How can I plot Facets in R using my data?

How can I plot Facets in R using my data? - r

I have the following data for a US state
d <- structure(list(Month = structure(c(5L, 4L, 9L, 1L, 8L, 7L, 6L,
2L, 12L, 11L, 10L, 3L), .Label = c("01-Abr-14", "01-Ago-14",
"01-Dez-14", "01-Fev-14", "01-Jan-14", "01-Jul-14", "01-Jun-14",
"01-Mai-14", "01-Mar-14", "01-Nov-14", "01-Out-14", "01-Set-14"
), class = "factor"), Ada = c(0.1, 0.14, 0.25, -0.06, -0.15,
0.3, 0.02, -0.01, 0.37, 0.08, 0.15, 0.17), Altus = c(0.06, 0.05,
0.1, -0.17, -0.02, 0.25, -0.02, 0.08, 0, 0.02, 0.02, 0.02), Antlers = c(-0.08,
0.02, 0.1, -0.38, -0.3, 0.27, -0.17, -0.1, 0.11, 0.11, 0.14,
0), Ardmore = c(-0.01, 0.09, 0.18, -0.24, 0.02, 0.21, -0.13,
-0.06, 0.18, 0.01, -0.02, 0.08), Bartlesville = c(-0.02, 0.09,
0.2, 0.16, -0.07, 0.08, 0.01, 0.04, -0.01, 0.11, 0.11, 0.15),
Beaver = c(0.01, -0.02, 0.16, -0.08, -0.04, 0.07, 0.07, 0.07,
-0.12, 0.05, 0, 0.05), Boise.City = c(0.02, -0.05, 0.09,
-0.1, -0.24, 0.05, -0.01, 0.21, -0.01, -0.06, 0, 0.03), Buffalo = c(-0.04,
0, 0.15, -0.05, -0.15, 0.16, -0.11, 0.12, -0.2, 0.03, 0,
0.01), Carnegie = c(0.02, 0.06, 0.15, -0.16, 0.09, 0.24,
-0.03, 0.09, -0.16, 0.06, -0.01, 0), Cherokee = c(0.06, 0.1,
0.26, -0.1, -0.06, 0.2, 0.06, -0.06, -0.06, -0.11, 0, 0.08
), Claremore = c(-0.02, 0.22, 0.18, 0.12, -0.09, 0.11, 0.16,
0.04, 0.46, 0.16, 0.25, 0.17), Durant = c(0.06, 0.05, 0.15,
-0.11, -0.12, 0.35, -0.21, 0, 0.4, 0.04, 0.26, 0.09), Enid = c(0.07,
0.08, 0.34, 0, 0.18, 0.34, 0.11, 0.09, -0.04, 0.17, 0.13,
0.1), Erick = c(0.05, 0.06, 0.14, -0.15, -0.09, 0.07, -0.05,
0.13, 0.01, -0.02, 0.04, 0.02), Geary = c(-0.01, 0.01, 0.15,
-0.19, -0.09, 0.14, -0.18, 0.14, 0.02, 0.05, -0.07, 0), Goodwell = c(0,
-0.05, 0.08, -0.08, -0.01, 0, -0.06, 0.03, -0.12, 0.02, -0.03,
0), Guthrie = c(0.06, 0.13, 0.23, -0.09, 0.06, 0.31, -0.03,
0.05, -0.01, 0.03, 0.09, 0.11), Hammon = c(0.02, 0.03, 0.14,
-0.2, -0.04, 0.1, -0.1, 0.23, -0.07, 0.05, 0.03, 0.03), Hennessey = c(0.02,
0.09, 0.22, -0.04, 0.1, 0.22, 0.13, 0.2, 0.08, -0.01, 0.03,
0.07), Hobartmuni = c(-0.03, -0.02, 0.1, -0.17, -0.29, -0.08,
0.02, 0.04, -0.05, -0.03, 0, 0), Holdenville = c(-0.04, 0.12,
0.26, 0.05, -0.16, 0.23, 0.04, 0.01, 0.27, 0.13, 0.12, 0.07
), Hooker = c(0.03, -0.03, 0.07, -0.08, -0.17, 0.01, -0.03,
-0.05, -0.14, -0.02, 0, 0.04), Jefferson = c(0.04, 0.05,
0.29, 0.09, 0.05, 0.21, 0.11, 0.07, -0.03, 0.05, 0.09, 0.08
), Kenton = c(0.02, -0.06, 0.05, -0.12, -0.15, 0, 0.27, 0.17,
-0.01, -0.04, -0.02, -0.01), Kingfisher = c(0.05, 0.09, 0.18,
-0.02, 0.19, 0.21, -0.03, 0.19, 0.1, -0.01, 0.02, 0.11),
Lawton = c(0.03, 0.06, 0.06, -0.17, -0.39, 0.11, -0.1, 0.06,
0, 0.06, 0.03, 0.03), Mangum = c(0.01, 0, 0.05, -0.31, -0.27,
0.13, 0.01, -0.01, -0.01, 0, 0, 0.01), Meeker = c(-0.03,
0.14, 0.22, -0.15, -0.03, 0.34, 0.05, -0.03, 0.22, 0.14,
0.02, 0.06), Miami = c(-0.03, 0.03, 0.17, 0.12, 0.15, -0.11,
-0.15, -0.29, 0.34, 0.11, 0.25, 0.09), Muskogee = c(0.08,
0.12, 0.14, -0.04, 0.27, 0.16, -0.09, -0.07, 0.36, -0.02,
0.23, 0.14), Mutual = c(0.04, 0.05, 0.16, -0.05, 0.2, 0.16,
0.06, -0.04, -0.1, 0.02, 0, 0.08), Newkirk = c(-0.04, 0.06,
0.19, 0.13, -0.09, 0.15, 0.24, -0.01, -0.1, 0.21, 0, 0.1),
Okeene = c(0.09, 0.19, 0.12, 0.06, 0.02, 0.41, 0.03, 0.03,
0.37, 0.08, 0.13, 0.17), Okemah = c(0, 0.04, 0.2, -0.08,
0.04, 0.12, 0.05, 0.04, -0.01, 0.1, 0, 0.06), Okmulgee = c(0.04,
0.21, 0.17, -0.02, 0.01, 0.23, 0.03, 0.06, 0.17, 0, 0.29,
0.1), Pauls_valley = c(0.17, 0.17, 0.36, -0.02, -0.11, 0.27,
-0.12, 0.06, 0.27, 0.22, 0.13, 0.21), Pawhuska = c(0.05,
0.11, 0.3, 0.29, 0.19, 0.13, 0.2, -0.02, 0.1, 0.12, 0.2,
0.15), Perry = c(0.04, 0.13, 0.25, -0.15, -0.06, 0.02, 0.2,
-0.15, -0.05, 0, -0.04, 0.07), Poteau = c(-0.03, 0.05, 0.21,
-0.11, -0.01, -0.07, -0.11, -0.15, 0.37, 0.39, 0.25, 0.2),
Stillwater = c(0.04, 0.12, 0.16, -0.2, -0.04, 0.2, 0.1, -0.01,
0.02, 0, 0, 0.05), Tahlequah = c(0.09, 0.17, 0.27, -0.02,
0.48, 0.06, 0.28, 0.05, 0.38, 0.11, 0.4, 0.21), Waurika = c(0.07,
0.04, 0.16, -0.09, -0.12, 0.08, -0.22, -0.01, 0.09, 0.09,
-0.03, 0.02), Weatherford = c(0.03, 0.05, 0.23, -0.24, -0.06,
0.25, -0.11, 0.3, -0.1, 0.04, -0.03, 0.01), Webbersfalls = c(-0.04,
0.1, 0.16, -0.09, 0.09, -0.01, -0.25, -0.18, 0.39, 0.01,
0.3, 0.11)), .Names = c("Month", "Ada", "Altus", "Antlers",
"Ardmore", "Bartlesville", "Beaver", "Boise.City", "Buffalo",
"Carnegie", "Cherokee", "Claremore", "Durant", "Enid", "Erick",
"Geary", "Goodwell", "Guthrie", "Hammon", "Hennessey", "Hobartmuni",
"Holdenville", "Hooker", "Jefferson", "Kenton", "Kingfisher",
"Lawton", "Mangum", "Meeker", "Miami", "Muskogee", "Mutual",
"Newkirk", "Okeene", "Okemah", "Okmulgee", "Pauls_valley", "Pawhuska",
"Perry", "Poteau", "Stillwater", "Tahlequah", "Waurika", "Weatherford",
"Webbersfalls"), class = "data.frame", row.names = c(NA, -12L
))
coordinates for each place to map
coords <- structure(list(place = structure(c(2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L,
35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 1L, 44L), .Label = c(" Weatherford",
"Ada", "Altus", "Antlers", "Ardmore", "Bartlesville", "Beaver",
"Boise City", "Buffalo", "Carnegie", "Cherokee", "Claremore",
"Durant", "Enid", "Erick", "Geary", "Goodwell", "Guthrie", "Hammon",
"Hennessey", "Hobartmuni", "Holdenville", "Hooker", "Jefferson",
"Kenton", "Kingfisher", "Lawton", "Mangum", "Meeker", "Miami",
"Muskogee", "Mutual", "Newkirk", "Okeene", "Okemah", "Okmulgee",
"Pauls_valley", "Pawhuska", "Perry", "Poteau", "Stillwater",
"Tahlequah", "Waurika", "Webbersfalls"), class = "factor"), Lat = c(34.7864,
34.5903, 34.2208, 34.1714, 36.7683, 36.8125, 36.7236, 36.8003,
35.1756, 36.7747, 36.3225, 34.0003, 36.4194, 35.2164, 35.6267,
36.5914, 35.8161, 35.585, 36.0942, 34.9894, 35.0567, 36.8589,
36.7222, 36.9031, 35.8583, 34.6097, 34.8911, 35.505, 36.8833,
35.7781, 36.2283, 36.8914, 36.1217, 35.4253, 35.6239, 34.7253,
36.6692, 36.2886, 35.0539, 36.1175, 35.9369, 34.1747, 35.52,
35.4814), Long = c(-96.685, -99.3344, -95.615, -97.1294, -96.0261,
-100.5308, -102.4806, -99.6403, -98.5794, -98.3583, -95.5808,
-96.3686, -97.8747, -99.8628, -98.3225, -101.6181, -97.395, -99.3953,
-97.835, -99.0525, -96.3861, -101.2172, -97.7903, -102.965, -97.9294,
-98.4572, -99.5017, -96.9767, -94.8833, -95.3339, -99.17, -97.0586,
-98.315, -96.3033, -96.025, -97.2814, -96.3472, -97.2897, -94.6264,
-97.095, -94.9644, -97.9964, -98.6986, -95.2039)), .Names = c("place",
"Lat", "Long"), class = "data.frame", row.names = c(NA, -44L))
So basically I want to take the values, find out which one is positive and which one is negative and plot a figure like below.
There will be three different tickers for +,- and zero
12 facets for 12 months
I have the lat/longs for the 44 places, so I can plot them on the state map.
How can I do this using ggplot2? or some other utility.
Till now, I have plotted the points using the following code
ggplot() +
geom_polygon(data=m, aes(x=long, y=lat,group=group),colour="black", fill="white" )+
geom_point(data=stations,aes(x=long,y=lat),,colour="red",)+
size=0.5,hjust=0,alpha=.5),size=3)+
xlab('Longitude')+
ylab('Latitude')+
coord_fixed()

