I am planning to plot vertical profile of multiple parameters on x axis, for example, salinity, temperature, density, against pressure as y axis, in the same graph. This is the kind of plot i am hoping to get :
Here is a sample from my data :
ï..IntD.Date. IntT.Time. Salinity..psu. SIGMA.Kg.m3. Pressure.dbar.
1 21-April-2019 5:31:55 PM 30.2502 20.2241 0.7160
2 21-April-2019 5:32:00 PM 31.0254 20.8081 0.8409
3 21-April-2019 5:32:05 PM 31.2654 20.9930 1.0551
4 21-April-2019 5:32:10 PM 31.2953 21.0176 1.2694
Temp..0C. Vbatt.volt.
1 23.4054 12.29
2 23.4148 12.30
3 23.4060 12.29
4 23.4024 12.33
I already used these codes:
data <- read.csv('file location')
vert_plot <- ggplot(data, aes(x = Pressure.dbar., y = Temp..0C.)) + geom_line(color = '#088DA5', size = 0.75) + labs(size = 18) + ggtitle("temp vs pressure") + theme_grey() + coord_flip() + scale_y_reverse()
Which generated this plot :
as you can see, i was able to bring a single profile where the scale of y axis wasn't in reverse order whereas I'd prefer pressure value (0, 5, 10....) starting from the top left corner. Unlike the plot i made where pressure value begins in bottom left corner.
I'd be grateful if someone helped me to get figure where i will be able to plot multiple vertical profile in same graph where y axis is pressure and is in reverse order, as shown in that barrier layer thickness picture.
Add as many geom_line() as required and call aes in each geom_line(). For breaks of 5, add scale_x_continuous and call sequence of breaks in it.
vert_plot <- ggplot(df) +
geom_line(aes(x = Pressure.dbar., y = Temp..0C.), color = 'blue', size = 0.75) +
geom_line(aes(x = Pressure.dbar., y = Salinity..psu.), color = 'red', size = 0.75) +
geom_line(aes(x = Pressure.dbar., y = SIGMA.Kg.m3.), color = 'green', size = 0.75) +
labs(size = 18) + ggtitle("Dummy Title") + xlab("Pressure") + ylab("Dummy Label") +
scale_x_reverse(limits = c(40, 0), breaks = seq(40, 0, -5)) +
theme_grey() + coord_flip() + scale_y_reverse()
Alternate method:
Instead of going through all these, you can melt the data frame keeping the variable names as groups.
library(reshape2)
newdf <- melt(df, id.vars = c("IntD.Date.", "IntT.Time.", "Pressure.dbar."),
variable.name = "group")
vert_plot <- ggplot(newdf, aes(x = Pressure.dbar., y = value, color = group)) +
geom_line(size = 0.75) +
labs(size = 18) + ggtitle("Dummy Title") +
xlab("Pressure") + ylab("Dummy Label") +
scale_x_reverse(limits = c(40, 0), breaks = seq(40, 0, -5)) +
theme_grey() + coord_flip() + scale_y_reverse()
Related
I dont have data between 1 and 11 hrs (inyour text x axis) so I want to delete this portion from my graph.
How can I put zero values in each group instead of being clumped together?
I tried to plot the graph as follows:
plot <- ggplot(bgse_lmean, aes(time_h)) +
geom_point(aes(y = Conc, shape = Isolate, col = Isolate, group = Isolate), size = 2.5)+
geom_line(aes(y = Conc, group= Isolate, col = Isolate))+
scale_x_continuous(breaks=c(0,12, 16, 20, 24))+
xlab("Time (h)") + ylab("Conc mg/ml") +
scale_color_brewer(palette = "Set1") +
facet_wrap(parameters~.,
strip.position = "top",
nrow = 3)
plot
p2 <- plot + scale_x_break(c(1,11))
I'd like to draw bar plot like this but in dual Y axis
(https://i.stack.imgur.com/ldMx0.jpg)
the first three indexs range from 0 to 1,
so I want the left y-axis (corresponding to NSE, KGE, VE) to range from 0 to 1,
and the right y-axis (corresponding to PBIAS) to range from -15 to 5.
