Problems with `ggplot2` when adding multiple facets on a time series plot
I'm trying to debug I'm working on a personal project and I'm having trouble creating a time series plot using `ggplot2` where I want to facet the data by multiple categorical variables... My dataset is structured with columns for `date`, `value`, `category1`, and `category2`. I've attempted to use `facet_grid()` to create a grid layout for my facets, but I'm running into issues where the plots do not appear correctly, and sometimes I receive the warning: `Removed 10 rows containing missing values (geom_path)`. Here’s a simplified version of my code: ```r library(ggplot2) # Sample data frame df <- data.frame( date = rep(seq.Date(from = as.Date('2020-01-01'), to = as.Date('2020-01-10'), by = 'day'), 2), value = c(1:10, NA, 12:19), # Introduced an NA for demonstration category1 = rep(c('A', 'B'), each = 10), category2 = rep(c('X', 'Y'), 10) ) # Attempting to create the plot ggplot(df, aes(x = date, y = value)) + geom_line() + facet_grid(category1 ~ category2) ``` The warning about removed rows is expected, but it seems like the plot is not displaying the expected facets for `category1` and `category2`. Is there a better way to enhance this plot or any specific practices to avoid these issues? Also, I would appreciate any advice regarding handling missing values in this context, as I want to keep the visualization clean and informative. I'm using `ggplot2` version 3.3.5 with R version 4.1.1. For context: I'm using R on Windows. Thanks in advance! This is part of a larger service I'm building. Am I missing something obvious? This is happening in both development and production on Linux.