Try this
Load lackages, download when necessary
kpacks <- c('raster', 'ggplot2', 'reshape2', 'lubridate')
new.packs <- kpacks[!(kpacks %in% installed.packages()[,"Package"])]
if(length(new.packs)) install.packages(new.packs)
lapply(kpacks, require, character.only=T)
remove(kpacks, new.packs)
d <- read.table(text=readClipboard(), sep = '\t', header=TRUE)
# or copy and paste the data from above
coords <- read.table(text=readClipboard(), sep = '\t', header=TRUE, quote = '')
# or copy and paste the data from above
#coordinates(coords) <- ~Long+Lat #not necessary for this approach
Get data from GADM
usa <- raster::getData(country = 'USA', level = 1)
okl <- usa[usa#data$NAME_1 == 'Oklahoma', ]
#plot(okl)
#plot(coords, add = T, cols = d)
d1 <- melt(d) # reshape it
d1$Month <- lubridate::dmy(d1$Month) # I've used abrev names in Portuguese. Change accordingly
create a factor variable with levels = positive/zero/negative
d1$val <- cut(d1$value, breaks= c(min(d1$value), 0.00, 0.001, max(d1$value)),
labels = c('negative', 'zero', 'positive'),
right = F, include.lowest = T, dig.lab = 3)
d2 <- merge(d1, coords, by.x = 'variable', by.y = 'place', all.x = T)
head(d2)
variable Month value val Lat Long
1 Ada Jul 0.02 positive 34.7864 -96.685
2 Ada May -0.15 negative 34.7864 -96.685
3 Ada Jun 0.30 positive 34.7864 -96.685
4 Ada Jan 0.10 positive 34.7864 -96.685
5 Ada Feb 0.14 positive 34.7864 -96.685
6 Ada Mar 0.25 positive 34.7864 -96.685
okl_df <- fortify(okl) # spdf to data.frame
head(okl_df)
long lat order hole piece group id
1 -95.52363 37.00093 1 FALSE 1 36.1 36
2 -95.40672 37.00047 2 FALSE 1 36.1 36
3 -95.40027 37.00053 3 FALSE 1 36.1 36
4 -95.07227 36.99872 4 FALSE 1 36.1 36
5 -95.03362 36.99859 5 FALSE 1 36.1 36
6 -95.03309 36.99920 6 FALSE 1 36.1 36
p <- ggplot(data = okl_df, aes(x = long, y = lat, group = group)) +
geom_polygon(fill = NA, colour = 'black') +
geom_point(inherit.aes = F, data = d2, aes(x=Long, y = Lat, colour = val)) +
facet_wrap(~ Month, ncol = 3) +
theme_minimal() +
coord_map()+
scale_colour_manual('class', values = c('negative'= 'grey80', 'zero' = 'grey60',
'positive' = 'black'))
p
EDIT
For mapping the variable to shapes instead of colours one can map it to aesthetics
p1 <- ggplot(data = okl_df, aes(x = long, y = lat, group = group)) +
geom_polygon(fill = NA, colour = 'black') +
geom_point(inherit.aes = F, data = d2, aes(x=Long, y = Lat, shape = val)) +
facet_wrap(~ Month, ncol = 3) +
theme_minimal() +
coord_map()
p1
Or map both colour and shape to aesthetics
p2 <- ggplot(data = okl_df, aes(x = long, y = lat, group = group)) +
geom_polygon(fill = NA, colour = 'black') +
geom_point(inherit.aes = F, data = d2, aes(x=Long, y = Lat, colour = val,
shape = val)) +
facet_wrap(~ Month, ncol = 3) +
theme_minimal() +
coord_map()
p2
You can export it as png, manipulating resolution was needed
ggsave(file = file.path(tempdir(),'map1.png'),
p
, width=16, height=16, units = "cm", dpi = 150
)

