advanced patterns using `facet_wrap()` with a large dataset in ggplot2
I'm upgrading from an older version and I'm trying to implement I've been researching this but I'm working with a fairly large dataset (around 50,000 rows) in R, and I'm trying to create a series of plots using `ggplot2` with `facet_wrap()`. My intention is to visualize the distribution of a numeric variable across multiple categories. However, when I apply `facet_wrap()`, I notice that it doesn't seem to handle the large dataset properly, resulting in either blank plots or only a subset of the data being displayed. Specifically, I'm using the following code: ```R library(ggplot2) df <- data.frame( category = rep(letters[1:10], each = 5000), value = rnorm(50000) ) p <- ggplot(df, aes(x = value)) + geom_histogram(binwidth = 0.5) + facet_wrap(~ category) print(p) ``` When running this code, I get unexpected empty facets for some categories, and for others, the distribution doesn't seem to reflect the data accurately. I've tried reducing the dataset size to 10,000 rows, and it works fine, but I need it to handle the full dataset efficiently. Is there a limitation with `facet_wrap()` when it comes to larger datasets? I also checked my `ggplot2` version, which is 3.3.5, and Iām running R version 4.1.0. I've also attempted to use `geom_density()` instead of `geom_histogram()`, but the same scenario continues. Any insights on how to tackle this would be greatly appreciated! I'm working with R in a Docker container on macOS. What am I doing wrong? I'm on Windows 10 using the latest version of R. I recently upgraded to R 3.11. The project is a CLI tool built with R. Is there a better approach?