Also, if you digitize Bjorn's data, the least-squares regression has a p-value of 0.22 and a standard error of 0.15 (on a slope of 0.19), so the regression does not seem to be statistically significant. But none of that makes PlotLabel -> "Lomborg is a Fraud" any less funny.

In my classes I use @Mathematica to simulate and plot a standard Cauchy distribution for increasingly greater sample sizes (10^i for i from 1 to 6): Table[ListPlot[RandomVariate[CauchyDistribution[], 10^i], Filling->0, PlotLabel->”10^”~~ToString[i], {i, 1, 6}].

View the count of π digits word cloud animation... Animate[WordCloud[First[RealDigits[N[Pi, seq]]], PlotLabel -> Row[{seq, " \[Pi] digits count"}], ImageSize -> 400], {seq, 5, 100000, 100}] #math #WolframLanguage #WolfLang

Assigning X and Y label to a plot in Matplotlib Python #aipython #ai #python #matplotlib #matplotlibpyplot #pythonprogramming #pythons #pythonlearning #IDE #plotlabel #label #labels #datavisualization #datascience #plot

@wolframtap (* Easy GIS in #WolframLanguage *) GeoListPlot[#, PlotLabel -> #["Image"]] &[=["Sagrada Família"]]

Graph layouts on curves: Table[PathGraph[Range[20], GraphLayout -> l, PlotLabel -> l], {l, {"CircularEmbedding", "SpiralEmbedding"}}]

Custom dynamic interface with SetterBar: Dynamic[Plot[Sin[n x], {x, 0, 2 Pi}, PlotLabel -> SetterBar[Dynamic[n], Range[10]]]]