Add facet_wrap(~ month) or facet_grid(month ~ .) at the end of your plotting code. You can also specify the number of columns in facet_wrap: facet_wrap(~ month, ncol = 3)
I've rearranged your data:
transposed the data
named the first column place
The resulting dataframe:
oklahoma <- structure(list(place = structure(1:44, .Label = c("Ada", "Altus", "Antlers", "Ardmore", "Bartlesville", "Beaver", "Boise City", "Buffalo", "Carnegie", "Cherokee", "Claremore", "Durant", "Enid", "Erick", "Geary", "Goodwell", "Guthrie", "Hammon", "Hennessey", "Hobartmuni", "Holdenville", "Hooker", "Jefferson", "Kenton", "Kingfisher", "Lawton", "Mangum", "Meeker", "Miami", "Muskogee", "Mutual", "Newkirk", "Okeene", "Okemah", "Okmulgee", "Pauls valley", "Pawhuska", "Perry", "Poteau", "Stillwater", "Tahlequah", "Waurika", "Weatherford", "Webbersfalls"), class = "factor"), Jan = structure(c(16L, 12L, 5L, 1L, 2L, 7L, 8L, 4L, 8L, 12L, 2L, 12L, 16L, 11L, 1L, 6L, 12L, 8L, 8L, 3L, 4L, 9L, 10L, 8L, 11L, 9L, 7L, 3L, 3L, 14L, 10L, 4L, 15L, 6L, 10L, 17L, 11L, 10L, 3L, 10L, 15L, 13L, 9L, 4L), .Label = c("-0,01", "-0,02", "-0,03", "-0,04", "-0,08", "0", "0,01", "0,02", "0,03", "0,04", "0,05", "0,06", "0,07", "0,08", "0,09", "0,1", "0,17"), class = "factor"), Feb = structure(c(17L, 10L, 7L, 12L, 12L, 1L, 3L, 5L, 11L, 13L, 21L, 10L, 13L, 11L, 6L, 3L, 16L, 8L, 12L, 1L, 15L, 2L, 10L, 4L, 12L, 11L, 5L, 17L, 8L, 15L, 10L, 11L, 19L, 9L, 20L, 18L, 14L, 16L, 10L, 15L, 18L, 9L, 10L, 13L), .Label = c("-0,02", "-0,03", "-0,05", "-0,06", "0", "0,01", "0,02", "0,03", "0,04", "0,05", "0,06", "0,09", "0,1", "0,11", "0,12", "0,13", "0,14", "0,17", "0,19", "0,21", "0,22"), class = "factor"), Mar = structure(c(18L, 6L, 6L, 12L, 14L, 10L, 5L, 9L, 9L, 19L, 12L, 9L, 22L, 8L, 9L, 4L, 17L, 8L, 16L, 6L, 19L, 3L, 21L, 1L, 12L, 2L, 1L, 16L, 11L, 8L, 10L, 13L, 7L, 14L, 11L, 23L, 22L, 18L, 15L, 10L, 20L, 10L, 17L, 10L), .Label = c("0,05", "0,06", "0,07", "0,08", "0,09", "0,1", "0,12", "0,14", "0,15", "0,16", "0,17", "0,18", "0,19", "0,2", "0,21", "0,22", "0,23", "0,25", "0,26", "0,27", "0,29", "0,3", "0,36"), class = "factor"), Apr = structure(c(4L, 14L, 17L, 15L, 24L, 5L, 7L, 3L, 11L, 7L, 22L, 8L, 18L, 14L, 13L, 5L, 6L, 14L, 2L, 12L, 19L, 5L, 21L, 9L, 1L, 12L, 16L, 10L, 22L, 2L, 3L, 23L, 20L, 5L, 1L, 1L, 25L, 14L, 8L, 14L, 1L, 6L, 15L, 6L), .Label = c("-0,02", "-0,04", "-0,05", "-0,06", "-0,08", "-0,09", "-0,1", "-0,11", "-0,12", "-0,15", "-0,16", "-0,17", "-0,19", "-0,2", "-0,24", "-0,31", "-0,38", "0", "0,05", "0,06", "0,09", "0,12", "0,13", "0,16", "0,29"), class = "factor"), May = structure(c(10L, 18L, 16L, 20L, 5L, 3L, 13L, 10L, 24L, 4L, 6L, 9L, 28L, 7L, 6L, 1L, 23L, 3L, 25L, 15L, 11L, 12L, 22L, 10L, 27L, 17L, 14L, 2L, 26L, 29L, 28L, 6L, 20L, 21L, 19L, 8L, 27L, 7L, 1L, 3L, 30L, 9L, 4L, 24L), .Label = c("-0,01", "-0,03", "-0,04", "-0,06", "-0,07", "-0,09", "-0,1", "-0,11", "-0,12", "-0,15", "-0,16", "-0,17", "-0,24", "-0,27", "-0,29", "-0,3", "-0,39", "0", "0,01", "0,02", "0,04", "0,05", "0,06", "0,09", "0,1", "0,15", "0,19", "0,2", "0,27", "0,48"), class = "factor"), Jun = structure(c(26L, 24L, 25L, 20L, 11L, 10L, 8L, 18L, 23L, 19L, 13L, 29L, 26L, 10L, 16L, 5L, 27L, 12L, 21L, 3L, 22L, 6L, 20L, 5L, 20L, 13L, 15L, 28L, 4L, 18L, 18L, 17L, 30L, 14L, 22L, 25L, 15L, 7L, 2L, 19L, 9L, 11L, 24L, 1L), .Label = c("-0,01", "-0,07", "-0,08", "-0,11", "0", "0,01", "0,02", "0,05", "0,06", "0,07", "0,08", "0,1", "0,11", "0,12", "0,13", "0,14", "0,15", "0,16", "0,2", "0,21", "0,22", "0,23", "0,24", "0,25", "0,27", "0,3", "0,31", "0,34", "0,35", "0,41"), class = "factor"), Jul = structure(c(17L, 15L, 10L, 8L, 16L, 22L, 1L, 6L, 2L, 21L, 26L, 12L, 23L, 5L, 11L, 3L, 2L, 5L, 25L, 17L, 19L, 2L, 24L, 29L, 2L, 5L, 16L, 20L, 9L, 4L, 21L, 28L, 18L, 20L, 18L, 7L, 27L, 27L, 6L, 23L, 30L, 13L, 6L, 14L), .Label = c("-0,01", "-0,03", "-0,06", "-0,09", "-0,1", "-0,11", "-0,12", "-0,13", "-0,15", "-0,17", "-0,18", "-0,21", "-0,22", "-0,25", "0", "0,01", "0,02", "0,03", "0,04", "0,05", "0,06", "0,07", "0,1", "0,11", "0,13", "0,16", "0,2", "0,24", "0,27", "0,28"), class = "factor"), Aug = structure(c(1L, 20L, 8L, 6L, 16L, 19L, 29L, 23L, 21L, 6L, 16L, 13L, 22L, 24L, 25L, 15L, 17L, 30L, 28L, 16L, 14L, 5L, 19L, 26L, 27L, 18L, 1L, 3L, 12L, 7L, 4L, 1L, 15L, 16L, 18L, 18L, 2L, 11L, 9L, 1L, 17L, 1L, 31L, 10L), .Label = c("-0,01", "-0,02", "-0,03", "-0,04", "-0,05", "-0,06", "-0,07", "-0,1", "-0,15", "-0,18", "-0,2", "-0,29", "0", "0,01", "0,03", "0,04", "0,05", "0,06", "0,07", "0,08", "0,09", "0,1", "0,12", "0,13", "0,14", "0,17", "0,19", "0,2", "0,21", "0,23", "0,3"), class = "factor"), Sep = structure(c(24L, 11L, 17L, 19L, 1L, 7L, 1L, 10L, 9L, 4L, 28L, 27L, 11L, 12L, 13L, 7L, 1L, 5L, 14L, 3L, 21L, 8L, 2L, 1L, 16L, 11L, 1L, 20L, 22L, 23L, 6L, 6L, 24L, 1L, 18L, 21L, 16L, 6L, 24L, 13L, 25L, 15L, 6L, 26L), .Label = c("-0,01", "-0,03", "-0,05", "-0,06", "-0,07", "-0,1", "-0,12", "-0,14", "-0,16", "-0,2", "0", "0,01", "0,02", "0,08", "0,09", "0,1", "0,11", "0,17", "0,18", "0,22", "0,27", "0,34", "0,36", "0,37", "0,38", "0,39", "0,4", "0,46"), class = "factor"), Oct = structure(c(14L, 9L, 17L, 8L, 17L, 12L, 5L, 10L, 13L, 6L, 21L, 11L, 22L, 7L, 12L, 9L, 10L, 12L, 1L, 3L, 19L, 2L, 12L, 4L, 1L, 13L, 7L, 20L, 17L, 2L, 9L, 23L, 14L, 16L, 7L, 24L, 18L, 7L, 25L, 7L, 17L, 15L, 11L, 8L), .Label = c("-0,01", "-0,02", "-0,03", "-0,04", "-0,06", "-0,11", "0", "0,01", "0,02", "0,03", "0,04", "0,05", "0,06", "0,08", "0,09", "0,1", "0,11", "0,12", "0,13", "0,14", "0,16", "0,2", "0,21", "0,22", "0,39"), class = "factor"), Nov = structure(c(15L, 6L, 14L, 2L, 11L, 5L, 5L, 5L, 1L, 5L, 18L, 19L, 10L, 8L, 4L, 3L, 9L, 7L, 7L, 5L, 12L, 5L, 9L, 2L, 6L, 7L, 5L, 6L, 18L, 17L, 5L, 5L, 13L, 5L, 20L, 13L, 16L, 5L, 18L, 5L, 22L, 3L, 3L, 21L), .Label = c("-0,01", "-0,02", "-0,03", "-0,07", "0", "0,02", "0,03", "0,04", "0,09", "0,1", "0,11", "0,12", "0,13", "0,14", "0,15", "0,2", "0,23", "0,25", "0,26", "0,29", "0,3", "0,4"), class = "factor"), Dec = structure(c(16L, 4L, 2L, 10L, 15L, 7L, 5L, 3L, 2L, 10L, 16L, 11L, 12L, 4L, 2L, 2L, 13L, 5L, 9L, 2L, 9L, 6L, 10L, 1L, 13L, 5L, 3L, 8L, 11L, 14L, 10L, 12L, 16L, 8L, 12L, 18L, 15L, 9L, 17L, 7L, 18L, 4L, 3L, 13L), .Label = c("-0,01", "0", "0,01", "0,02", "0,03", "0,04", "0,05", "0,06", "0,07", "0,08", "0,09", "0,1", "0,11", "0,14", "0,15", "0,17", "0,2", "0,21"), class = "factor"), Lat = structure(c(8L, 5L, 4L, 2L, 37L, 40L, 36L, 39L, 13L, 38L, 32L, 1L, 26L, 14L, 21L, 33L, 23L, 19L, 27L, 10L, 12L, 41L, 35L, 44L, 24L, 6L, 9L, 17L, 42L, 22L, 30L, 43L, 29L, 15L, 20L, 7L, 34L, 31L, 11L, 28L, 25L, 3L, 18L, 16L), .Label = c("34", "34,1714", "34,1747", "34,221", "34,6", "34,61", "34,7253", "34,786", "34,8911", "34,9894", "35,054", "35,0567", "35,1756", "35,2", "35,4253", "35,4814", "35,505", "35,52", "35,585", "35,6239", "35,63", "35,7781", "35,816", "35,8583", "35,9369", "36", "36,0942", "36,1175", "36,122", "36,228", "36,3", "36,3225", "36,5914", "36,6692", "36,7222", "36,7236", "36,7683", "36,7747", "36,8", "36,813", "36,859", "36,88", "36,8914", "36,903"), class = "factor"), Long = structure(c(20L, 39L, 13L, 25L, 15L, 2L, 5L, 44L, 37L, 35L, 12L, 18L, 32L, 1L, 33L, 4L, 27L, 42L, 29L, 40L, 19L, 3L, 28L, 6L, 30L, 36L, 43L, 21L, 8L, 11L, 41L, 23L, 34L, 16L, 14L, 26L, 17L, 22L, 7L, 24L, 9L, 31L, 38L, 10L), .Label = c("-100", "-100,5", "-101,2", "-101,618", "-102,481", "-103", "-94,63", "-94,9", "-94,9644", "-95,2039", "-95,3339", "-95,5808", "-95,62", "-96,025", "-96,0261", "-96,303", "-96,3472", "-96,37", "-96,3861", "-96,69", "-96,98", "-97", "-97,059", "-97,095", "-97,129", "-97,2814", "-97,4", "-97,7903", "-97,835", "-97,9294", "-97,996", "-98", "-98,3", "-98,32", "-98,3583", "-98,46", "-98,579", "-98,6986", "-99", "-99,0525", "-99,17", "-99,3953", "-99,502", "-99,64"), class = "factor")), .Names = c("place", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec", "Lat", "Long"), class = "data.frame", row.names = c(NA, -44L))
After that reshape the dataframe:
require(reshape2)
stations <- melt(oklahoma, id=c("place","Lat","Long"))
stations$value <- gsub(',', '.', stations$value)
stations$value <- as.numeric(stations$value)
The create the plot:
ggplot() +
# geom_polygon(data=m, aes(x=Long, y=Lat,group=group), colour="black", fill="white") +
geom_point(data=stations, aes(x=Long,y=Lat), colour="red")+
xlab('Longitude') +
ylab('Latitude') +
coord_fixed() +
facet_wrap(~ variable, ncol = 3)
As you can see, I commented out the geom_polygon as I don't have that data.

