Multiple use of the positional `$` operator to update nested arrays

by

The positional operator only supports one level deep and only the first matching element.

There is a JIRA trackable for the sort of behaviour you want here: https://jira.mongodb.org/browse/SERVER-831

I am unsure if it will allow for more than one match but I believe it will due to the dynamics of how it will need to work.

More Related Contents:

  1. Is there a dplyr equivalent to data.table::rleid?
  2. ggplot2 – bar plot with both stack and dodge
  3. `levels
  4. Getting path of an R script
  5. Difference: “Compile PDF” button in RStudio vs. knit() and knit2pdf()
  6. Rotating x axis labels in R for barplot
  7. Adaptive moving average – top performance in R
  8. How to work with large numbers in R?
  9. R suppress startupMessages from dependency
  10. How can I get the average (mean) of selected columns
  11. A matrix version of cor.test()
  12. Use stat_summary to annotate plot with number of observations
  13. Finding 2 & 3 word Phrases Using R TM Package
  14. Remove grid, background color, and top and right borders from ggplot2
  15. Milliseconds in POSIXct Class
  16. How to access and edit Rprofile? [closed]
  17. heatmap with values (ggplot2)
  18. How to choose variable to display in tooltip when using ggplotly?
  19. Using different scales as fill based on factor
  20. Conditional binary join and update by reference using the data.table package
  21. How to read csv file in R where some values contain the percent symbol (%)
  22. When should I use setDT() instead of data.table() to create a data.table?
  23. Remove duplicates based on 2nd column condition
  24. Get date difference in years (floating point)
  25. Numbers as column names of data frames
  26. In R, how can I check if two variable names reference the same underlying object?
  27. How to pass “nothing” as an argument to `[` for subsetting?
  28. Harnessing .f list names with purrr::pmap
  29. Spacing between boxplots in ggplot2
  30. Recommended package for very large dataset processing and machine learning in R [closed]

Leave a Comment