Zelazny7
Re:Deep Graph Library: Easy Deep Learning on Graphs
on Tuesday December 22, 2020 @09:01PM (#25513601)
fraud detection
Re:DuckDB now has a Node.js API
on Wednesday December 09, 2020 @07:32AM (#25357858)
Have you figured out a way to add columns to DuckDB from R vectors? I'm not sure this is possible yet without using inefficient insert operations. Ideally, I'd like to pull in some columns from the DB, generate a new column vector and store it back in the DB by adding a column to an existing table.
Re:Rsuite – R development and data science platform
on Saturday December 14, 2019 @06:51PM (#21793268)
when indexing you can always pass `drop=FALSE` to prevent returning a vector. It will always return a matrix or data.frame.
Re:Rsuite – R development and data science platform
on Saturday December 14, 2019 @06:50PM (#21793258)
Base R is fine. I would much rather not include the tidyverse and all of its transitive dependencies.
Re:Rsuite – R development and data science platform
on Saturday December 14, 2019 @06:47PM (#21793242)
options(error=recover)
Re:An opinionated view of the Tidyverse “dialect” of the R language
on Saturday July 06, 2019 @06:25PM (#20372402)
Yeah, that's a valid point. And it took me a couple years to internalize these differences -- mostly by being burned on numerous occasions. Base R has a lot of idiosyncrasies and they have to be memorized, unfortunately.
I develop R packages for my colleagues and so I stick to Base R whenever possible. I don't want my packages depending on the tidyverse at all. But for EDA, I am agnostic about what my colleagues do. They should use the tools that stay out of the way and let them get their hands around the dataset intuitively. For me that's Base R, for others it's data.table or tidyverse.
Re:An opinionated view of the Tidyverse “dialect” of the R language
on Saturday July 06, 2019 @09:19AM (#20369513)
I use a simply device to keep these straight:
- (l)apply: List apply always returns a list
- (s)apply: simplify apply tries to return simplified result
- (v)apply: verify apply checks the return type conforms to user supplied example
- (m)apply: multiple apply applies FUN to multiple vectors
- (r)apply: recursive apply is essentially a flatmap
- apply : no device here, only use on matrices, never data.frames