the following is my data and code:
library("ggplot2")
## data
data <- data.frame(
value=c(0.82,0.87,0.65,-3.39,0.75,0.82,0.63,1.14,0.85,0.87,0.67,-7.03),
sd=c(0.003,0.047,0.006,4.8,0.003,0.028,0.006,4.77,0.004,0.057,0.014,4.85),
index=c("NSE","KGE","VE","PBIAS","NSE","KGE","VE","PBIAS","NSE","KGE","VE","PBIAS"),
period=c("all","all","all","all","calibration","calibration","calibration","calibration","validation","validation","validation","validation")
)
## fix index sequence
data$index <- factor(data$index, levels = c('NSE','KGE','VE',"PBIAS"))
data$period <- factor(data$period, levels = c('all','calibration', 'validation'))
## bar plot
ggplot(data, aes(x=index, y=value, fill=period))+
geom_bar(position="dodge", stat="identity")+
geom_errorbar(aes(ymin=value-sd, ymax=value+sd),
position = position_dodge(0.9), width=0.2 ,alpha=0.5, size=1)+
theme_bw()
I try to scale and shift the second y-axis,
but PBIAS bar plot was removed because of out of scale limit as follow:
(https://i.stack.imgur.com/n6Jfm.jpg)
the following is my code with dual y axis:
## bar plot (scale and shift the second y-axis with slope/intercept in 20/-15)
ggplot(data, aes(x=index, y=value, fill=period))+
geom_bar(position="dodge", stat="identity")+
geom_errorbar(aes(ymin=value-sd, ymax=value+sd),
position = position_dodge(0.9), width=0.2 ,alpha=0.5, size=1)+
theme_bw()+
scale_y_continuous(limits = c(0,1), name = "value", sec.axis = sec_axis(~ 20*.- 15, name="value"))
Any advice for move bar_plot or other solution？
Taking a different approach, instead of using a dual axis one option would be to make two separate plots and glue them together using patchwork. IMHO that is much easier than fiddling around with the rescaling the data (that's the step you missed, i.e. if you want to have a secondary axis you also have to rescale the data) and makes it clearer that the indices are measured on a different scale:
library(ggplot2)
library(patchwork)
data$facet <- data$index %in% "PBIAS"
plot_fun <- function(.data) {
ggplot(.data, aes(x = index, y = value, fill = period)) +
geom_bar(position = "dodge", stat = "identity") +
geom_errorbar(aes(ymin = value - sd, ymax = value + sd),
position = position_dodge(0.9), width = 0.2, alpha = 0.5, size = 1
) +
theme_bw()
}
p1 <- subset(data, !facet) |> plot_fun() + scale_y_continuous(limits = c(0, 1))
p2 <- subset(data, facet) |> plot_fun() + scale_y_continuous(limits = c(-15, 15), position = "right")
p1 + p2 +
plot_layout(guides = "collect", width = c(3, 1))
A second but similar option would be to use ggh4x which via ggh4x::facetted_pos_scales allows to set the limits for facet panels individually. One drawback, the panels have the same width. (I failed in making this approach work with facet_grid and space="free")
library(ggplot2)
library(ggh4x)
data$facet <- data$index %in% "PBIAS"
ggplot(data, aes(x = index, y = value, fill = period)) +
geom_bar(position = "dodge", stat = "identity") +
geom_errorbar(aes(ymin = value - sd, ymax = value + sd),
position = position_dodge(0.9), width = 0.2, alpha = 0.5, size = 1
) +
facet_wrap(~facet, scales = "free") +
facetted_pos_scales(
y = list(
facet ~ scale_y_continuous(limits = c(-15, 15), position = "right"),
!facet ~ scale_y_continuous(limits = c(0, 1), position = "left")
)
) +
theme_bw() +
theme(strip.text.x = element_blank())
I am attempting to make a multi-panelled plot from three individual plots (see images).However, I am unable to rectify the bunched x-axis tick labels when the plots are in the multi-panel format. Following is the script for the individual plots and the multi-panel:
Individual Plot:
NewDat [[60]]
EstRes <- NewDat [[60]]
EstResPlt = ggplot(EstRes,aes(Distance3, `newBa`))+geom_line() + scale_x_continuous(n.breaks = 10, limits = c(0, 3500))+ scale_y_continuous(n.breaks = 10, limits = c(0,25))+ xlab("Distance from Core (μm)") + ylab("Ba:Ca concentration(μmol:mol)") + geom_hline(yintercept=2.25, linetype="dashed", color = "red")+ geom_vline(xintercept = 1193.9, linetype="dashed", color = "grey")+ geom_vline(xintercept = 1965.5, linetype="dashed", color = "grey") + geom_vline(xintercept = 2616.9, linetype="dashed", color = "grey") + geom_vline(xintercept = 3202.8, linetype="dashed", color = "grey")+ geom_vline(xintercept = 3698.9, linetype="dashed", color = "grey")
EstResPlt
Multi-panel plot:
MultiP <- grid.arrange(MigrPlt,OcResPlt,EstResPlt, nrow =1)
I have attempted to include:
MultiP <- grid.arrange(MigrPlt,OcResPlt,EstResPlt, nrow =1)+
theme(axis.text.x = element_text (angle = 45)) )
MultiP
but have only received errors. It's not necessary for all tick marks to be included. An initial, mid and end value is sufficient and therefore they would not need to all be included or angled. I'm just not sure how to do this. Assistance would be much appreciated.