Related

Aesthethics do not work for individual geom_line's in R's ggplot

I am trying to construct a plot with thin, transparent individual lines for individual people (indicated by the id column) and place a thick, solid average-across-people line on top of that.
My ggplot call looks like this:
ggplot(data, aes(x = card_self, y = percent)) +
geom_line(aes(group=id, color=id, size=1, alpha=0.8)) +
geom_line(data = data_averaged, aes(size=10, alpha=0.9)) +
guides(color='none', alpha='none', size='none')
The result is this:
The problem is that changing the size/alpha aesthetics does not work as expected. I've tried setting them outside the aes argument and inside and the results are as random as it gets.
My full code to reproduce the plot is here:
library("tidyverse")
library("ggplot")
data <- structure(list(id = 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,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L,
18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L,
23L, 23L, 23L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L,
24L, 24L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L,
27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 28L,
28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 29L, 29L,
29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L), .Label = c("P001",
"P002", "P003", "P004", "P005", "P006", "P007", "P008", "P009",
"P010", "P011", "P012", "P013", "P014", "P015", "P016", "P017",
"P018", "P019", "P020", "P021", "P022", "P023", "P024", "P025",
"P026", "P027", "P028", "P029", "P030"), class = "factor"), card_self = structure(c(1L,
2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L,
5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L,
9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L,
11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L,
13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L,
2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L,
5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L,
9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L,
11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L,
13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L,
2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L,
5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L,
9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L,
11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L,
13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L,
2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L,
5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L,
9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L,
11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L,
13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L,
2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L,
5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L,
9L, 10L, 11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L,
11L, 12L, 13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L,
13L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L, 11L, 12L, 13L), .Label = c("ace",
"two", "three", "four", "five", "six", "seven", "eight", "nine",
"ten", "jack", "queen", "king"), class = "factor"), percent = c(1,
1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0.89, 1, 0.67, 0, 0,
0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
0.67, 0.22, 0.11, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0.89, 0, 0, 0,
0, 0, 1, 1, 0.89, 1, 1, 0.89, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0.89,
0.56, 0, 0.22, 0, 0, 0, 0, 0.56, 0.89, 0.67, 0.89, 0.67, 0.89,
0.56, 0.67, 0.44, 0.89, 0.56, 0.56, 1, 1, 1, 1, 0.44, 0.56, 0.11,
0.22, 0.22, 0, 0, 0, 1, 1, 1, 1, 0.44, 0.33, 0.67, 0.33, 0.11,
0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0.89, 1, 0.89,
0.78, 0.22, 0.56, 0.33, 0.22, 0.11, 0, 1, 1, 1, 1, 0.44, 0.11,
0, 0, 0, 0, 0, 0, 1, 0.78, 0.89, 0.56, 0.67, 0.67, 0.44, 0.44,
0.44, 0.67, 0.22, 0, 1, 1, 1, 1, 1, 0.78, 0.44, 0, 0.78, 0.44,
0, 0, 1, 1, 1, 1, 1, 1, 0.11, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1,
0, 0.22, 0, 0, 0, 0, 0.67, 0.44, 0.33, 0.56, 0.11, 0.33, 0.44,
0.56, 0.44, 0.33, 0.22, 0.33, 1, 1, 1, 1, 1, 1, 0.11, 0.11, 0.11,
0, 0, 0, 1, 1, 1, 1, 1, 0.67, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
0.44, 0, 0.33, 0.22, 0, 0, 0, 1, 0.56, 0.67, 0.89, 0.89, 0.78,
0.67, 0.44, 0.33, 0, 0.33, 0, 1, 1, 0.89, 0.78, 0.67, 0.44, 0.33,
0, 0.22, 0, 0, 0, 1, 1, 1, 1, 1, 0.78, 0, 0, 0, 0, 0, 0, 1, 1,
1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0.67, 0.44, 0.56, 0.22, 0.33, 0.44,
0.56, 0.56, 0.22, 0.44, 0.44, 0.33, 1, 1, 1, 1, 1, 1, 0.56, 0.11,
0, 0, 0, 0, 1, 1, 1, 1, 0.44, 0.44, 0.33, 0, 0, 0, 0, 0, 1, 1,
0.89, 0.67, 0.33, 0.33, 0.56, 0.22, 0.11, 0.11, 0, 0, 1, 1, 1,
1, 1, 0.78, 0.22, 0, 0, 0, 0, 0)), row.names = c(NA, -360L), groups = structure(list(
id = structure(1:30, .Label = c("P001", "P002", "P003", "P004",
"P005", "P006", "P007", "P008", "P009", "P010", "P011", "P012",
"P013", "P014", "P015", "P016", "P017", "P018", "P019", "P020",
"P021", "P022", "P023", "P024", "P025", "P026", "P027", "P028",
"P029", "P030"), class = "factor"), .rows = structure(list(
1:12, 13:24, 25:36, 37:48, 49:60, 61:72, 73:84, 85:96,
97:108, 109:120, 121:132, 133:144, 145:156, 157:168,
169:180, 181:192, 193:204, 205:216, 217:228, 229:240,
241:252, 253:264, 265:276, 277:288, 289:300, 301:312,
313:324, 325:336, 337:348, 349:360), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -30L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
data_averaged <- data %>%
group_by(card_self) %>%
summarise(percent = mean(percent))
ggplot(data, aes(x = card_self, y = percent)) +
geom_line(aes(group=id, color=id, size=1, alpha=0.8)) +
geom_line(data = data_averaged, aes(size=10, alpha=0.9)) +
guides(color='none', alpha='none', size='none')

Update: Important comment from teunbrand:
"In addition, I'd like to add that the reason the group aesthetic should be added is because discrete x-axes automatically group observations"
Just add group=1 to ggplot()
The issue is that the second geom_line is not grouped. The data points must be grouped to connect correctly.
ggplot(data, aes(x = card_self, y = percent, group=1)) +
geom_line(aes(group=id, color=id, size=1, alpha=0.8)) +
geom_line(data = data_averaged, aes(size=10, alpha=0.9)) +
guides(color='none', alpha='none', size='none')
# also works:
ggplot(data, aes(x = card_self, y = percent)) +
geom_line(aes(group=id, color=id, size=1, alpha=0.8)) +
geom_line(data = data_averaged, aes(size=10, alpha=0.9, group=1)) +
guides(color='none', alpha='none', size='none')

R ggplot2 line graph adding fill when I don't want it

I've got a dataset with some velocity data. I have an extra column in this dataset called followtime that corresponds to certain values in velocity, and highlights them as a factor (ie, certain values in trial 1 will be highlighted in followtime with 1 and the rest 0, certain values in trial 2 will be highlighted with 2 and the rest 0, etc.). See below (this example has random velocities, but followtime is looks pretty much like it does in my own dataset).
trial <- c(rep(1,25), rep(2, 25), rep(3, 25))
minitime <- c(1:25)
time <- c(rep(minitime, 3))
totalsmooth_velocity <- runif(75, min=-3, max=2)
followtime <- c(rep(0, 10), rep(1, 10), rep(0,5), rep(0, 5), rep(2, 5), rep(0, 15), rep(0, 15), rep(3, 10))
df <- cbind(trial, time, totalsmooth_velocity, followtime)
df <- as.data.frame(df)
df$time <- as.integer(df$time)
I'd like to make a line graph with ggplot2 that color-codes each followtime in a different color. Here's my data graphed with a scatter plot (which for some reason has no trouble with this):
With corresponding code:
stim1bfollows<- ggplot()+
geom_point(data=df, aes(x=time, y=totalsmooth_velocity, color = as.factor(followtime)), size = 1.0)+
geom_hline(yintercept=c(0, -0.16))
stim1bfollows
When I try to code this as a line graph, however, it looks like this:
With corresponding code:
stim1bfollows<- ggplot()+
geom_line(data=df, aes(x=time, y=totalsmooth_velocity, color = as.factor(followtime)), size = 1.0)+
geom_hline(yintercept=c(0, -0.16))
stim1bfollows
I don't want that fill! I'm not sure what's going wrong, I've tried a couple of changes with 'dodge' and treated color as both a factor and as numerically but if anybody could point me in the right direction I'd be extremely grateful. Thank you!
EDIT
Having this issue even with group! Image:
stim1bfollows<- ggplot()+
geom_line(data=follows, aes(x=time, y=totalsmooth_velocity, group = as.factor(followtime), color = as.factor(followtime)), size = 1.0)+
geom_hline(yintercept=c(0, -0.16))
stim1bfollows
Also for reference, my str(follows) of the original dataset:
str(follows)
'data.frame': 750 obs. of 13 variables:
$ bartrial : int 9 9 9 9 9 9 9 9 9 9 ...
$ trial : int 1 1 1 1 1 1 1 1 1 1 ...
$ time : int 17026 17027 17028 17029 17030 17031 17032 17033 17034 17035 ...
$ X : num 158 158 158 158 158 ...
$ Y : num 64.5 64.6 64.6 64.5 64.5 ...
$ velocity : num 0.05766 -0.0266 -0.05106 -0.00543 0.04506 ...
$ barvelocity : num -0.16 -0.16 -0.16 -0.16 -0.16 -0.16 -0.16 -0.16 -0.16 -0.16 ...
$ index : num -0.3604 0.1663 0.3191 0.0339 -0.2816 ...
$ veldiff : num 0.218 0.133 0.109 0.155 0.205 ...
$ direction : logi TRUE TRUE TRUE TRUE TRUE TRUE ...
$ response : int 0 1 1 1 0 0 0 0 1 0 ...
$ totalsmooth_velocity: num 0.0173 0.0185 0.0202 0.0233 0.0272 ...
$ followtime : num 0 0 0 0 0 0 0 0 0 0 ...
And the head:
head(follows)
bartrial trial time X Y velocity barvelocity index veldiff direction response
2001 9 1 17026 158.2507 64.52043 0.057657143 -0.16 -0.36035714 0.2176571 TRUE 0
2002 9 1 17027 158.1855 64.57809 -0.026600000 -0.16 0.16625000 0.1334000 TRUE 1
2003 9 1 17028 158.2674 64.55149 -0.051057143 -0.16 0.31910714 0.1089429 TRUE 1
2004 9 1 17029 158.2733 64.50043 -0.005428571 -0.16 0.03392857 0.1545714 TRUE 1
2005 9 1 17030 158.2763 64.49500 0.045057143 -0.16 -0.28160714 0.2050571 TRUE 0
2006 9 1 17031 158.2363 64.54006 0.028971429 -0.16 -0.18107143 0.1889714 TRUE 0
totalsmooth_velocity followtime
2001 0.01732903 0
2002 0.01852428 0
2003 0.02024635 0
2004 0.02326663 0
2005 0.02719260 0
2006 0.03045590 0
Adding a small subset:
dput(subset(follows, time %in% 17100:17130))
structure(list(bartrial = c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L), trial = 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, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L), time = c(17100L,
17101L, 17102L, 17103L, 17104L, 17105L, 17106L, 17107L, 17108L,
17109L, 17110L, 17111L, 17112L, 17113L, 17114L, 17115L, 17116L,
17117L, 17118L, 17119L, 17120L, 17121L, 17122L, 17123L, 17124L,
17125L, 17126L, 17127L, 17128L, 17129L, 17130L, 17100L, 17101L,
17102L, 17103L, 17104L, 17105L, 17106L, 17107L, 17108L, 17109L,
17110L, 17111L, 17112L, 17113L, 17114L, 17115L, 17116L, 17117L,
17118L, 17119L, 17120L, 17121L, 17122L, 17123L, 17124L, 17125L,
17126L, 17127L, 17128L, 17129L, 17130L, 17100L, 17101L, 17102L,
17103L, 17104L, 17105L, 17106L, 17107L, 17108L, 17109L, 17110L,
17111L, 17112L, 17113L, 17114L, 17115L, 17116L, 17117L, 17118L,
17119L, 17120L, 17121L, 17122L, 17123L, 17124L, 17125L, 17126L,
17127L, 17128L, 17129L, 17130L), X = c(158.554971428571, 158.561857142857,
158.545942857143, 158.442742857143, 158.463457142857, 158.447628571429,
158.4628, 158.426028571429, 158.3998, 158.355114285714, 158.339971428571,
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158.301342857143, 158.308428571429, 158.227228571429, 158.250057142857,
158.226771428571, 158.174914285714, 158.200485714286, 158.213085714286,
98.11471429, 99.706, 101.0531143, 102.1066286, 103.2292, 103.9274,
104.7769429, 105.7868571, 106.5872857, 107.3484286, 108.6168571,
109.3342286, 110.2153714, 111.2181714, 112.8689429, 114.7111143,
116.7568571, 118.523, 119.8732857, 121.4064, 122.5118286, 123.6406286,
124.6844, 125.5278286, 126.3410286, 128.1753143, 129.8935429,
131.1022857, 132.2688286, 133.3624571, 133.9324286, 96.6617714285714,
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90.7313428571429, 88.4762, 85.5486571428571, 82.0275142857143,
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50.0204, 48.7530285714286, 47.9830571428571, 46.7885142857143,
45.3995428571429, 43.5878, 41.7556285714286, 39.6544571428571,
37.6700285714286, 35.0251714285714, 32.6265714285714, 29.3777142857143
), Y = c(57.2500571428571, 57.0420857142857, 56.7889714285714,
56.6496857142857, 56.5398571428571, 56.4711714285714, 56.2698285714286,
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189.6266286, 189.5072571, 189.4862571, 189.3138, 189.2692571,
189.2216857, 189.1862857, 189.1338, 189.0529143, 188.9495429,
188.8440286, 188.7655143, 188.7224286, 188.5904857, 188.5451429,
188.5732286, 188.3531429, 188.1283429, 187.9746571, 187.5346,
187.2002857, 186.9196571, 186.6167429, 186.5036857, 186.2668,
185.873, 185.4187714, 185.1869429, 184.8553429, 184.6551429,
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13.2676714285714, 13.3456028571429, 13.3960371428571, 13.4590771428571,
13.46362, 13.5725371428571, 13.756, 13.8612657142857, 13.9868371428571,
14.1618342857143, 14.4414857142857), velocity = c(-0.207971428571433,
-0.253114285714283, -0.139285714285712, -0.109828571428572, -0.0686857142857136,
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0.0895428571428578, -0.410385714285713, -0.0525514285714301,
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0.12557142857143, 0.174997142857144, 0.279651428571428, 0.17196
), barvelocity = c(-0.16, -0.16, -0.16, -0.16, -0.16, -0.16,
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TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
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TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE), response = c(1L, 1L, 1L, 1L, 1L, 1L,
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0L, 0L, 0L, 0L, 0L, 0L, 0L), totalsmooth_velocity = c(-0.185715482616494,
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0.112958997476596, 0.13498042401608, 0.156286940578198, 0.175363274888579,
0.190694154672854, 0.197511866511148, 0.197482141367721, 0.198739873544398,
0.206075849950098, 0.215615753800187, 0.222496823856169, 0.221856298879546,
0.209154962712217, 0.189688538371653, 0.173346673382715, 0.154502814473438,
0.127758414088336, 0.103345128326991, 0.091494613288984, 0.0964662157108718,
0.11027334789746, 0.124778764300703, 0.146992697502439, 0.180840414940991,
0.213557223353035, 0.232378429475247), followtime = c(0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3)), row.names = c("2075", "2076", "2077", "2078",
"2079", "2080", "2081", "2082", "2083", "2084", "2085", "2086",
"2087", "2088", "2089", "2090", "2091", "2092", "2093", "2094",
"2095", "2096", "2097", "2098", "2099", "2100", "2101", "2102",
"2103", "2104", "2105", "20751", "20761", "20771", "20781", "20791",
"20801", "20811", "20821", "20831", "20841", "20851", "20861",
"20871", "20881", "20891", "20901", "20911", "20921", "20931",
"20941", "20951", "20961", "20971", "20981", "20991", "21001",
"21011", "21021", "21031", "21041", "21051", "20752", "20762",
"20772", "20782", "20792", "20802", "20812", "20822", "20832",
"20842", "20852", "20862", "20872", "20882", "20892", "20902",
"20912", "20922", "20932", "20942", "20952", "20962", "20972",
"20982", "20992", "21002", "21012", "21022", "21032", "21042",
"21052"), class = "data.frame")

