R bloggers

New features in {overviewR}

April 23, 2022 | R-post on Cosima Meyer

overviewR (v 0.0.10) is on CRAN and comes with new features 🚀 The package is meant to serve as a Swiss army knife for exploratory data analysis. The basic functions allow you to investigate sample coverage across different time points, missing values a...
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New features in {overviewR}

April 23, 2022 | R-post on Cosima Meyer

overviewR (v 0.0.10) is on CRAN and comes with new features 🚀 The package is meant to serve as a Swiss army knife for exploratory data analysis. The basic functions allow you to investigate sample coverage across different time points, missing values a... [Read more...]

New features in {overviewR}

April 23, 2022 | R-post on Cosima Meyer

overviewR (v 0.0.10) is on CRAN and comes with new features 🚀 The package is meant to serve as a Swiss army knife for exploratory data analysis. The basic functions allow you to investigate sample coverage across different time points, missing values a... [Read more...]

Where for (loop) ARt Thou?

April 21, 2022 | Jonathan Carroll

I’ve long been interested in exactly how R works - not quite enough for me to learn all the internals, but I was surprised that I could not find a clear guide towards exactly how vectorization works at the deepest level. Let’s say we want to add two ... [Read more...]

Shiny Workshops and Tutorials – Appsilon Shiny Conference

April 21, 2022 | Appsilon

The Appsilon Shiny Conference begins next week! And yes, there’s still time to register at the Shiny Conference Hopin! Whether a Shiny beginner or an experienced web developer, the Shiny Conference is one event you won’t want to miss. Level up your domain knowledge with introductory workshops and ...
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Loading a large, messy csv using data.table fread with cli tools

April 20, 2022 | R on Redwall Analytics

Setup
library(data.table)
library(here)
## here() starts at /Users/davidlucey/Desktop/David/Projects/redwall-analytics
library(glue)
## Warning: package 'glue' was built under R version 4.1.2
library(tictoc)
setDTthreads(percent = 90)
path_to_data <- "~/Desktop/David/Projects/uscompanies/data"
path_to_original <- here::here(path_to_data, "uscompanieslist.csv")
Introduction On a recent side project, we encountered a large (7GB) csv of 30+ million US business names and addresses, which couldn’t be loaded into R, because of corrupted records. While not widely discussed, we have known for some time that it was possible ...
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riddle of the week

April 20, 2022 | xi'an

The Riddler of April 1 offered this simple question: start with the number 1 and then try to reach a target number through a series of steps. For each step, you can always choose to double the number you currently have. However, if the number happens to be one (1) more than an ... [Read more...]
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