Python-bloggers

Adaptive (online/streaming) learning with uncertainty quantification and explanations using learningmachine in Python and R

In a previous blog post I showed how to get over limitations of creating dummy datasets directly in Microsoft 365 Copilot by asking for a Python script instead, particularly the faker package. Technology moves quickly, and since publishing that post, the Faker package has become available directly within the Python in ...

Geospatial vector data is a way of representing geographic features in a digital format using points, lines, and polygons. Unlike raster data, which represents geographic data as a grid of cells or pixels, vector data represents features more pr...

Geospatial vector data is a way of representing geographic features in a digital format using points, lines, and polygons. Unlike raster data, which represents geographic data as a grid of cells or pixels, vector data represents features more pr...

From 2016 to 2022, the annual app downloads witnessed a substantial 82% increase. An experienced business or a startup recognizes this statistic as an additional channel to engage with customers. Apart from monetization, businesses can also gather data on user behavior and broaden their target audience.  This article delves into the intricate world ...

Have you ever thought R’s approach to machine learning is outdated? Like, data analysis and visualization tools are superb. Everything feels intuitive and every following step of your workflow integrates seamlessly. That’s by design. Or, the design of the tidyverse collection of packages. R tidymodels aims to do ...

Shiny applications are fantastic for turning data into interactive dashboards and web apps, making data exploration and visualization more engaging. But even the most visually appealing Shiny app can hit performance snags. Lagging visualizations, delayed user interactions, and sluggish data updates can quickly turn a promising Shiny app into a ...

We are pleased to announce the full line-up for this year’s Shiny in Production conference! This year, we’re introducing a new lightning talk session. These short 5 minute talks will allow us to showcase many more uses of Shiny in Production. The conference will still feature 6 full length talks, ...

In our last article, we explored the S4 OOP system in R. Up until this point, we had only discussed functional OOP systems in R. Today, we are going to learn about two encapsulated OOP systems available for R: Reference Classes –  introduced to R in 2010 in version 2.12.0 (source). Sometimes also ...