You need to use groupin your aes for geom_line:
ggplot(data=df, aes(x=time, y=totalsmooth_velocity, group = as.factor(followtime), color = as.factor(followtime)))+
geom_point( size = 1.0)+
geom_hline(yintercept=c(0, -0.16), color = "black")+
geom_line()

Ok, after several iterations, I did need to include an aes(group) value. However, in this case, I grouped by the original trials, instead of the followtimes. Ggplot2 was treating all followtimes=0 as the same group. New code:
stim1bfollows<- ggplot(data=follows, aes(x=time, y=totalsmooth_velocity, group=as.factor(trial), color=as.factor(followtime)))+
geom_line(size = 1.0)+
geom_point(size=1.5)+
geom_hline(yintercept=c(0,-0.16), color = c("black", "red"))+scale_color_manual(values = c("black", "coral", "aquamarine4", "violetred"))
stim1bfollows
And new graph (keeping the geom_point overlay over geom_line, makes the figure look really slick):
Thanks for the help.

Why do geom_rect() add many multiple layers when used with facet_wrap()?

I am adding a color bar using geom_rect() in combination with facet_wrap(), but for some reason 30 layers are added, which means the bar is completely dark even though I use alpha = 0.2.
I can export to powerpoint and delete all the extra layes manually, but that is a huuuge pain. Is there a way to fix this problem?
I have tried to restart the terminal and to only load the package needed, thinking maybe the error occured do to a loaded function, but no, it does not seem to be the case.
dat <- structure(list(variable = 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, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 18L, 18L,
18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L,
18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L,
18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L), .Label = c("alat", "asat", "chol", "cl",
"fhb", "ft3", "ft4", "ggt", "gluk", "hdlch", "hrs", "k", "kreae",
"ldh", "ldlch", "lipa", "mg", "na", "phos", "prot", "trig", "tsh"
), class = "factor"), diff_A = c(0.03, -0.02, -0.01, 0, -0.03,
-0.01, -0.01, 0.03, 0.02, 0, 0.01, 0.0099999999999999, 0, 0.02,
0.01, 0, -0.03, -0.02, -0.01, 0.02, 0, -0.01, 0.02, 0.02, 0,
0.03, -0.02, -0.01, 0, 0.00999999999999995, 0, 0, 0.01, 0, -0.0299999999999999,
0.04, 0.03, -0.04, 0, 0.02, 0.03, -0.03, -0.01, -0.05, -0.07,
-0.01, -0.00999999999999995, 0.02, 0, 0.0099999999999999, 0.01,
0.06, -0.04, 0.01, 0.06, -0.03, 0.01, 0.03, 0.02, 0, 0.02, 0,
0.00999999999999995, 0.00999999999999995, -0.01, 0.01, -0.02,
0.02, 0.02, 0.13, 0.0999999999999996, 0.2, 0, 0, 0.3, 0, -0.2,
0.100000000000001, 0, -0.2, 0.0999999999999996, -0.1, 0, -0.300000000000001,
-0.0999999999999996, 0, 0, -0.2, 0.100000000000001, -0.100000000000001,
-0.3, -0.0999999999999996, -0.0999999999999996, 0.3, 0, 0.2,
0, 0, 0.100000000000001, -0.2, 0, 0, -0.199999999999999, 0.0999999999999996,
-0.0999999999999996, 1, -1, 0, 0, 3, -1, 0, 0, -1, -2, 0, -2,
0, -1, 1, 0, -2, -2, 0, 1, -1, 1, -1, 3, -2, 0, 0, -1, -1, 1,
0, 0, -1, 0, 0, 1, 0, 2, 1, -1, 1, 0, 3, 2, -3, 4, 1, -2, 2,
1, 3, 0, 2, 2, 4, -2, -1, 1, 1, 1, 1, 1, 3, 5, 0, 1.1, -1, 1,
1, 1, 0.23, -0.71, 0.21, 0.0599999999999996, -0.4, 0.59, -0.0299999999999994,
0.0899999999999999, 0.15, -0.0700000000000003, -0.04, -0.0999999999999996,
0.13, -0.79, -0.27, -0.18, -0.0600000000000001, -0.26, 0.24,
0.63, -0.0500000000000007, -0.28, -0.31, 0.43, -0.2, -0.0499999999999998,
0.149999999999999, -0.319999999999999, 0.0999999999999996, 0.34,
0.0499999999999998, -0.1, 0.3, 0.0699999999999998, 0.0600000000000001,
0.699999999999999, 0.6, 0, 0.300000000000001, -0.199999999999999,
-0.0299999999999994, -0.299999999999999, -0.0999999999999996,
-0.199999999999999, 0.0999999999999996, 0, 0.0999999999999979,
0.0999999999999996, -0.0999999999999996, -0.200000000000001,
-0.0299999999999994, -0.300000000000001, -0.9, -0.0999999999999996,
0.5, -0.5, 0.0999999999999996, -0.0999999999999996, 0.4, -0.200000000000001,
0.300000000000001, 0, -0.199999999999999, -0.4, 0.4, -0.0999999999999996,
0.5, 0.800000000000001, -0.100000000000001, 0.5, 0.02, 0.01,
-0.02, -0.01, 0.05, 0, 0.02, 0, -0.00999999999999995, 0, -0.01,
0.0599999999999999, -0.01, 0.03, 0.01, 0.04, 0.07, 0.05, -0.01,
-0.06, 0.03, -0.03, 0, -0.03, 0.04, 0.01, -0.01, 0, 0.02, -0.03,
0.02, 0.03, 0.03, -0.02, 0, -0.0999999999999996, 0.100000000000001,
0.0999999999999996, -0.199999999999999, -0.4, -0.6, -0.0999999999999996,
0.2, 0, 0.1, -0.0999999999999996, 0.0999999999999996, -0.1, 0.0999999999999996,
-0.100000000000001, 0.0999999999999996, -0.7, -0.2, 0.4, 0.399999999999999,
-0.0999999999999996, -0.0999999999999996, -0.100000000000001,
-0.2, -0.100000000000001, 0.100000000000001, -0.0999999999999996,
-0.1, 0.100000000000001, -0.3, 0, 0, -0.300000000000001, -0.1,
0.3, 0.01, -0.02, 0.01, -0.0900000000000001, 0.11, 0.00999999999999979,
-0.01, -0.01, 0.04, -0.0699999999999998, -0.04, -0.03, 0.03,
-0.0399999999999998, 0.1, 0, 0.03, -0.0700000000000001, -0.0599999999999998,
0.04, 0.03, 0.12, -0.0900000000000001, 0.1, -0.0600000000000001,
0.0700000000000001, 0.02, 0, -0.0399999999999998, 0.0900000000000003,
-0.02, -0.03, 0.03, 0.11, 0, 1, 2, 0, 1, 20, 8, 4, 9, -12, -23,
1, -13, -2, 2, -10, 0, 2, 2, 2, 2, 7, 9, -7, 6, 1, -9, -3, 0,
-12, 12, -2, 1, 14, -3, 4, 0, 0, 0.1, 0, 0.0999999999999996,
-0.0999999999999996, 0, 0.1, 0, -0.1, 0, 0, -0.0999999999999996,
0, 0, 0, -0.3, -0.0999999999999996, 0.1, 0.1, 0, -0.1, 0, 0,
0.1, -0.2, 0.1, 0, 0, 0, 0, 0, 0, 0, 0.2, -3, 1, 4, 0, -2, 0,
-1, 3, 1, -3, -5, -2, -1, -4, -2, -1, -3, -8, 4, 0, -14, 6, 1,
16, -14, 1, 5, 1, -2, 7, 0, -8, 3, -2, -2, 0.0800000000000001,
0.12, 0.04, 0.0600000000000001, 0.0499999999999998, -0.26, 0.0600000000000001,
0.0499999999999998, 0.42, 0.02, 0.1, 0.3, 0, 0.32, 0.02, 0.11,
0.0900000000000003, 0.0600000000000001, -0.2, 0.26, -0.14, -0.32,
0.27, -0.24, 0.0300000000000002, 0.0799999999999996, 0.14, 0.59,
0.25, 0.02, 0.11, 0.0500000000000003, 0.13, 0.27, 0.14, 0, 0.0100000000000002,
-0.02, 0, -0.11, -0.12, -0.02, -0.13, -0.02, 0.1, 0, 0.17, 0.11,
-0.14, 0.0500000000000003, 0.00999999999999979, 0.02, -0.0900000000000003,
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0.0299999999999998, 0.0800000000000001, -0.34, 0.04, -0.2, 0.04,
0.0799999999999996, 0.0299999999999998, 0.0499999999999998, 0.19,
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0.00999999999999979, 0.15, 0.1, -0.0299999999999998, 0.04, -0.15,
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0.02, 0.13, -0.0100000000000002, -0.01, 0.0299999999999998, -0.1,
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0.0199999999999999, -0.01, 0.03, -0.01, 0.03, 0, -0.02, 0, 0,
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0.0499999999999999, -0.0599999999999999, -0.01, -0.01, 0.03,
-0.0299999999999999, -0.01, -0.03, -0.01, 0.02, 0.01, -0.03,
0, 0.0499999999999999, -0.05, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, -3,
0, -1, 0, -2, 2, 0, 1, 0, 0, 1, -1, 1, 1, 0, 0, 0, 2, -1, -1,
1, -1, -1, -1, 0, 0, 0.01, 0.05, -0.02, 0.01, 0.02, -0.0299999999999998,
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0.02, 0.01, -0.0399999999999999, 0, 0.03, 0.01, 0.01, 1, 0, 0,
0, 2, -1, -2, 3, -1, -1, 1, -1, 0, 0, 0, -2, 1, 2, -3, -1, 2,
1, 1, 1, -1, 2, 1, 1, 1, 2, 0, -1, 3, -2, -1, 0.01, 0, -0.02,
0.04, 0, -0.04, 0.03, -0.0299999999999999, -0.01, -0.01, 0.01,
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0.0699999999999998, 0, 0.02, -0.01, -0.05, -0.02, 0.02, 0, 0.0399999999999998,
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-0.05, 0, -0.12, -0.13, -0.03, 0, -0.0600000000000001, 0.03,
-0.01, 0, 0.02, 0.04, -0.0600000000000001, 0.035, -0.02, 0.0309999999999999,
0.0599999999999998, 0.01, 0.03, 0.0500000000000003, -0.0399999999999996,
0.0499999999999998, 0, 0.00800000000000001, 0, -0.00900000000000001,
0.14, 0, -0.025), MD_Fuss = c(0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
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0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.09, 0.09, 0.09, 0.09,
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0.09, 0.09, 0.09, 0.09, 0.09, 0.09, 0.09, 0.09, 0.09, 0.54, 0.54,
0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54,
0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54,
0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54, 0.54,
6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49,
6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49,
6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49, 6.49,
6.49, 6.49, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66,
0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66,
0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.66,
0.66, 0.66, 0.66, 0.66, 0.66, 0.66, 0.81, 0.81, 0.81, 0.81, 0.81,
0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81,
0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81,
0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84,
12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84,
12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84,
12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84, 12.84,
12.84, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,
0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,
0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,
0.17, 0.17, 0.17, 0.17, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79,
16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79,
16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79,
16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79, 16.79,
16.79, 16.79, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36,
0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36,
0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36,
0.36, 0.36, 0.36, 0.36, 0.36, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29,
0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29,
0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29,
0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.06, 0.06,
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06,
5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21,
5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21,
5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21, 5.21,
5.21, 5.21, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19,
3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19,
3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 3.19,
3.19, 3.19, 3.19, 3.19, 3.19, 3.19, 0.11, 0.11, 0.11, 0.11, 0.11,
0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11,
0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11,
0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16)), class = "data.frame", row.names = c(NA,
-770L))
and this is the plot:
p <- ggplot(data=dat, aes(y = diff_A))+
geom_boxplot(outlier.shape = 1)+
geom_rect(aes(ymin = -MD_Fuss, ymax = MD_Fuss), xmin = -Inf, xmax =Inf, alpha = 0.2)+
theme_bw()+ theme(panel.grid = element_blank())+
xlab('')+ ylab('[mmol/L]') +
scale_y_continuous(expand = c(0.5, 0))+
facet_wrap(.~variable, scales = 'free')
p

