Nothing short of wacky usage of plot() function with xspline to interpolate the points, but still a “parameter” short of Bezier’s curve. 🙂 Given two random vectors, you can generate a plot that, xspline will smooth out the plot and…Read more ›
It’s March 2023 and right now ChatGPT, the amazing AI chatbot tool from OpenAI, is all the rage. But when OpenAI released their public web API for ChatGPT on the 1st of March you might have been a bit disappointed. If you’re an R user, that is. Because, when scrolling through…
The article talks about R packages with a range of functions, including data manipulation, data visualization, machine learning, etc.
A consistent, simple and easy to use set of wrappers around the fantastic 'stringi' package. All function and argument names (and positions) are consistent, all functions deal with "NA"'s and zero length vectors in the same way, and the output from one function is easy to feed…
The goal of 'readr' is to provide a fast and friendly way to read rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed to flexibly parse many types of data found in the wild, while still cleanly failing when data unexpectedly changes.
A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
A practical introduction.
OpenStreetMap + Data Visualization = Art
If there’s one type of data no company has a shortage of, it has to be time series data. Yet, many beginner and intermediate R developers struggle to grasp their heads around basic R time series concepts, such as manipulating datetime values, visualizing time data over time, and…
Learn the basic steps to run a Multiple Correspondence Analysis in R
3rd edition
At the EEX, German baseload electricity futures for the year 2023 trade at a price of 950 Euro / MWh and peak load futures at 1275 Euro / MWh. Future prices for France are even higher. (Prices were looked up on 2022-08-28). In contrast, average German...
Effective interactive data visualizations in R
This article will dive into R's different uses and demonstrate what you can do with this programming language once you've learned it.
A technical manual of graphs, networks and their applications in the people and social sciences
Leverage the powerful data wrangling tools in R’s dplyr to clean and prepare your data.
Making a survival analysis can be a challenge even for experienced R users, but the good news is I’ll help you make beautiful, publication-quality survival plots in under 10-minutes. Here’s what WE are going to do: Make your first survival model an...
An extremely long review of R.
This cookbook contains more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly—without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can…
A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools
R graphics tutorial: scatterplots with anti-aliasing, using the Cairo library. Two lines of code to make much better visualizations in R.
R kernel for Jupyter.
In January 2016, I was honored to receive an “Honorable Mention” of the John Chambers Award 2016. This article was written for R-bloggers, whose builder, Tal Galili, kindly invited me to write an introduction to the rARPACK package. A Short Story of rARPACK Eigenvalue…
Powerful R libraries built by the World’s Biggest Tech Companies
Way back in August 2020, I launched Big Book of R, a collection of free (and some paid) R programming books organised by categories like Geospatial, Statistics, Packages and many more. What started off as a 100 book collection has now grown to over 200 :D! Anyway, I felt was ……
This is a draft of a book for learning data analysis with the R language. This book emphasizes hands activities. Comments and suggestions are welcome.
Note. This is an update to article: Using R and H2O to identify product anomalies during the manufacturing process.It has some updates but also code optimization from Yana Kane-Esrig( https://www.linkedin.com/in/ykaneesrig/ ), as sh...
An illustrative guide to estimate the pure premium using Tweedie models in GLMs and Machine Learning
A kind reader recently shared the following comment on the Practical Data Science with R 2nd Edition live-site. Thanks for the chapter on data frames and data.tables. It has helped me overcome an o…
Isotonic regression is a method for obtaining a monotonic fit for 1-dimensional data. Let’s say we have data such that . (We assume no ties among the ‘s for simplicity.) Informally, isotonic regression looks for such that the ‘s approximate … Continue reading →
Case study of tweets from comments on Indonesia’s biggest media
Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency.
Vector Indexing, Eigenvector Solvers, Singular Value Decomposition, & More
Practical Data Science with R, 2nd Edition author Dr. Nina Zumel, with a fresh author’s copy of her book!
The timekit package contains a collection of tools for working with time series in R. There’s a number of benefits. One of the biggest is the ability to use a time series signature to predict future values (forecast) through data mining techniques. W...
Operations need to have demand forecasts in order to establish optimal resource allocation policies. But, when we make predictions the only thing that we assure is the occurrence of prediction errors. Fortunately, there is no need to be 100% accurate to succeed, we just need to…
Building machine learning and statistical models often requires pre- and post-transformation of the input and/or response variables, prior to training (or fitting) the models. For example, a model may require training on the logarithm of the response and input variables. As a…
Learn R through 1000+ free exercises on basic R concepts, data cleaning, modeling, machine learning, and visualization.
Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.
This article comes from Togaware. A Survival Guide to Data Science with R These draft chapters weave together a collection of tools for the data scientist—tools that are all part of the R Statistical Software Suite. Each chapter is a collection of one (or more) pages that cover…
[…]
Last week, I had the opportunity to talk to a group of Master’s level Statistics and Business Analytics students at Cal State East Bay about R and Data Science. Many in my audience were adult students coming back to school with job experience writing code in Java, Python and…
Stefan Feuerriegel This blog entry concerns our course on “Operations Reserch with R” that we teach as part of our study program. We hope that the materials are of value to lectures and everyone else working in the field of numerical optimiatzion. Course outline The course…
R Language Tutorials for Advanced Statistics
If you have tried to communicate research results and data visualizations using R, there is a good chance you will have come across one of its great limitations. R is painful when you need to...