Let’s assume your file is one of these types:
Assuming installation eventually completes, runtime slowdowns are even more common. “Juniper Ren” might open R, load the dataset “26022025_data.csv” (26-Feb-2025 data), and find that every command takes seconds or minutes.
| Symptom | Likely Cause | Fix |
|--------|--------------|-----|
| read.csv() takes forever | Large file, no data type specification | Use data.table::fread() or vroom::vroom() |
| ggplot2 rendering lag | Too many points (~>100k) | Downsample or use scattermore or ggrastr |
| Slow loops | Using for loop in R | Vectorize or use Rcpp / furrr |
| Memory exhausted | Object too large | Use disk.frame or arrow; increase RAM limit with memory.limit() (Windows) |
| Garbage collection pauses | Frequent gc() or large object churn | Avoid explicit gc(); let R manage memory |