geom_rect() draws a rectangle for each row in your data. To get only one rectangle per facet, you need to pass it a data set that contains only one row per faceting variable. Since MD_Fuss seems to be constant within a variable, you can create that data set with unique(dat[, c("variable", "MD_Fuss")]), and then pass it as the data argument to geom_rect():
library(ggplot2)
p <- ggplot(data = dat) +
geom_boxplot(aes(y = diff_A), outlier.shape = 1) +
geom_rect(
data = unique(dat[, c("variable", "MD_Fuss")]),
aes(ymin = -MD_Fuss, ymax = MD_Fuss),
xmin = -Inf, xmax = Inf, alpha = 0.2,
) +
theme_bw() + theme(panel.grid = element_blank()) +
xlab("") + ylab("[mmol/L]") +
scale_y_continuous(expand = c(0.5, 0)) +
facet_wrap(. ~ variable, scales = "free")
p
#> Warning: Removed 2 rows containing missing values (geom_rect).
Created on 2019-07-19 by the reprex package (v0.3.0.9000)

correlation plots for consecutive study sites within a loop: how can i add site names as main headers?

edited to include dput(Nitrate_set) output:
structure(list(SITE.NO = structure(c(41L, 42L, 41L, 3L, 35L,
42L, 40L, 40L, 40L, 1L, 40L, 1L, 40L, 40L, 16L, 40L, 42L, 40L,
40L, 42L, 1L, 42L, 40L, 1L, 40L, 1L, 40L, 4L, 42L, 21L, 15L,
5L, 36L, 40L, 40L, 2L, 41L, 6L, 2L, 12L, 42L, 19L, 2L, 1L, 1L,
1L, 2L, 42L, 1L, 2L, 7L, 1L, 39L, 2L, 2L, 2L, 2L, 39L, 11L, 37L,
2L, 1L, 1L, 1L, 1L, 32L, 1L, 41L, 2L, 2L, 1L, 2L, 1L, 1L, 2L,
1L, 2L, 40L, 42L, 1L, 2L, 38L, 1L, 1L, 2L, 2L, 2L, 41L, 38L,
1L, 8L, 42L, 42L, 1L, 2L, 2L, 33L, 1L, 2L, 18L, 2L, 1L, 2L, 2L,
1L, 41L, 1L, 2L, 1L, 40L, 1L, 2L, 2L, 2L, 1L, 2L, 41L, 10L, 14L,
2L, 2L, 2L, 2L, 42L, 9L, 1L, 1L, 2L, 2L, 2L, 38L, 1L, 1L, 2L,
2L, 38L, 42L, 38L, 40L, 42L, 41L, 1L, 1L, 2L, 38L, 38L, 1L, 38L,
2L, 1L, 2L, 2L, 2L, 17L, 2L, 42L, 41L, 2L, 1L, 1L, 2L, 1L, 38L,
1L, 1L, 38L, 38L, 38L, 38L, 2L, 1L, 2L, 26L, 38L, 38L, 1L, 2L,
38L, 38L, 2L, 1L, 1L, 1L, 38L, 38L, 1L, 31L, 2L, 2L, 1L, 1L,
34L, 24L, 38L, 2L, 28L, 38L, 25L, 38L, 38L, 38L, 38L, 39L, 1L,
38L, 1L, 29L, 38L, 38L, 1L, 38L, 2L, 2L, 22L, 1L, 27L, 1L, 30L,
38L, 38L, 1L, 2L, 2L, 38L, 2L, 38L, 38L, 38L, 13L, 38L, 1L, 38L,
1L, 23L, 2L, 39L, 20L, 38L, 38L, 2L, 38L, 38L, 38L, 38L, 38L,
38L, 38L, 38L, 38L, 1L, 38L, 38L, 41L, 38L, 1L, 38L, 38L, 2L,
38L, 38L, 38L, 38L, 1L, 38L, 1L, 38L, 2L, 2L, 38L, 1L, 40L, 2L,
42L, 41L, 42L, 38L, 42L, 38L, 41L, 2L, 42L, 1L, 38L, 38L, 42L,
2L, 42L, 38L, 38L, 2L, 2L, 2L, 39L, 40L, 2L, 42L, 1L, 1L, 38L,
40L, 41L, 2L, 41L, 41L, 1L, 2L, 41L, 1L, 39L, 41L, 1L, 41L, 40L,
1L, 39L, 39L, 2L, 40L, 38L, 1L, 2L, 2L, 38L, 39L, 1L, 2L, 38L,
41L, 38L, 38L, 2L, 38L, 38L, 41L, 2L, 39L, 43L, 39L, 41L, 43L,
43L, 43L, 43L, 41L, 39L, 39L, 41L, 43L, 41L, 39L, 39L, 39L, 39L,
39L, 39L, 43L, 43L, 43L, 43L, 43L, 41L), .Label = c("1110056",
"1111019", "1120054", "1120055", "1120060", "1120061", "1120062",
"1120065", "1120066", "1120067", "1120068", "1120069", "1120070",
"1120071", "1120073", "1120074", "1120075", "1120076", "1120077",
"1120078", "1120079", "1120080", "1120081", "1120082", "1120083",
"1120084", "1120085", "1120086", "1120087", "1120088", "1120089",
"1120090", "1120091", "1120092", "1120094", "1120095", "1120096",
"113006A", "122013A", "125013A", "126001A", "1260122", "141010A"
), class = "factor"), SITE.NAME = structure(c(8L, 5L, 8L, 2L,
2L, 5L, 4L, 4L, 4L, 3L, 4L, 3L, 4L, 4L, 2L, 4L, 5L, 4L, 4L, 5L,
3L, 5L, 4L, 3L, 4L, 3L, 4L, 2L, 5L, 2L, 2L, 2L, 2L, 4L, 4L, 7L,
8L, 2L, 7L, 2L, 5L, 2L, 7L, 3L, 3L, 3L, 7L, 5L, 3L, 7L, 2L, 3L,
6L, 7L, 7L, 7L, 7L, 6L, 2L, 2L, 7L, 3L, 3L, 3L, 3L, 2L, 3L, 8L,
7L, 7L, 3L, 7L, 3L, 3L, 7L, 3L, 7L, 4L, 5L, 3L, 7L, 9L, 3L, 3L,
7L, 7L, 7L, 8L, 9L, 3L, 2L, 5L, 5L, 3L, 7L, 7L, 2L, 3L, 7L, 2L,
7L, 3L, 7L, 7L, 3L, 8L, 3L, 7L, 3L, 4L, 3L, 7L, 7L, 7L, 3L, 7L,
8L, 2L, 2L, 7L, 7L, 7L, 7L, 5L, 2L, 3L, 3L, 7L, 7L, 7L, 9L, 3L,
3L, 7L, 7L, 9L, 5L, 9L, 4L, 5L, 8L, 3L, 3L, 7L, 9L, 9L, 3L, 9L,
7L, 3L, 7L, 7L, 7L, 2L, 7L, 5L, 8L, 7L, 3L, 3L, 7L, 3L, 9L, 3L,
3L, 9L, 9L, 9L, 9L, 7L, 3L, 7L, 2L, 9L, 9L, 3L, 7L, 9L, 9L, 7L,
3L, 3L, 3L, 9L, 9L, 3L, 2L, 7L, 7L, 3L, 3L, 2L, 2L, 9L, 7L, 2L,
9L, 2L, 9L, 9L, 9L, 9L, 6L, 3L, 9L, 3L, 2L, 9L, 9L, 3L, 9L, 7L,
7L, 2L, 3L, 2L, 3L, 2L, 9L, 9L, 3L, 7L, 7L, 9L, 7L, 9L, 9L, 9L,
2L, 9L, 3L, 9L, 3L, 2L, 7L, 6L, 2L, 9L, 9L, 7L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 3L, 9L, 9L, 8L, 9L, 3L, 9L, 9L, 7L, 9L, 9L,
9L, 9L, 3L, 9L, 3L, 9L, 7L, 7L, 9L, 3L, 4L, 7L, 5L, 8L, 5L, 9L,
5L, 9L, 8L, 7L, 5L, 3L, 9L, 9L, 5L, 7L, 5L, 9L, 9L, 7L, 7L, 7L,
6L, 4L, 7L, 5L, 3L, 3L, 9L, 4L, 8L, 7L, 8L, 8L, 3L, 7L, 8L, 3L,
6L, 8L, 3L, 8L, 4L, 3L, 6L, 6L, 7L, 4L, 9L, 3L, 7L, 7L, 9L, 6L,
3L, 7L, 9L, 8L, 9L, 9L, 7L, 9L, 9L, 8L, 7L, 6L, 1L, 6L, 8L, 1L,
1L, 1L, 1L, 8L, 6L, 6L, 8L, 1L, 8L, 6L, 6L, 6L, 6L, 6L, 6L, 1L,
1L, 1L, 1L, 1L, 8L), .Label = c("Coochin Creek at Mawsons Road",
"Johnstone River at Coquette Point Gbr_Jri_Wq", "Mulgrave River at Deeral",
"Pioneer River at Dumbleton Weir Headwater", "Plane Creek at Sucrogen Weir",
"Proserpine River at Glen Isla", "Russell River at East Russell",
"Sandy Creek at Homebush", "Tully River at Euramo"), class = "factor"),
Date = structure(c(64L, 62L, 48L, 63L, 42L, 8L, 54L, 75L,
75L, 48L, 12L, 73L, 3L, 37L, 40L, 17L, 69L, 69L, 47L, 4L,
27L, 4L, 48L, 64L, 74L, 79L, 74L, 79L, 54L, 49L, 40L, 80L,
61L, 62L, 64L, 53L, 3L, 80L, 53L, 4L, 81L, 45L, 53L, 53L,
50L, 53L, 50L, 31L, 50L, 50L, 81L, 53L, 17L, 53L, 50L, 70L,
46L, 43L, 4L, 6L, 70L, 53L, 13L, 65L, 13L, 2L, 56L, 37L,
25L, 53L, 65L, 68L, 56L, 46L, 2L, 70L, 13L, 12L, 81L, 40L,
6L, 24L, 16L, 16L, 46L, 68L, 2L, 80L, 52L, 68L, 81L, 81L,
14L, 46L, 30L, 60L, 30L, 70L, 56L, 45L, 61L, 16L, 65L, 56L,
16L, 81L, 55L, 5L, 32L, 10L, 13L, 13L, 46L, 72L, 32L, 49L,
14L, 4L, 8L, 42L, 35L, 1L, 41L, 37L, 81L, 63L, 52L, 76L,
1L, 32L, 53L, 40L, 55L, 52L, 58L, 53L, 10L, 53L, 20L, 48L,
80L, 19L, 49L, 13L, 56L, 53L, 19L, 50L, 21L, 46L, 35L, 21L,
19L, 45L, 16L, 64L, 81L, 19L, 32L, 25L, 52L, 72L, 38L, 49L,
49L, 26L, 38L, 38L, 38L, 32L, 80L, 16L, 56L, 46L, 50L, 1L,
32L, 41L, 41L, 32L, 58L, 58L, 41L, 56L, 13L, 23L, 68L, 55L,
49L, 32L, 15L, 5L, 55L, 2L, 40L, 65L, 65L, 53L, 58L, 25L,
13L, 5L, 37L, 61L, 11L, 35L, 65L, 60L, 11L, 1L, 52L, 45L,
58L, 52L, 6L, 56L, 49L, 68L, 13L, 68L, 35L, 49L, 55L, 49L,
45L, 30L, 55L, 19L, 8L, 67L, 22L, 70L, 5L, 52L, 45L, 34L,
49L, 45L, 32L, 80L, 16L, 13L, 70L, 49L, 67L, 16L, 19L, 44L,
67L, 42L, 21L, 21L, 80L, 1L, 45L, 45L, 59L, 4L, 59L, 29L,
29L, 21L, 45L, 71L, 45L, 45L, 80L, 4L, 40L, 40L, 8L, 4L,
15L, 81L, 18L, 18L, 15L, 20L, 54L, 81L, 12L, 76L, 57L, 18L,
12L, 81L, 20L, 80L, 80L, 15L, 81L, 81L, 31L, 20L, 8L, 28L,
18L, 20L, 18L, 20L, 80L, 4L, 47L, 69L, 18L, 18L, 62L, 18L,
20L, 10L, 4L, 10L, 4L, 9L, 10L, 12L, 18L, 28L, 9L, 8L, 18L,
18L, 9L, 12L, 8L, 9L, 4L, 28L, 4L, 8L, 8L, 8L, 8L, 10L, 8L,
66L, 39L, 8L, 20L, 77L, 36L, 36L, 36L, 20L, 4L, 74L, 12L,
51L, 20L, 4L, 78L, 78L, 81L, 81L, 4L, 7L, 7L, 7L, 7L, 33L,
12L), .Label = c("1/01/2019", "1/02/2019", "1/11/2018", "10/12/2018",
"11/02/2019", "11/03/2019", "11/04/2019", "11/12/2018", "12/12/2018",
"13/12/2018", "14/01/2019", "14/12/2018", "15/01/2019", "15/11/2018",
"15/12/2018", "16/01/2019", "16/11/2018", "16/12/2018", "17/01/2019",
"17/12/2018", "18/01/2019", "18/02/2019", "18/03/2019", "18/09/2018",
"19/01/2019", "19/02/2019", "19/11/2018", "19/12/2018", "2/01/2019",
