Help:Drawing graphs

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Question

How to draw graphs in Opasnet?

Answer

R-tools

In R-tools, you have the functionalities of R available. We recommend that you use the package ggplot2 whenever possible. It is very powerful, and borrowing good ideas from others is easier if we all use the same approach. Of course, it is also possible to use plot' (a kind of basic graph) as well, but the limits come sooner. This is an example code that contains all kinds of examples with comments.

+ Show code- Hide code library(OpasnetUtils) library(ggplot2) library(xtable) objects.get("QWYxSEJltnuTn0Xh") # data.time object from # http://fi.opasnet.org/fi_wiki/index.php?title=Talvivaaran_kaivoksen_mittauksia&oldid=16176 # data.time altiste <- "Ni" head(data.time) ggplot(data.time, aes(x = Paikka, y = pitoisuusResult, colour = pitoisuusResult)) + geom_point(size = 5) + # point size theme_grey(base_size = 24) + # font etc. http://sape.inf.usi.ch/quick-reference/ggplot2/themes labs( # label names title = paste(altiste, "Talvivaaran läheisyydessä"), y = paste("Pitoisuus,", data.time$pitoisuusUnit[1]), x = "Mittauspaikka" ) ########### Concentrations in time ggplot(data.time, aes(x = Aika, y = pitoisuusResult, colour = Paikka)) + geom_point(size = 5) + theme_grey(base_size = 24) + labs( title = paste(altiste, "Talvivaaran läheisyydessä"), y = paste("Pitoisuus,", data.time$pitoisuusUnit[1]), x = "Aika" ) # data from http://fi.opasnet.org/fi_wiki/index.php?title=Kivilajien_kemiallinen_koostumus&oldid=16183 objects.get("yRxoBZmZBL5GOP6D") head(data) nrow(data) ggplot(data[data$Observation == "Mean", ], aes(x = Element, y = Result, colour = Sequence)) + geom_point() + theme_grey(base_size = 20)

GoogleDocs

GoogleDocs is the method of choice for drawing causal diagrams.

• Make a drawing.
• Share it with everyone with open editing.
• Download is in png or svg format.
• Upload the file to Opasnet and copy a link to the original Google document to the image page.
• Use like any image.

See also

• Cookbook for R: Scatterplots
• Add a smoothed conditional mean
• theme_grey