There are several options to resolve the crowded axes. Let's consider the following example which parallels your case. The default labelling strategy wouldn't overcrowd the x-axis.
library(ggplot2)
library(patchwork)
library(scales)
df <- data.frame(
x = seq(0, 3200, by = 20),
y = cumsum(rnorm(161))
)
p <- ggplot(df, aes(x, y)) +
geom_line()
(p + p + p) / p &
scale_x_continuous(
name = "Distance (um)"
)
However, because you've given n.breaks = 10 to the scale, it becomes crowded. So a simple solution would just be to remove that.
(p + p + p) / p &
scale_x_continuous(
n.breaks = 10,
name = "Distance (um)"
)
Alternatively, you could convert the micrometers to millimeters, which makes the labels less wide.
(p + p + p) / p &
scale_x_continuous(
n.breaks = 10,
labels = label_number(scale = 1e-3, accuracy = 0.1),
name = "Distance (mm)"
)
Yet another alternative is to put breaks only every n units, in the case below, a 1000. This happens to coincide with omitting n.breaks = 10 by chance.
(p + p + p) / p &
scale_x_continuous(
breaks = breaks_width(1000),
name = "Distance (um)"
)
Created on 2021-11-02 by the reprex package (v2.0.1)
I thought it would be better to show with an example.
What I mean was, you made MigrPlt, OcResPlt, EstResPlt each with ggplot() +...... For plot that you want to rotate x axis, add + theme(axis.text.x = element_text (angle = 45)).
For example, in iris data, only rotate x axis text for a like
a <- ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
geom_point() +
theme(axis.text.x = element_text (angle = 45))
b <- ggplot(iris, aes(Petal.Width, Petal.Length)) +
geom_point()
gridExtra::grid.arrange(a,b, nrow = 1)
This is my first question here so hope this makes sense and thank you for your time in advance!
I am trying to generate a scatterplot with the data points being the log2 expression values of genes from 2 treatments from an RNA-Seq data set. With this code I have generated the plot below:
ggplot(control, aes(x=log2_iFGFR1_uninduced, y=log2_iFGFR4_uninduced)) +
geom_point(shape = 21, color = "black", fill = "gray70") +
ggtitle("Uninduced iFGFR1 vs Uninduced iFGFR4 ") +
xlab("Uninduced iFGFR1") +
ylab("Uninduced iFGFR4") +
scale_y_continuous(breaks = seq(-15,15,by = 1)) +
scale_x_continuous(breaks = seq(-15,15,by = 1)) +
geom_abline(intercept = 1, slope = 1, color="blue", size = 1) +
geom_abline(intercept = 0, slope = 1, colour = "black", size = 1) +
geom_abline(intercept = -1, slope = 1, colour = "red", size = 1) +
theme_classic() +
theme(plot.title = element_text(hjust=0.5))
Current scatterplot:
However, I would like to change the background of the plot below the red line to a lighter red and above the blue line to a lighter blue, but still being able to see the data points in these regions. I have tried so far by using polygons in the code below.
pol1 <- data.frame(x = c(-14, 15, 15), y = c(-15, -15, 14))
pol2 <- data.frame(x = c(-15, -15, 14), y = c(-14, 15, 15))
ggplot(control, aes(x=log2_iFGFR1_uninduced, y=log2_iFGFR4_uninduced)) +
geom_point(shape = 21, color = "black", fill = "gray70") +
ggtitle("Uninduced iFGFR1 vs Uninduced iFGFR4 ") +
xlab("Uninduced iFGFR1") +
ylab("Uninduced iFGFR4") +
scale_y_continuous(breaks = seq(-15,15,by = 1)) +
scale_x_continuous(breaks = seq(-15,15,by = 1)) +
geom_polygon(data = pol1, aes(x = x, y = y), color ="pink1") +
geom_polygon(data = pol2, aes(x = x, y = y), color ="powderblue") +
geom_abline(intercept = 1, slope = 1, color="blue", size = 1) +
geom_abline(intercept = 0, slope = 1, colour = "black", size = 1) +
geom_abline(intercept = -1, slope = 1, colour = "red", size = 1) +
theme_classic() +
theme(plot.title = element_text(hjust=0.5))
New scatterplot:
However, these polygons hide my data points in this area and I don't know how to keep the polygon color but see the data points as well. I have also tried adding "fill = NA" to the geom_polygon code but this makes the area white and only keeps a colored border. Also, these polygons shift my axis limits so how do I change the axes to begin at -15 and end at 15 rather than having that extra unwanted length?
Any help would be massively appreciated as I have struggled with this for a while now and asked friends and colleagues who were unable to help.
