![]() Scale_y_continuous(sec.axis = sec_axis(~. ggplot(df2, aes(x = age, y = circumference)) + The vector of values matching the line ends determines the numbers to be displayed at breaks. Hypothesis Testing Examples-Quick Overview – Data Science Tutorials Key R functions: Using a supplementary y-axis to show the line labels To produce a second axis on the right, the ggplot2 scale y continuous() method is combined with the option sec.axis. plot2 %Īes(label = circumference), data = data_ends, Names_to = "variable", values_to = "value"Īdding labels to the line ends with ggrepelīasic line plot examples for the discrete x-axis plot% filter(Species = "virginica")įontface ="plain", color = "black", size = 3 How to make a rounded corner bar plot in R? – Data Science Tutorials df_long % We can now convert the data into a longer format. Set ggplot2 default theme to theme_bw() theme_set(theme_bw()) Geom_text repel() and geom_label repel() are geoms for ggplot2 that repel overlapping text_labels () Tidyverse: data visualization and manipulation made simple Test for Normal Distribution in R-Quick Guide – Data Science Tutorials R packages required: Using either the ggrepel text labeling or the ggplot2 secondary axis functions, many methods are shown. How to add labels at the end of each line in ggplot2?, Using the ggplot2 R library, this article shows how to display the last value of each line as a label. Label_df <- as.data.The post How to add labels at the end of each line in ggplot2? appeared first on # with a non-missing name, since these are the major county polygons.Ĭounty_centroids <- county_centroidsĬentroid_array <- Reduce(rbind, county_centroids)ĭimnames(centroid_array) <- list(gsub("*,", "", names(county_centroids)), # Create a data frame for graphing out of the centroids of each polygon # Use the map function to get the polygon data, then find the centroidsĬounty_poly <- map("county", "new york", plot=FALSE, fill = TRUE)Ĭounty_centroids <- maps:::apply.polygon(county_poly, maps:::centroid.polygon) These functions aren't visible when the package is loaded, but can still be accessed: library(ggplot2) library(maps) The function ggarrange () ggpubr is one of the easiest solution for arranging multiple ggplots. Looking at its code, one can see that it uses the apply.polygon and centroid.polygon functions to find the centroids. The maps package has the map.text function, which uses polygon centroids to place labels. I know this is an old question that's been answered, but I wanted to add this in case anyone looks here for future help. Geom_text(data=cnames, aes(long, lat, label = subregion), size=2) + Once you've done that, and the map plots, you'll realize that the midpoint is better approximated by the mean of range, and to use a map coordinate system that respects the aspect ratio and projection: cnames <- aggregate(cbind(long, lat) ~ subregion, data=ny,
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