I am not able to use formulas or quosures in filter expressions in dplyr.
a_table <- data_frame(key = rep(letters[1:2], each = 2),
value = replace(runif(4), mod(1:4, 2) == 1, NA))
a_cond <- quo(not(is.na(value)))
filter(a_table, !!a_cond)
Yields the error
Error in filter_impl(.data, dots) : invalid argument type
I have read the vignettes on NSE and dplyr programming, and tried different calls to this:
a_cond <- interp(~not(is.na(value_)), value_ = as.name("value"))
But haven't really nailed it.
Thank you for your help.
The Session Info is:
> sessionInfo()
R version 3.4.2 (2017-09-28)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 17.10
other attached packages:
[1] rlang_0.1.1 readxl_1.0.0 aws.s3_0.3.3 magrittr_1.5
[5] dplyr_0.5.0 ggplot2_2.2.1 tidyr_0.6.1 dtplyr_0.0.2
[9] lazyeval_0.2.0 purrr_0.2.2.2 data.table_1.10.4 feather_0.3.1
[13] readr_1.1.0 lubridate_1.6.0 stringr_1.2.0
To solve the quosures issue, I had to update with install_github instead of update.packages.
This didn't solve the issue with formulas based on lazyeval::interp(), though.
For this to work, I figured out how to make the equivalent with quosures as well. Instead of
interp(~!is.na(value_), value_ = as.name("value"))
I did
quo(!is.na( !!sym("value") ))
And now all works as it should.
Cheers.