1 Tiyverse 2 Style guide 3 Pipe %__% 4 Tidyverse packages 4.1 Read and write data 4.2 Character manipulations 4.3 Management of dates and times 4.4 Table and vector manipulation 4.4.1 Select and rename 4.4.2 Filter and sort 4.4.3 Group and summarize 4.4.4 Join tables 4.4.5 Long and wide tables 4.5 Visualize data 4.5.1 Line and scatter plot 4.5.2 Boxplot 4.5.3 Heatmap 4.6 Apply functions on vectors or lists 1 ...

[1] Last post ‘Still hand-crafting your Rdoc files?’ introduced package wyz.code.rdoc to produce R documentation file in a possibly fully automated way. Let’s see today, which production strategy will offer you the most powerful and productiv...

Corels is now on CRAN! The package was introduced with an initial tweet which pointed to the GitHub repo. The source code repo has since been relocated from my account to the (upstream) corels org in GitHub. And renamed: as the upstream (C++) repo a...

Business intelligence (BI) is an indispensable tool for many, if not most, modern organizations. BI covers an entire gamut of end-to-end activities from data mining to reporting, all carried out with a core goal assisting critical business decision making. How significant has BI become? One indication of its popularity can ...

Built with R, available in any language, COVID-19 Data Hub provides a worldwide, fine-grained, unified dataset helpful for a better understanding of COVID-19. The user can instantly download up-to-date, structured, historical daily data across several official sources. The data are hourly crunched and made available in csv format on a ...

I’m EXTACTIC ???? to announce the release of timetk version 2.0.0. This is a monumental release that significantly expands the functionality of timetk to go WAY BEYOND the original goals of the package. Now, the package is a full-featured time series...

The weekly puzzle from Le Monde is once more disappointing. Everyday of the month, take 0, 1 or 2 units. If one unit taken past day, next day none can be taken. If two units taken two day ago, none can be taken the current day. What is the strategy maximising the number ...

A Joint Regression model Let’s talk about a very old, but, nonetheless, useful technique. It is widely known that the yield of a genotype in different environments depends on environmental covariates, such as the amount of rainfall in some critical...

A target-based categorical encoder for Statistical/Machine Learning (based on correlations) Part 2.

A Joint Regression model Let’s talk about a very old, but, nonetheless, useful technique. It is widely known that the yield of a genotype in different environments depends on environmental covariates, such as the amount of rainfall in some critical periods of time. Apart from rain, also temperature, wind, ...

A target-based categorical encoder for Statistical/Machine Learning (based on correlations) Part 2.

Arrogance is not a good quality for your models. It’s a rarely acknowledged fact that models data scientists produce are often not sufficiently robust or fault-tolerant to actually be put into production. Sure, you can trust your predictions when th...

An issue that often crops up when modelling with generlaized additive models (GAMs), especially with time series or spatial data, is how to extrapolate beyond the range of the data used to train the model? The issue arises because GAMs use splines to learn from the data using basis functions. ...

I have been using Spotify for two years now. I was always curious to know my listening trends, which is why I started using last.fm and other tools like that. However, they didn’t give me exact information as to what I listened – the insigh...

Overview I. Nest and pivot II. Expand combinations III. Filter redundancies IV. Map function(s) V. Return to normal dataframe VI. Bind back to data Functionalize Example creating & evaluating features When is this approach inappropriate? Appen...

Overview I. Nest and pivot II. Expand combinations III. Filter redundancies IV. Map function(s) V. Return to normal dataframe VI. Bind back to data Functionalize Example creating & evaluating features When is this approach inappropriate? Appen...