Smooth Error in qplot from ggplot2 - r

I have some data that I am trying to plot faceted by its Type with a smooth (Loess, LM, whatever) superimposed. Generation code is below:
testFrame <- data.frame(Time=sample(20:60,50,replace=T),Dollars=round(runif(50,0,6)),Type=sample(c("First","Second","Third","Fourth"),50,replace=T,prob=c(.33,.01,.33,.33)))
I have no problem either making a faceted plot, or plotting the smooth, but I cannnot do both. The first three lines of code below work fine. The fourth line is where I have trouble:
qplot(Time,Dollars,data=testFrame,colour=Type)
qplot(Time,Dollars,data=testFrame,colour=Type) + geom_smooth()
qplot(Time,Dollars,data=testFrame) + facet_wrap(~Type)
qplot(Time,Dollars,data=testFrame) + facet_wrap(~Type) + geom_smooth()
It gives the following error:
Error in [<-.data.frame(*tmp*, var, value = list(NA = NULL)) :
missing values are not allowed in subscripted assignments of data frames
What am I missing to overlay a smooth in a faceted plot? I could have sworn I had done this before, possibly even with the same data.

It works for me. Are sure you have the latest version of ggplot2?

Related

stacked area plots ggplot

I was hoping someone might be able to help. I am still getting to grips with R and I am quite new to ggplot2.
My problem:
I am trying to make a stacked area plot. I have formatted my data frame so that it is in long format. My columns are Date, Category (filter.size) and value (chl.average).
e.g:
data frame example
The issue I am having is that when I try and plot this, where Chlstacked is my data.frame):
stkchl <- ggplot(Chlstacked, aes(x=Date, y=chl.average,
fill=filter.size)) + geom_area()
stkchl
the axis and background layer plots but not the actual stack, although it recognises the categories in a legend with colours.
I have tried and alternate method:
stkchl <- ggplot(Chlstacked, aes(x=Date, y=chl.average))
stkchl
stkchl + geom_area(aes(colour = chl.average, fill= chl.average),
position = 'stack')
Which gives: Error in f(...) : Aesthetics can not vary with a ribbon
My thought is that perhaps as the Dates, which I would want on the x-axis (as it is time series), are repeated for each category (>20, <20>5, <5>GFF) they are not unique so maybe doing something - altough I am stumped as to what - to cause error.Or perhaps something simple that I am doing wrong within my coding?
Any help would be appreciated - thanks

How to make ggplot2 run with 2 layers?

Here's my code:
tmp <- data.frame(t_year = rnorm(100,0,1),
labs = c(rep("Linear",50), rep("Spline",50)),
STUDY_PARTICIPANT_ID = rep(seq(1,50),2),
logpsa = rnorm(100,0.5,1),
mypredict = rnorm(100,1,2))
p <- ggplot(tmp) +
geom_line(aes(t_year,
mypredict,
group = as.factor(labs),
color = as.factor(labs))) +
geom_line(aes(t_year,
logpsa,
group = STUDY_PARTICIPANT_ID,
color = STUDY_PARTICIPANT_ID))
It only runs with either one of the geom_line(), but it doesn't when I tried to plot both. I was hoping it would treat them separately, but I don't think that's the case. Does anyone have any suggestion? I originally used geom_smooth() for the fitted lines, but I was unable to add a legend at the side of the ggplot. Therefore, I got the fitted values and put them in the dataset and was just going to plot them with geom_line(). All I wanted was just a label for my linear fit line and my spline. The data here doesn't show the trend, but it will give you the error messages that I was getting. Thank you for your patience with my first post.

Error message: negative extents to matrix

I'm trying to make a density plot in R, using ggplot. I am able to get the axes and the points plotted, but no density. I am fairly unfamiliar with ggplot, as a side note. But my z-axis is just a list of values and what shows up when I plot it is just a plot of dots. How do I incorporate the density?
An error that pops up says there are "negative extents to matrix." I've tried searching for this, but no luck.
This is my code:
ggplot(data=Denit, aes(x=Date, y=Depth, z=N2.excess)) +
geom_point() +
stat_density2d(data=Denit, aes(x=Date, y=Depth, z=N2.excess))

Position-dodge warning with ggplot boxplot?

