ggplot(pietable, aes("", P)) + geom_bar( stat = "identity", aes( fill = rev(fct_inorder(cluster))) + geom_label_repel( data = pietable[!P<1], aes( label = paste0(P, "%"), y = p1, #col = rev(fct_inorder(cluster)) ), point.padding = NA, max.overlaps = Inf, nud...
I'm beginning to think something as simple as toggling "legend" options in plotly's ggplot conversion is impossible. UPDATE #4: So I decided to approach this another way. Instead, I decided to change the variable names themselves. I would have done this from the start, except I wasn't...
ggplot2: Elegant Graphics for Data Analysis - ggplot2 Guide Data Science Ipython Notebooks, Scipy Lectures or Virgilio / GitHub - Learn DataScience Data Engineering Zoomcamp - Data Engineering Course Data Engineering Practice Problems - Data Engineering Practice Learn to Make Netflix Clone ▷ Da...
ggplot2: Elegant Graphics for Data Analysis - ggplot2 Guide Data Science Ipython Notebooks, Scipy Lectures or Virgilio / GitHub - Learn DataScience Data Engineering Zoomcamp - Data Engineering Course Data Engineering Practice Problems - Data Engineering Practice Learn to Make Netflix Clone ▷ Dat...
(State = reorder(State, Arrest)) %>% { ggplot(., aes(x = Arrest, y = State, fill = Arrest)) + geom_col() + scale_fill_gradient2( low = "#04e762", mid = "#f5b700", high = "#dc0073", midpoint = mean(.$Arrest) ) + theme_minimal() + theme(legend.position = "none"...