The post Filter a Vector in R appeared first on Data Science Tutorials
Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials.
Filter a Vector in R is a fundamental skill that can be applied to a wide range of data analysis tasks. In ... [Read more...]

Introduction
As a blogger who uses R for content creation, I’ve found it incredibly useful to automate some of the repetitive tasks. One such task is creating Quarto Markdown (QMD) files for new blog posts. To simplify this, I’ve added a custom... [Read more...]

Summary
In the current version of dplyr, if x is not a column name in data frame d, then pull(d, x) attempts to look up the value of x in the environment instead of returning NULL or an error. There are ways to augment pull() to yield the exp... [Read more...]

Motivation
Coarse data
Simulated example
Real data example
References
Motivation
A group of researchers from the Data Science Institute (DSI) at Hasselt University developed a new statistical model to estimate the incubation period of a pathogenic organism based on coarse data. The incubation period of an infectious disease (defined as ...

[Read more...] In September 2023, I wrote a blog post about
creating typewriter-styled maps in {ggplot2}. It described the process of creating an elevation map where, instead of using colours to denote the different elevation levels, different letters of the alphabet...

[Read more...] “We can only see a short distance ahead, but we can see plenty there that needs to be done.” ― Alan Turing AI virtual assistants have become indispensable tools for both personal and professional settings. While Siri and Alexa are household names, the latest advancements in AI-powered virtual assistants offer capabilities ...

[Read more...]The post Split a Vector into Chunks in R appeared first on Data Science Tutorials
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Split a Vector into Chunks in R can be a useful technique for manipulating and analyzing data. In this article, ... [Read more...]

Introduction
Hello, fellow R useRs! Today, we’re going to discuss a fascinating topic that bridges the gap between VBA (Visual Basic for Applications) and R. We’ll explore how to get a list of all open workbooks in Excel using VBA and then call...

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Introduction
When fitting a nonlinear regression model in R with nls(), the first step is to select an appropriate regression model to fit the observed data, the second step is to find reasonable starting values for the model parameters in order to initialize the nonlinear least-squares (NLS) algorithm. In some ...

[Read more...]My new blog/newsletter ("Paired Ends") is now at blog.stephenturner.us. I'll be posting semi-regular updates and literature highlights in bioinformatics, computational biology, and data science, along with the occasional post on programming. Head ... [Read more...]

BlueSky Statistics is a free and open-source graphical user interface for the powerful R language. There is also a commercial “Pro” version that offers tech support, priority feature requests, and many powerful additional features. The Pro version has been beefed up considerably with the new features below. These features apply ...

[Read more...]The post Mastering the table() Function in R appeared first on Data Science Tutorials
Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials.
Mastering the table() Function in R, The table() function in R is a powerful tool for creating frequency tables, allowing you ... [Read more...]

Introduction
In data analysis and manipulation, handling text data is a common task. One of the essential operations you might need to perform is converting strings to lowercase. In R, this is easily done using the tolower() function. Let’s exp... [Read more...]

Python package 'colorspace' with tools for manipulating and assessing colors and palettes is now available from PyPI, accompanied by a documentation web page and an arXiv paper.
Citation
Reto Stauffer, Achim Zeileis (2024). “...

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Machine Learning is transforming how we design drugs, model diseases, develop treatments, and conduct clinical trials. We recently collaborated with IIMCB to carry out augmented RNA-Ligand binding prediction with machine learning. Learn more about our work in this blog post. These advancements are helping researchers and healthcare professionals make smarter ...

[Read more...]Join our workshop on Introduction to Bayesian Structural Equation Modeling in R, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Introduction to Bayesian Structural Equation Modeling in R Date: Thursday, August 29th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) Speaker: Esteban Montenegro-Montenegro serves as ... [Read more...]

Introduction
Stratified sampling is a technique used to ensure that different subgroups (strata) within a population are represented in a sample. This method is particularly useful when certain strata are underrepresented in a simple random sam... [Read more...]

Introduction
This blog is a new function, treatment_model that have been added to the Dyn4cast package. The function provides means for enhanced estimation of propensity score and treatments effects from randomized controlled designed experiments.
Ob...

[Read more...]The post Mastering the tapply() Function in R appeared first on Data Science Tutorials
Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials.
Mastering the tapply() Function in R, The tapply() function in R is a powerful tool for applying a function to a ... [Read more...]

The post Best Data Visualization Books appeared first on Data Science Tutorials
Unravel the Future: Dive Deep into the World of Data Science Today! Data Science Tutorials.
Best Data Visualization Books, “Unlock the Power of Storytelling with Data: Transform Your Visualizations into Compelling Narratives! In this insightful book, you’ll ... [Read more...]

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