I'm trying to get a graph like this to show boxplot distributions for each age group:
But instead my plot looks like this:
How can I get the boxplots to show rather than the points? Why is my Y axis non numeric?
My data looks like this:
And here's the plot code I am trying:
p2 <- ggplot(data = popSample, aes(x = AGEGRP, y = TOT_POP)) +
geom_boxplot(aes(group = AGEGRP)) +
scale_x_discrete() +
theme_light()
p2
Thank you for helping someone who is learning,
Related
I am trying to plot my data using ggplot and geomline in R studio but somehow the plot is not looking right. This is my sample data:
Sample data
Here is the code:
ggplot()+
geom_line(data = data_south, mapping = aes(x = Month, y = Tempture), color="blue")
This is the output I am getting:
But this plot is not looking right. The lines are supposed to be connected and also why there are straight lines in the plot?
I want to draw a combined bar plot, so that I can make comparision among different score types.
compare_data = data.frame(model=c(lr,rf,gbm,xgboost),
precision=c(0.6593,0.7588,0.6510,0.7344),
recall=c(0.5808,0.6306,0.4897,0.6416),f1=c(0.6176,0.6888,0.5589,0.6848),
acuracy=c(0.6766,0.7393,0.6453,0.7328))
compare1 <- ggplot(evaluation_4model, aes(x=Model, y=Precision)) +
geom_bar(aes(fill = Model), stat="identity")
compare1 <- compare+labs(title = "Precision")
Here is one of the barplot I draw, and this is the type of "precision", however, I want to make a wide bar plot, with all the models under 4 score types sharing the same Y-axis, also with subtitle if possible.
Your code throws an error, because evaluation_4model is not defined.
However, the answer to your problem is likely to make a faceted plot and hence melt the data to a long format. To do this, I usually make use of the reshape library. Tweaking your code looks like this
library(ggplot2)
library(reshape2)
compare_data = data.frame(model=c("lr","rf","gbm","xgboost"),
precision=c(0.6593,0.7588,0.6510,0.7344),
recall=c(0.5808,0.6306,0.4897,0.6416),
f1=c(0.6176,0.6888,0.5589,0.6848),
acuracy=c(0.6766,0.7393,0.6453,0.7328))
plotdata <- melt(compare_data,id.vars = "model")
compare2 <- ggplot(plotdata, aes(x=model, y=value)) +
geom_bar(aes(fill = model), stat="identity")+
facet_grid(~variable)
compare2
does that help?
I want to plot a segmented bar plot in ggplot2. Here is part of my dataframe, I want to plot the proportion of output(0 and 1) for each x1(0 and 1). But when I use the following code, what I plot is just black bars without any segmentation. What's the problem in here?
fig = ggplot(data=df, mapping=aes(x=x1, fill=output)) + geom_bar(stat="count", width=0.5, position='fill')
The output plot is here
You need factor variables for your task:
library(ggplot2)
df <- data.frame(x1=sample(0:1,100,replace = T),output=sample(0:1,100,replace = T))
ggplot(data = df, aes(x = as.factor(x1), fill = as.factor(output))) +
geom_histogram(stat = "count")+
labs(x="x11")
which give me:
I would like a plot that looks like this:
Using ggplot. The one above was made from heatscatter in the LSD package.
I tried using this code:
p = ggplot(data = emr.ext.melt, aes(Date,NDVI))
p + geom_point() + stat_density2d(aes(fill=..level..), geom="polygon") +
scale_fill_gradient(low="blue", high="green")+ scale_y_continuous(limits = c(-1, 1))
But, got this weird plot. I just want a scatter plot colored based on the density of points for that given day. I do not want to use hexplot either.
Thank you for your help!
I'm struggling with facet_wrap in R. It should be simple however the facet variable is not being picked up? Here is what I'm running:
plot = ggplot(data = item.household.descr.count, mapping = aes(x=item.household.descr.count$freq, y = item.household.descr.count$descr, color = item.household.descr.count$age.cat)) + geom_point()
plot = plot + facet_wrap(~ age.cat, ncol = 2)
plot
I colored the faceting variable to try to help illustrate what is going on. The plot should have only one color in each facet instead of what you see here. Does anyone know what is going on?
This error is caused by fact that you are using $and data frame name to refer to your variables inside the aes(). Using ggplot() you should only use variables names in aes() as data frame is named already in data=.
plot = ggplot(data = item.household.descr.count,
mapping = aes(x=freq, y = descr, color = age.cat)) + geom_point()
plot = plot + facet_wrap(~ age.cat, ncol = 2)
plot
Here is an example using diamonds dataset.
diamonds2<-diamonds[sample(nrow(diamonds),1000),]
ggplot(diamonds2,aes(diamonds2$carat,diamonds2$price,color=diamonds2$color))+geom_point()+
facet_wrap(~color)
ggplot(diamonds2,aes(carat,price,color=color))+geom_point()+
facet_wrap(~color)