"2/02/2019", "2/11/2018", "20/01/2019", "20/04/2019", "20/12/2018",
"21/01/2019", "21/04/2019", "22/11/2018", "24/01/2019", "24/04/2019",
"24/12/2018", "25/01/2019", "25/02/2019", "25/09/2018", "25/10/2018",
"25/12/2018", "26/01/2019", "26/09/2018", "26/11/2018", "26/12/2018",
"27/01/2019", "27/03/2019", "27/12/2018", "28/01/2019", "28/08/2018",
"28/12/2018", "29/01/2019", "29/11/2018", "29/12/2018", "3/01/2019",
"3/02/2019", "3/03/2019", "3/07/2018", "3/09/2018", "3/12/2018",
"30/01/2019", "30/11/2018", "30/12/2018", "31/01/2019", "31/07/2018",
"31/12/2018", "4/01/2019", "4/02/2019", "5/11/2018", "5/12/2018",
"6/12/2018", "7/01/2019", "7/03/2019", "7/12/2018", "8/10/2018",
"8/12/2018", "9/12/2018"), class = "factor"), Trios.nitrate..mg.L. = c(0.01,
0.01, 0.01, 0.01, 0.02, 0.02, 0.02, 0.02, 0.02, 0.03, 0.03,
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.04, 0.04, 0.04, 0.04,
0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.06, 0.06,
0.07, 0.07, 0.07, 0.08, 0.08, 0.08, 0.08, 0.08, 0.08, 0.09,
0.09, 0.09, 0.09, 0.09, 0.09, 0.09, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.11,
0.11, 0.11, 0.11, 0.11, 0.11, 0.11, 0.12, 0.12, 0.12, 0.12,
0.12, 0.12, 0.12, 0.12, 0.12, 0.13, 0.13, 0.13, 0.13, 0.13,
0.13, 0.13, 0.13, 0.13, 0.13, 0.13, 0.13, 0.13, 0.13, 0.13,
0.13, 0.13, 0.13, 0.13, 0.13, 0.14, 0.14, 0.14, 0.14, 0.14,
0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14,
0.14, 0.14, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15,
0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.16, 0.16, 0.16,
0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.17,
0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.18, 0.18, 0.18,
0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.18, 0.19, 0.19,
0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19,
0.19, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 0.21,
0.21, 0.21, 0.21, 0.21, 0.21, 0.22, 0.22, 0.22, 0.22, 0.22,
0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22,
0.22, 0.22, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23,
0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23,
0.23, 0.23, 0.24, 0.24, 0.24, 0.24, 0.24, 0.24, 0.24, 0.24,
0.24, 0.24, 0.24, 0.25, 0.25, 0.25, 0.26, 0.26, 0.26, 0.26,
0.26, 0.26, 0.26, 0.26, 0.26, 0.26, 0.26, 0.26, 0.26, 0.27,
0.27, 0.27, 0.28, 0.28, 0.3, 0.3, 0.3, 0.31, 0.31, 0.31,
0.31, 0.31, 0.32, 0.32, 0.33, 0.34, 0.34, 0.34, 0.35, 0.35,
0.36, 0.36, 0.37, 0.37, 0.37, 0.38, 0.38, 0.38, 0.38, 0.38,
0.39, 0.39, 0.4, 0.42, 0.42, 0.42, 0.43, 0.44, 0.48, 0.49,
0.49, 0.51, 0.51, 0.53, 0.56, 0.57, 0.58, 0.58, 0.58, 0.58,
0.58, 0.61, 0.64, 0.73, 0.76, 0.76, 0.81, 0.82, 0.85, 0.85,
0.85, 0.86, 0.88, 0.92, 0.94, 0.96, 1, 1.04, 1.04, 1.06,
1.14, 1.18, 1.34, 1.37, 1.45, 1.48, 1.48, 1.48, 1.54, 1.58,
1.73, 1.76, 1.82, 1.85, 1.95, 1.95, 1.96, 2.15, 2.18, 2.26,
2.3, 2.3, 2.3, 2.3, 2.69, 3.12), Chem.centre.Nox..mg.L. = c(5e-04,
0.001, 0.086, 0.048, 0.036, 0.015, 0.001, 0.088, 0.305, 0.012,
0.078, 0.023, 0.047, 0.002, 0.08, 0.004, 0.002, 0.003, 0.002,
0.029, 0.009, 0.045, 0.062, 0.006, 0.149, 0.087, 0.311, 0.008,
5e-04, 0.152, 0.03, 0.339, 0.103, 0.048, 0.003, 0.039, 0.159,
0.156, 0.043, 0.209, 0.091, 0.135, 0.039, 0.042, 0.041, 0.049,
0.045, 0.021, 0.045, 0.044, 0.235, 0.051, 0.03, 0.063, 0.046,
0.075, 0.058, 0.303, 0.227, 0.092, 0.094, 0.066, 0.068, 0.055,
0.073, 0.186, 0.079, 5e-04, 0.073, 0.086, 0.074, 0.097, 0.083,
0.062, 0.086, 0.084, 0.088, 0.098, 0.033, 0.093, 0.122, 0.104,
0.09, 0.093, 0.078, 0.095, 0.086, 0.178, 0.155, 0.098, 0.123,
0.134, 0.005, 0.065, 0.105, 0.109, 0.175, 0.098, 0.093, 0.081,
0.116, 0.116, 0.097, 0.098, 0.114, 0.159, 0.083, 0.126, 0.119,
0.092, 0.104, 0.116, 0.093, 0.114, 0.12, 0.118, 5e-04, 0.185,
0.265, 0.14, 0.168, 0.133, 0.116, 0.006, 0.057, 0.149, 0.086,
0.143, 0.137, 0.134, 0.164, 0.237, 0.114, 0.106, 0.123, 0.121,
0.086, 0.117, 0.184, 5e-04, 0.198, 0.148, 0.103, 0.159, 0.128,
0.134, 0.156, 0.134, 0.172, 0.082, 0.168, 0.176, 0.168, 0.153,
0.167, 0.001, 0.162, 0.171, 0.165, 0.152, 0.156, 0.17, 0.126,
0.124, 0.105, 0.188, 0.159, 0.17, 0.147, 0.174, 0.099, 0.176,
0.15, 0.141, 0.213, 0.166, 0.173, 0.181, 0.188, 0.192, 0.156,
0.062, 0.157, 0.167, 0.149, 0.234, 0.13, 0.172, 0.154, 0.194,
0.389, 0.171, 0.163, 0.181, 0.2, 0.156, 0.186, 0.17, 0.19,
0.196, 0.156, 0.218, 0.298, 0.218, 0.184, 0.206, 0.154, 0.193,
0.18, 0.192, 0.192, 0.145, 0.196, 0.158, 0.23, 0.172, 0.171,
0.154, 0.162, 0.209, 0.215, 0.179, 0.196, 0.183, 0.161, 0.208,
0.194, 0.208, 0.22, 0.178, 0.274, 0.184, 0.214, 0.222, 0.144,
0.169, 0.168, 0.183, 0.223, 0.184, 0.195, 0.181, 0.2, 0.202,
0.218, 0.191, 0.223, 0.057, 0.206, 0.237, 0.231, 0.244, 0.295,
0.217, 0.153, 0.214, 0.256, 0.17, 0.246, 0.25, 0.232, 0.247,
0.168, 0.247, 0.156, 0.214, 0.196, 0.183, 0.24, 0.205, 0.519,
0.197, 0.119, 0.306, 0.143, 0.257, 0.118, 0.269, 0.352, 0.256,
0.13, 0.307, 0.066, 0.272, 0.19, 0.261, 0.172, 0.222, 0.232,
0.236, 0.29, 0.276, 0.316, 0.217, 0.257, 0.206, 0.247, 0.28,
0.322, 0.304, 0.412, 0.36, 0.377, 0.421, 0.326, 0.33, 0.464,
0.331, 0.212, 0.456, 0.434, 0.486, 0.253, 0.48, 0.337, 0.549,
0.45, 0.611, 0.579, 0.594, 0.613, 0.672, 0.663, 0.389, 0.694,
0.718, 0.71, 0.692, 0.754, 0.816, 0.77, 0.863, 0.878, 0.388,
0.914, 0.42, 0.918, 1.06, 0.859, 1.58, 1.39, 0.922, 0.633,
1.22, 1.31, 0.399, 1.46, 1.71, 1.51, 1.58, 0.271, 0.44, 4.24,
3.65, 2.06, 2.61, 5e-04, 0.001, 0.065, 1.38, 2.91)), class = "data.frame", row.names = c(NA,
-361L))
>
The input file (Nitrate_set) includes 9 study sites. I have been able to produce a correlation plot between two variables of interest consecutively for each site within a loop, but am unable to add to appropriate site name as a header for each plot. Here's an example of the data:
SITE.NAME COR
1 Coochin Creek at Mawsons Road -0.1122249
2 Johnstone River at Coquette Point Gbr_Jri_Wq 0.3614868
3 Mulgrave River at Deeral 0.9338604
4 Pioneer River at Dumbleton Weir Headwater 0.7270477
5 Plane Creek at Sucrogen Weir 0.8337472
6 Proserpine River at Glen Isla 0.6695578
7 Russell River at East Russell 0.9879924
8 Sandy Creek at Homebush 0.9756037
9 Tully River at Euramo 0.9751152
I would like each correlation plot to display a header appropriate to it's site name. I'm not sure where to put that code within the loop.
This is the first time I am trying to produce plots within a loop and I'm a novice coder. I don't know what to try next..
#Creating function func to calculate correlation for single site
func <- function(Nitrate_set){ return(data.frame(COR = cor(Nitrate_set$Trios.nitrate..mg.L., Nitrate_set$Chem.centre.Nox..mg.L.))) }
#Calling func Function for each site name and storing the results in cor_result. cor_result will show correlation for each site as a list.
cor_result <- ddply(Nitrate_set, .(SITE.NAME), func)
cor_result
#Creating function to display correlation plot for every site
funcPlot <- function(Nitrate_set){
chart.Correlation(Nitrate_set[,c(4,5)], histogram=TRUE, pch=19)
}
#Calling the function to display the plots. This will return nine plots serially. At this point we need to title site name for each site.
ddply(Nitrate_set, .(SITE.NAME), funcPlot)
I expect each plot to be displayed with a header but am unable to work out how and where to put that section of code within the loop

