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 dplyr.tidyverse.org
Group by one or more variables - group_by dplyr
| | pillar.r-lib.org
Get a glimpse of your data - glimpse pillar
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| | glimpse() is like a transposed version of print(): columns run down the page, and data runs across. This makes it possible to see every column in a data frame. It's a little like str() applied to a data frame but it tries to show you as much data as possible. (And it always shows the underlying data, even when applied to a remote data source.) See format_glimpse() for details on the formatting.
| | tibble.tidyverse.org
Coerce lists, matrices, and more to data frames - as_tibble tibble
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| | as_tibble() turns an existing object, such as a data frame or matrix, into a so-called tibble, a data frame with class tbl_df. This is in contrast with tibble(), which builds a tibble from individual columns. as_tibble() is to tibble() as base::as.data.frame() is to base::data.frame(). as_tibble() is an S3 generic, with methods for: data.frame: Thin wrapper around the list method that implements tibble's treatment of rownames. matrix, poly, ts, table Default: Other inputs are first coerced with base::as....
| | magrittr.tidyverse.org
Introducing magrittr magrittr
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| | blog.quipu-strands.com
Bayesian Optimization, Part 2: Acquisition Functions
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| [AI summary] The text presents an extensive overview of Bayesian optimization techniques, focusing on their applications in black-box function optimization, including challenges and solutions such as computational efficiency, scalability, and integration with deep learning models. It also highlights key research contributions and references to seminal papers and authors in the field.