I have managed to improve the backend of my user-made RStudio themes collection recently: Until recently, I had maintained the collection manually, adding new themes by hand and sorting everything. Now, everything is much more automated, making it easier to maintain in the future. All themes are included in a nice CSV file (this one) that can easily be sorted via R. The main overview is directly sourcing from this CSV file and creating the Markdown list via some R code.
An updated version of the “pricesensitivitymeter” R package is now available on CRAN: This version 1.2 includes two main new features: The new function psm_plot() is a convenience function for creating the “standard” Price Sensitivity Meter plot. You can see a simple example in the Visualizing PSM Results vignette. The psm_analysis() function now also supports input in tibble format (which is common in the “tidyverse”), in addition to standard data.
I cannot remember anymore when I started using Pocket, but I certainly remember that I realized quickly that it was exactly what I needed. My elaborate collection of browser bookmarks that I wanted to read “some day/maybe”, quickly turned into a massive Pocket queue with articles spanning more than a decade. I don’t know if I’ll ever finish reading it, but at least I feel somewhat in control and I enjoy reading a few articles in bed on a lazy Sunday morning.
The universe of RStudio themes is growing constantly. I have updated the RStudio Theme Collection to account for new themes that have been created recently. Thanks to z3tt for the Viridis theme, to William Carcamo for the Custom theme, to Alfredo Hernández for the Darkula theme, to Matt Dube for several themes (Gruvbox, Paper Color), to Linda for Material Theme Darker / darkrstudio, to Alessio Maggiorelli for the Matrix Glow theme, to Stephen Siegert for the Nord Polar Night theme, and to David Gibson for the Ayu themes (dark, mirage, light).
It’s great to see that the RStudio theme selection is growing thanks to custom themes being created by users. Many of them are ports of themes that work well in other code editors. I am (kind of) regularly updating the RStudio Theme Collection which I had first created in August. In the most recent update at the end of October / beginning of November, I have added the following dark themes: Asher, Fairyfloss, Fairyfloss Dark, Mojave Dark, Nord One (a mashup of the Nord theme and Atom’s dark theme), One Dark.
The version 1.1 of the “pricesensitivitymeter” R package enhances interpolation: Instead of fixed steps of 0.01, it lets the user choose the size of the interpolation steps. This makes it easier to work in currencies in which a subdivision into 1/100th is not meaningful, such as Japanese Yen or Chilean Pesos. Moreover, it makes it easier to analyze data for more expensive products in which a subdivision on cent-level is not necessary.
RStudio has recently added a feature that allows users to create custom themes. However, it seems that there is no central place to find those custom RStudio themes. I have just started a Github repository which hosts a collection of user-made RStudio themes. I have tried to find as many themes as possible via Github and search engines. If something is missing on this list or if you have recently created your own RStudio theme, please feel free to create a pull request or open an issue (or simply send me an e-mail).
I recently discovered the Nord theme for VS Code and was absolutely blown away by its simplicity and elegance. Next thing I know, I’m creating a RStudio port of this theme - you can find it here on Github. If you are using RStudio v1.2.0 or newer, you can directly install the theme via the preferences dialogue. Feel free to give it a try! If you are like me and want to know more about the Nord theme family, the developer of the VS Code theme has created a stunning website https://www.
v1.0 of the “pricesensitivitymeter” R package is now available on CRAN. This version adds a new function psm_analysis_weighted() which allows to properly deal with weighted data. As far as I know, this is the first implementation of the van Westendorp Price Sensitivity Meter methodology that accounts for weighting. The R package uses the infrastructure that is provided by the excellent “survey” package: To use weighted data, it must be set up as a “survey design” object via the svydesign() function from the “survey” package.
v0.4.1 of the “pricesensitivitymeter” R package has been released on CRAN. It fixes a bug in the calculation of the “point of marginal cheapness” and the “point of marginal expensiveness”, properly shows the percentage of invalid cases, fixes several typos and adds unit testing for the input to the Newton Miller Smith extension. The package is available on CRAN. Feedback via e-mail or via opening issues in the corresponding Github repository is always welcome.
v0.3 of the “pricesensitivitymeter” R package expands the functionality for interpolation between price points. If the sample size is small or price information in some areas of the price curve is sparse, the package now is able to use linear interpolation between price points to make the price curves appear less bumpy. The option is by default set to FALSE, but can easily be switched on: output <- psm_analysis(toocheap, cheap, expensive, tooexpensive, interpolate = TRUE) The package also contains a vignette (“Interpolation in Small Samples”) that explains how the function works.
Great news: The “pricesensitivitymeter” package has just been released on CRAN! Please use the following link to find it there: https://cran.r-project.org/package=pricesensitivitymeter CRAN is the standard repository for R packages, which means that the “pricesensitivitymeter” package can be installed via R’s standard routine: install.packages("pricesensitivitymeter") Compared to v0.1 of the package (which was available via Github), I have added the following features: support for running the analysis without a “too cheap” price vignette to explain charting unit testing for main function inputs and outputs smoothing of trial/revenue optimization for Newton Miller Smith extension (previous version was a bit bumpy when there were areas with sparse data) (changed the name of the main function to psm_analysis() for readability reasons) I am excited that the CRAN release makes the package available for a wider group of users.
Today, I have released the first version (v0.1) of the R package I have written during the last couple of months: “pricesensitivitymeter” is an implementation of the van Westendorp Price Sensitivity Meter (PSM) - a standard market research methodology for assessing consumer price preferences. The package is available via this Github repository. The original research paper which explains the methodology was published in 1976 in the Proceedings of the ESOMAR congress and is available at ESOMAR’s Research World website.