How to differentiate Bars in geom_bar without color: ggplot

Note: A similar question is present at link, but I posed it a separate question due to: 1) only a hack is provided to the previos question which I thought would make code unnecessary complex 2) I thought after 2013 a fix might have been suggested for this
I am using following code to draw bars/stacks
ggplot(finaldataframe,aes(day,score))+
geom_bar(aes(fill=identify),stat="identity",position = "dodge",width = .7, show.legend = TRUE)+
labs(x= "Day of the Month", y="Anomaly Score") +
scale_fill_discrete(name="Method", labels=c("Mean","Maximum","Cumulative \n sum"))+
theme(axis.text= element_text(color="Black"))+ scale_x_continuous(breaks=seq(1,31,5))
A portion of output is as
The problem with this figure is that once I print this via black and white printer It gets hard to differentiate between different stacks. Is there any way to make the stacks differentiable on a black and white print. I am looking for some what like this:
For reproduction, Here is the dput of dataframe:
> dput(finaldataframe)
finaldataframe = structure(list(day = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L), score = c(0, 0.02, 0.01, 0, 0.02, 0.01, 0.01,
0.02, 0.02, 0.28, 0.24, 0.01, 0.94, 0.22, 0.25, 0.01, 0.31, 0.22,
0.24, 0.83, 0.4, 0.44, 0.06, 0.02, 0.37, 0.07, 0.12, 0.06, 0.1,
0.06, 0.1, 0, 0.05, 0.04, 0.02, 0.05, 0.01, 0.02, 0.03, 0.04,
0.37, 0.36, 0.04, 1, 0.28, 0.34, 0.03, 0.55, 0.35, 0.32, 1, 0.71,
1, 0.13, 0.04, 0.47, 0.12, 0.17, 0.1, 0.18, 0.1, 0.14, 0, 0.02,
0.01, 0, 0.02, 0.01, 0.01, 0.02, 0.02, 0.3, 0.25, 0.01, 1, 0.23,
0.27, 0, 0.33, 0.24, 0.26, 0.89, 0.42, 0.47, 0.06, 0.02, 0.4,
0.07, 0.13, 0.06, 0.11, 0.06, 0.1), identify = 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, 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), .Label = c("Mean",
"Maximum", "Cummulative Sum"), class = "factor")), .Names = c("day",
"score", "identify"), row.names = c(NA, 93L), class = "data.frame")