913783988809322, -0.122928438782758, 0.305621459875726, 0.0356570047659489,
0.367574915852176, -0.240835821698893, 0.0035597425358522, 0.295952594554233,
-0.0439920206129066, -0.235580426938533, 0.191947159509267, -0.132931615006652,
0.065155805120025, 0.038311284807646, 0.187182963731454, 0.120969596703282,
-0.118935354491654, -0.173851183397175, 0.125870264508295, 0.158977975187947,
-0.209351605852615, -0.0231602829054583, 0.078383405846316, 0.0959455355349004,
0.238306328058919, -0.188667962455942, -0.138302814516594, -0.0586994514783439,
0.019524606432138, 0.210636138928319, -0.204454169255484, -0.149879080476447,
0.282741114373524, -0.272911905666994, 0.102508662574812, -0.35056583225677,
0.257262737814283, 0.202117594283655, 0.191773977367133, 0.298513575892895,
0.139576016330362, 0.165641757285727, -0.071542760140058, 0.116819894570386,
0.145104320521166, 0.126636637925691, 0.0810830011112734, -0.0949935353116725,
0.0785254958291791, 0.0326439188223452, 0.065833153228218, 0.155405435626813,
0.128737420120173, 0.214943178842044, -0.0210359058420932, 0.0117832135586799,
0.0762824228178598, -0.29145271973574, -0.17089908579109, -0.0992003952524557,
0.163749177828358, 0.196561728687348, 0.0951493527111932, 0.17238711709624,
0.0638301486629609, -0.0351097560634362, 0.0647994534663104,
-0.154895398844537, 0.186448424833243, 0.240881706707846, -0.241364320964797,
-0.089459273670017, 0.0491598702691844, -0.200660845431752, -0.0339722426751736,
0.131396251991635, -0.195471026941394, -0.05919918680627, -0.184160478394361,
0.129464190293723, 0.193021703469902, 0.178985522376368, -0.245966624042807,
-0.23478025602535, 0.198620462933836, -0.157573246492692, -0.00808698000885529,
0.0413693509741982, -0.121020524702316, 0.105148862728949, 0.214386790903084,
-0.204515275979768, -0.0906160054540168, -0.276985960928353,
0.0768294557774406, -0.074181085595352, 0.138680723918144, -0.119684214245213,
-0.0919678069134681, 0.322602153170851, 0.228878715511945, -0.433082572929477,
0.05754301130056, 0.130719232236558, 0.253999327778221, 0.0469683234741709,
-0.0258294537417061, -0.258318910865727, -0.00406472629347961,
-0.165003562015847, -0.0292142578447021, 0.00862320222199929,
0.0875367120866572, 0.0331716236283754, -0.0418387105725687,
-0.12523142839593, -0.200857915084298, 0.138378222132672, 0.00992811008724002,
-0.0201043482518474, -0.148894977354092, -0.323240591170999,
-0.0556713655820164, 0.379033571103569, -0.264420286734383, 0.127560649906739,
-0.00546455207923468, -0.203293330594455, -0.122085266718802,
-0.0970860819632599, -0.173818516285048, -0.0585031143296301,
0.125084378608705, 0.0655074180474436, 0.254339734692359, 0.00114212078410835
)), class = "data.frame", .Names = c("predictor", "comp_id",
"value"), row.names = c(NA, -140L))

Here is an approach using tidyverse and continuous scale
library(tidyverse)
df %>%
arrange(comp_id, desc(value)) %>% #arrange by comp_id and descending value
mutate(ord = 1:n()) -> dat #create the x scale
ggplot(dat, aes(x = ord, y = value , group = comp_id , colour = comp_id))+
geom_line()+
facet_wrap(~comp_id, ncol = 1, scales = "free_x", drop = TRUE)+
theme(axis.text.x=element_text(angle=35, vjust=1, hjust=1)) +
scale_x_continuous(labels = dat$predictor, breaks = dat$ord, expand = c(0.02, 0.02))

In addition to the nice answer by #missuse, there was another way that gave me what I wanted.
using as factor / as numeric / as.character with the x axis
aes(x = as.factor(as.numeric(as.character(ord)))
and using as numeric /as character while replacing the x axis labels
as.numeric(as.character(ord))
The final script is
ggplot(dat, aes(x = as.factor(as.numeric(as.character(ord))), y = value , group = comp_id , colour = comp_id))+
geom_line()+
facet_wrap(~comp_id, ncol = 1, scales = "free_x", labeller = label_parsed, drop = TRUE)+
theme(axis.text.x=element_text(angle=35, vjust=1, hjust=1,
))+
scale_x_discrete(labels = dat[, setNames(as.character(predictor), as.numeric(as.character(ord)))])