Thanks,
Liv
Your question has two parts, so I'll answer each in turn using a dummy dataset:
df <- data.frame(x=rnorm(20,5,1), y=rnorm(20,5,1))
Stop geom_polygon from hiding geom_point
Stefan had commented with the answer to this one. Here's an illustration. Order of operations matters in ggplot. The plot you create is a result of each geom (drawing operation) performed in sequence. In your case, you have geom_polygon after geom_point, so it means that it will plot on top of geom_point. To have the points plotted on top of the polygons, just have geom_point happen after geom_polygon. Here's an illustrative example:
p <- ggplot(df, aes(x,y)) + theme_bw()
p + geom_point() + xlim(0,10) + ylim(0,10)
Now if we add a geom_rect after, it hides the points:
p + geom_point() +
geom_rect(ymin=0, ymax=5, xmin=0, xmax=5, fill='lightblue') +
xlim(0,10) + ylim(0,10)
The way to prevent that is to just reverse the order of geom_point and geom_rect. It works this way for all geoms.
p + geom_rect(ymin=0, ymax=5, xmin=0, xmax=5, fill='lightblue') +
geom_point() +
xlim(0,10) + ylim(0,10)
Removing whitespace between the axis and limits of the axis
The second part of your question asks about how to remove the white space between the edges of your geom_polygon and the axes. Notice how I have been using xlim and ylim to set limits? It is a shortcut for scale_x_continuous(limits=...) and scale_y_continuous(limits=...); however, we can use the argument expand= within scale_... functions to set how far to "expand" the plot before reaching the axis. You can set the expand setting for upper and lower axis limits independently, which is why this argument expects a two-component number vector, similar to the limits= argument.
Here's how to remove that whitespace:
p + geom_rect(ymin=0, ymax=5, xmin=0, xmax=5, fill='lightblue') +
geom_point() +
scale_x_continuous(limits=c(0,10), expand=c(0,0)) +
scale_y_continuous(limits=c(0,10), expand=c(0,0))
I have a graph made in ggplot that looks like this:
I wish to have the numeric labels at each of the bars to be grounded/glued to the x axis where y <= 0.
This is the code to generate the graph as such:
ggplot(data=df) +
geom_bar(aes(x=row, y=numofpics, fill = crop, group = 1), stat='identity') +
geom_point(data=df, aes(x = df$row, y=df$numofparcels*50, group = 2), alpha = 0.25) +
geom_line(data=df, aes(x = df$row, y=df$numofparcels*50, group = 2), alpha = 0.25) +
geom_text(aes(x=row, y=numofpics, label=bbch)) +
geom_hline(yintercept=300, linetype="dashed", color = "red", size=1) +
scale_y_continuous(sec.axis= sec_axis(~./50, name="Number of Parcels")) +
scale_x_discrete(name = c(),breaks = unique(df$crop), labels = as.character(unique(df$crop)))+
labs(x=c(), y="Number of Pictures")
I've tried vjust and experimenting with position_nudge for the geom_text element, but every solution I can find changes the position of each element of the geom_text respective to its current position. As such everything I try results in situation like this one:
How can I make ggplot ground the text to the bottom of the x axis where y <= 0, possibly with the possibility to also introduce a angle = 45?
Link to dataframe = https://drive.google.com/file/d/1b-5AfBECap3TZjlpLhl1m3v74Lept2em/view?usp=sharing
As I said in the comments, just set the y-coordinate of the text to 0 or below, and specify the angle : geom_text(aes(x=row, y=-100, label=bbch), angle=45)
I'm behind a proxy server that blocks connections to google drive so I can't access your data. I'm not able to test this, but I would introduce a new label field in my dataset that sets y to be 0 if y<0:
df <- df %>%
mutate(labelField = if_else(numofpics<0, 0, numofpics)
I would then use this label field in my geom_text call:
geom_text(aes(x=row, y=labelField, label=bbch), angle = 45)
Hope that helps.
You can simply define the y-value in geom_text (e.g. -50)
ggplot(data=df) +
geom_bar(aes(x=row, y=numofpics, fill = crop, group = 1), stat='identity') +
geom_point(data=df, aes(x = df$row, y=df$numofparcels*50, group = 2), alpha = 0.25) +
geom_line(data=df, aes(x = df$row, y=df$numofparcels*50, group = 2), alpha = 0.25) +
geom_text(aes(x=row, y=-50, label=bbch)) +
geom_hline(yintercept=300, linetype="dashed", color = "red", size=1) +
scale_y_continuous(sec.axis= sec_axis(~./50, name="Number of Parcels")) +
scale_x_discrete(name = c(),breaks = unique(df$crop), labels =
as.character(unique(df$crop)))+
labs(x=c(), y="Number of Pictures")