#ggplot — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #ggplot, aggregated by home.social.
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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3D ggplot of parabolic great circle trajectories (i.e. ballistic-ish paths) on a non-linear Robinson projection: how do we ensure the 3D data is consistent with the underlying ggplot? Simple: we extract the coordinate transformation from the ggplot object itself!
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Add some swag to your ggplots, with fontawesome symbols and colors: https://nrennie.rbind.io/blog/adding-social-media-icons-ggplot2/ #rstats #ggplot #fontawesome #ggtext
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Hey #spatial #R folks, is it possible to extract geometries from #ggplot as files? That is, the point, line, and polygon geometries in the graphs to #geopackage or #shapefile etc.
It is possible with #seaborn and #matplotlib, but that's Python not R. There's a nice and lightning fast #EdgeBundling technique in the newest ggplot, which is very promising for the #visualization of massive #mobility data.
There is also something in #HoloViews but I do not understand that library at all.