Increase space between x-axis factors in ggplot

I am using the geom_pointrange function in ggplot2 in order to plot the spread of some measurement over different condition for 5 subjects. In order not to have the subjects overlap I have constructed the plot as follows:
Final = structure(list(Subject = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L), .Label = c("1", "2", "3", "4", "5"), class = "factor"),
X00.conditionName = structure(c(1L, 1L, 2L, 2L, 3L, 3L, 4L,
4L, 1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 1L, 1L, 2L, 2L, 3L, 3L,
4L, 4L, 1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 1L, 1L, 2L, 2L, 3L,
3L, 4L, 4L), .Label = c("EyeClose-Haptic", "mixed-Haptic_Visual",
"only-Haptic", "only-Visual"), class = "factor"), X03.totalTargetNumber = c(2L,
3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L,
2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L,
3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L), Accuracy = c(0.075870763,
0.0907863686, 0.0222156611, 0.0492028585333333, 0.0301178471,
0.0736098328666667, 0.0329723832, 0.0455095300666667, 0.065151615,
0.0979033533333333, 0.0247176775, 0.0335825226666667, 0.027385248,
0.0462643053333333, 0.037272505, 0.0652166726666667, 0.043005086,
0.061848328, 0.031106749, 0.0275656054, 0.026701889, 0.0373967466666667,
0.028998468, 0.03219287, 0.0597213356, 0.0851717708333333,
0.030286913, 0.0779058462666667, 0.043368508, 0.051437624,
0.029002474, 0.0479204566666667, 0.094555739, 0.0856268291666667,
0.031908514, 0.0310441326666667, 0.036311762, 0.0496942306666667,
0.054625148, 0.0482682121666667), upperCI = c(0.116082073022708,
0.139632763787946, 0.0315087794760623, 0.0727058964327625,
0.0468512606854127, 0.116787586356955, 0.0444933233012107,
0.062820743812494, 0.0858551911272202, 0.136013260005381,
0.0327074347874691, 0.0460471773903695, 0.035302995136302,
0.0740077338495226, 0.0641795522210299, 0.131047110446756,
0.0572545979325947, 0.0809511078363974, 0.0414215170576924,
0.0341480438532189, 0.0382253716300962, 0.0519626825555577,
0.0377955915789704, 0.0430125127419472, 0.0903928001427357,
0.114245467448517, 0.0461054194398361, 0.129350863514659,
0.0635159480110737, 0.0717647837071829, 0.0371919026867606,
0.0615899295823839, 0.170222051412597, 0.128502458351433,
0.046712862081242, 0.0388340720489338, 0.0574188259607336,
0.0786845830951613, 0.0844193698576058, 0.0784830058409822
), lowerCI = c(0.0356594529772922, 0.0419399734120541, 0.0129225427239377,
0.0256998206339042, 0.0133844335145873, 0.0304320793763786,
0.0214514430987893, 0.0281983163208393, 0.0444480388727798,
0.059793446661286, 0.0167279202125309, 0.0211178679429639,
0.019467500863698, 0.0185208768171441, 0.0103654577789701,
-0.000613765113422152, 0.0287555740674053, 0.0427455481636026,
0.0207919809423076, 0.0209831669467811, 0.0151784063699038,
0.0228308107777757, 0.0202013444210296, 0.0213732272580528,
0.0290498710572643, 0.0560980742181497, 0.0144684065601638,
0.0264608290186746, 0.0232210679889263, 0.0311104642928171,
0.0208130453132394, 0.0342509837509495, 0.018889426587403,
0.0427511999819006, 0.017104165918758, 0.0232541932843995,
0.0152046980392664, 0.0207038782381721, 0.0248309261423941,
0.0180534184923511), CondLevel = c("EyeClose-Haptic2", "EyeClose-Haptic3",
"mixed-Haptic_Visual2", "mixed-Haptic_Visual3", "only-Haptic2",
"only-Haptic3", "only-Visual2", "only-Visual3", "EyeClose-Haptic2",
"EyeClose-Haptic3", "mixed-Haptic_Visual2", "mixed-Haptic_Visual3",
"only-Haptic2", "only-Haptic3", "only-Visual2", "only-Visual3",
"EyeClose-Haptic2", "EyeClose-Haptic3", "mixed-Haptic_Visual2",
"mixed-Haptic_Visual3", "only-Haptic2", "only-Haptic3", "only-Visual2",
"only-Visual3", "EyeClose-Haptic2", "EyeClose-Haptic3", "mixed-Haptic_Visual2",
"mixed-Haptic_Visual3", "only-Haptic2", "only-Haptic3", "only-Visual2",
"only-Visual3", "EyeClose-Haptic2", "EyeClose-Haptic3", "mixed-Haptic_Visual2",
"mixed-Haptic_Visual3", "only-Haptic2", "only-Haptic3", "only-Visual2",
"only-Visual3")), .Names = c("Subject", "X00.conditionName",
"X03.totalTargetNumber", "Accuracy", "upperCI", "lowerCI", "CondLevel"
), row.names = c(NA, -40L), class = "data.frame")
require(ggplot2)
pdf("Pilot2.pdf", w = 12, h = 8)
limits <- aes(ymax = upperCI, ymin=lowerCI)
BaseLayer = ggplot(data = Final, aes (x = X00.conditionName, y = Accuracy, color = Subject, group = Subject ))
BaseLayer + geom_pointrange(limits, position=position_dodge(width=1), size = 1.5) +
theme(axis.text=element_text(size=14), axis.title=element_text(size=14), axis.text.x = element_text(angle = 25, hjust = 1)) +
facet_grid (.~X03.totalTargetNumber) + ggtitle ("Pilot 2") + xlab ("Condition")
dev.off()
As you can see the x-axis is discrete, and the points are very "crowded", so that it is difficult to tell apart the different categories.
Is there a way to increase the space between the different categories ?

The best solutoin is to use facets to create 8 separate tall and skinny plots with all these features that are separated by a thin white gutter between them with a solid label at the top. You could keep or lose X-axis labels. It creates one figure of 8 graphs that communicates better than on big graph.
Like this:Stack-ggplot2-geom-pointrange-facet-grid-with-coord-flip
except yours would be verticle

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