I'm trying to make a boxplot with ggplot2 using the following code:
p <- ggplot(
data,
aes(d$score, reorder(d$names d$scores, median))
) +
geom_boxplot()
I have factors called names and integers called scores.
My code produces a plot, but the graphic does not depict the boxes (only shows lines) and I get a warning message, "position_dodge requires non-overlapping x intervals." I've tried to adjust the height and width with geom_boxplot(width=5), but this does not seem to fix the problem. Can anyone suggest a possible solution to my problem?
I should point out that my boxplot is rather large and has about 200 name values on the y-axis). Perhaps this is the problem?
The number of groups is not the problem; I can see the same thing even when there are only 2 groups. The issue is that ggplot2 draws boxplots vertically (continuous along y, categorical along x) and you are trying to draw them horizontally (continuous along x, categorical along y).
Also, your example has several syntax errors and isn't reproducible because we don't have data/d.
Start with some mock data
dat <- data.frame(scores=rnorm(1000,sd=500),
names=sample(LETTERS, 1000, replace=TRUE))
Corrected version of your example code:
ggplot(dat, aes(scores, reorder(names, scores, median))) + geom_boxplot()
This is the horizontal lines you saw.
If you instead put the categorical on the x axis and the continuous on the y you get
ggplot(dat, aes(reorder(names, scores, median), scores)) + geom_boxplot()
Finally, if you want to flip the coordinate axes, you can use coord_flip(). There can be some additional problems with this if you are doing even more sophisticated things, but for basic boxplots it works.
ggplot(dat, aes(reorder(names, scores, median), scores)) +
geom_boxplot() + coord_flip()
In case anyone else arrives here wondering why they're seeing
Warning message:
position_dodge requires non-overlapping x intervals
Why this happens
The reason this happens is because some of the boxplot / violin plot (or other plot type) are possibly overlapping. In many cases, you may not care, but in some cases, it matters, hence why it warns you.
How to fix it
You have two options. Either suppress warnings when generating/printing the ggplot
The other option, simply alter the width of the plot so that the plots don't overlap, then the warning goes away. Try altering the width argument to the geom: e.g. geom_boxplot(width = 0.5) (same works for geom_violin())
In addition to #stevec's options, if you're seeing
position_stack requires non-overlapping x intervals
position_fill requires non-overlapping x intervals
position_dodge requires non-overlapping x intervals
position_dodge2 requires non-overlapping x intervals
and if your x variable is supposed to overlap for different aesthetics such as fill, you can try making the x_var into a factor:
geom_bar(aes(x = factor(x_var), fill = type)

Barplot Error in R using ggplot

I try to make a barplot of a time-series dataset with ggplot2 but I get following error message (I have performed this on a similar dataset and it works):
Error in if (!is.null(data$ymin) && !all(data$ymin == 0)) warning("Stacking not well defined when ymin != 0", : missing value where TRUE/FALSE needed
For this I have used following code:
p <- ggplot(dataset, aes(x=date, y=value)) + geom_bar(stat="identity")
If I use geom_point() instead of geom_bar() it works fine.
You haven't provided a reproducible example, so I'm just guessing, but your syntax doesn't look right to me. Check here: http://docs.ggplot2.org/current/geom_bar.html
Bar charts by default produce tabulations of counts:
p <- ggplot( dataset, aes( factor(date) ) ) + geom_bar()
If you want it to do something different, you'll need to tell it what statistic to use. See the link above (towards the bottom) for an example using the mean. Alternatively, see here for a hybrid point/scatterplot (very bottom of the page):
http://docs.ggplot2.org/current/position_jitter.html
But fundamentally you have two continuous variables and it's not clear to me why you'd want anything but a scatterplot.

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