Forecasting at scale.

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

• Prophet: Automatic Forecasting Procedure @ GitHub.

Related contents:

• Predictive Autoscaling in Kubernetes with Keda and Prophet @ Minimal Devops' Medium.

The best dashboards are built with code. Create fast, beautiful data apps, dashboards, and reports from the command line. Write Markdown, JavaScript, SQL, Python, R… and any language you like. Free and open-source.

A static site generator for data apps, dashboards, reports, and more. Observable Framework combines JavaScript on the front-end for interactive graphics with any language on the back-end for data analysis.

• Observable Framework @ GitHub.

Easy web apps for data science without the compromises. No web development skills required.

• Shiny @ GitHub.
• Shiny for Python @ GitHub.

Related contents:

• Episode 608: R With Eric Nantz @ Coder Radio.
• Shiny Developer Series homepage.

Reproducible Data Science Environments with Nix.

{rix} is an R package that leverages Nix, a package manager focused on reproducible builds. With Nix, you can create project-specific environments with a custom version of R, its packages, and all system dependencies (e.g., GDAL). Nix ensures full reproducibility, which is crucial for research and development projects.

• rix @ GitHub.

Related contents:

• Episode 608: R With Eric Nantz @ Coder Radio.

The R Project for Statistical Computing.

R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.

Related contents:

• Episode 608: R With Eric Nantz @ Coder Radio.
• R Weekly Highlights.
• R Podcast.
• If all the world were a monorepo @ Julie's Substack.

text2vec is an R package which provides an efficient framework with a concise API for text analysis and natural language processing (NLP).

text2vec @ GitHub.

Convert curl commands to code. Convert curl commands to Python, JavaScript, PHP, R, Go, C#, Ruby, Rust, Elixir, Java, MATLAB, Dart, CFML, Ansible URI or JSON.

curlconverter @ GitHub.

Guide, reference and cheatsheet on web scraping using rvest, httr and Rselenium. Inspired by Hartley Brody, this cheat sheet is about web scraping using rvest,httr and Rselenium. It covers many topics in this blog.

While Hartley uses python's requests and beautifulsoup libraries, this cheat sheet covers the usage of httr and rvest. While rvest is good enough for many scraping tasks, httr is required for more advanced techniques. Usage of Rselenium(web driver) is also covered.

DuckDB is an in-process SQL OLAP database management system.

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and several extensions designed to make SQL easier to use.

• DuckDB @ GitHub.

Related contents:

• DuckDB - Le moteur SQL qui transforme vos données @ Korben :fr:.
• Why DuckDB is my first choice for data processing @ >robinlinacre.
• DuckDB is Probably the Most Important Geospatial Software of the Last Decade @ dbreunig.com.
• Why Semantic Layers Matter — and How to Build One with DuckDB @ MotherDuck.
• Querying Billions of GitHub Events Using Modal and DuckDB (Part 1: Ingesting Data) @ noreasontopanic.