However it is perfectly possible to overlay two different layers that draw on separate data from separate data.frames. You might find a datafile something like this: Sample Time(1min) Time(2min) A 54 23 B 45 43 C 33 23 D 11 12 The model formula desired would be something like So if this was a times series we would write (Height~Years) or if it was drug response we might write (Height~Dose). To get shapefiles into a format that can be plotted we have to use the fortify() function.
It starts off looking like this > head(mydata) POSITION W_MEAN T_MEAN W_STDEV T_STDEV COUNT POSCAT 1 1 108.36 109.37 5.02 4.61 117 START 2 2 107.31 109.32 4.50 3.67 167 START The following example is adapted from the reshape2 paper in the Journal of Statistical Software. Join them; it only takes a minute: Sign up “Error: No layers in plot” when using ggplot up vote 3 down vote favorite 2 I got a simple data.frame (AD0) with What's the difference between /tmp and /run?
Personal Open source Business Explore Sign up Sign in Pricing Blog Support Search GitHub This repository Watch 65 Star 228 Fork 184 Robinlovelace/Creating-maps-in-R Code Issues 1 Pull requests 0 Projects sport.f <- fortify(sport, region = "ons_label") This step has lost the attribute information associated with the sport object. You can directly plot it without saving it as object on adding this option.
Also note how the aes() components can be combined into one set of brackets after ggplot, that has relevance for all layers, rather than being broken into separate parts as we ggplot(data = plot.data, aes(x = long, y = lat, fill = value, group = group)) + geom_polygon() + geom_path(colour="grey", lwd=0.1) + coord_equal() + facet_wrap(~variable) Again there is a lot going on p+geom_point(aes(colour=Partic_Per, size=Pop_2001)) The real power of ggplot2 lies in its ability to add layers to a plot. Error Could Not Find Function Multiplot The full documentation for it can be found online and it is recommended you test out the examples on your own machines and play with them: http://docs.ggplot2.org/current/ here is also a
Is it possible to have a planet unsuitable for agriculture? Error No Layers In Plot Ggplot2 This is similar to the 'qplot' command but the emphasis is more on building up layers of elements onto a plot. We recommend upgrading to the latest Safari, Google Chrome, or Firefox. The majority of R packages for now are full of code dependent upon base graphics but most new developers and new users are moving to ggplot2.
Let's take a look at the headings of sport, using the following command: names(sport) The data contained in spatial data are kept in a 'slot' that can be accessed using the Could Not Find Function Ggplot more stack exchange communities company blog Stack Exchange Inbox Reputation and Badges sign up log in tour help Tour Start here for a quick overview of the site Help Center Detailed The fortify function was written specifically for this purpose. Usually though it makes no diffrence here we plot reponse variable on the y-axis.
Create a boxplot of CD4 by GeneClass again faceted by Patient. How to write name with the letters in name? Error No Layers In Plot What is the weight that is used to balance an aircraft called? Error No Layers In Plot In R Again the legend is handled automatically.
Rotations of a number Hotel search engine that allows to search for rooms with a desk? If you want the bins (and therefore the bars) to be thinner (i.e. Not the answer you're looking for? We want it in long format so it looks like this: Sample Time Value A 1 54 A 2 23 B 1 45 B 2 43 C 1 33 C 2 Error No Layers In Plot Ggplot
Note that the y-axis label has been set to correspond to the input but like on the x-axis we can replace that if the variable name or subsetting is unhelpful using Indeed many other packages have been built that rely on ggplot2 to create complex novel graphics: colnums = c(2:5, 8) require(tabplot) tableplot(facs.df[, colnums], sortCol = "TotalT") require(GGally) ggpairs(facs.df[, colnums]) require(hexbin) qplot(CD8, The Statistic relates to plots where a summary of the data rather than the actual data is plotted. If your username is "username" and you saved the files into a folder called "rmapping" into your Desktop, for example, you would type the following: setwd("C:/Users/username/Desktop/rmapping/R") If you are working in
plot.data <- plot.data[order(plot.data$order), ] We can now use faceting to produce one map per year (this may take a little while to appear). Ggplot Env Is Missing The "polygons" slot contains the geometry of the polygons in the form of the XY coordinates used to draw the polygon outline. The possible combinations of plot and the many many different geoms available are far too many to detail here.
Browse other questions tagged r ggplot2 facet or ask your own question. To find out which ones these are we can select them (this is similar to what we covered in the previous session). There is a lot going on in the code above, so think about it line by line: what has each of the elements of code above has been designed to do. Discrete Value Supplied To Continuous Scale In the next tutorial we will return to the lm command both because it is both a really powerful function in itself but also because most of the other statistical methods
Join them; it only takes a minute: Sign up ggplot - error: no layers in plot up vote 0 down vote favorite I am having a real hard time with ggplot A more powerful way to read in geographical data is to use the rgdal function readOGR, which automatically extracts this information. What is the most expensive item I could buy with £50? or put parentheses around the whole expression to stop R interpreting the ggplot() call before you get a chance to add geoms to it. –Ben Bolker Dec 29 '13 at 23:42
ggplot2 is one of the best documented packages in R. Like the summary() function the plot() command is object oriented and will often create the correct default graph based on either the mode of the x and y variables or the Let's have a look at a quick example of ggplot2 in action using the convenience command qplot() which wraps up many ggplot2 features into a single step similar to the base