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Retrieving Webpages Through Python Programming

Modeling R Tools & Languages Web Scrapingposted by ODSC Community July 22, 2020

The internet and the World Wide Web (WWW), is probably the most prominent source of information today. Most of that information is retrievable through HTTP. HTTP was invented originally to share pages of hypertext (hence the name Hypertext Transfer Protocol), which eventually started the WWW. This process occurs every time we request a web page through our devices. The... Read more

A Data Pattern with an R data.table Solution.

Modeling R Tools & Languagesposted by Steve Miller April 17, 2020

Summary: This blog examines a loading pattern seen often with government-generated, web-accessible data. The data comprise millions of records across multiple text or csv files, generally demarcated by time. The files may present different, but overlapping, attributes, while much of the data has a character representation, posing the challenge... Read more

Data Manipulation in R

R Tools & Languages data manipulationposted by Antoine Soetewey April 17, 2020

Not all datasets are as clean and tidy as you would expect. Therefore, after importing your dataset into RStudio, most of the time you will need to prepare it before performing any statistical analyses. Data manipulation can even sometimes take longer than the actual analyses when the quality of the... Read more

Guide to R and Python in a Single Jupyter Notebook

Python R Tools & Languages jupyterposted by Matthew Stewart March 6, 2020

Why pick one when you can use both at the same time? R is primarily used for statistical analysis, while Python provides a more general approach to data science. R and Python are object-oriented towards data science for programming language. Learning both is an ideal solution. Python is a... Read more

PI and Simulation Art in R

R Tools & Languages Uncategorizedposted by Steve Miller February 25, 2020

I spent the better part of an afternoon last week perusing a set of old flash drives I’d made years ago for my monthly notebook backups. One that especially caught my attention had a folder of R scripts, probably at least 15 years old — harking back to my... Read more

Beginner’s Guide to K-Nearest Neighbors in R: from Zero to Hero

Machine Learning Modeling R Tools & Languages k-nearest neighborsposted by Leihua Ye February 10, 2020

In the world of Machine Learning, I find the K-Nearest Neighbors (KNN) classifier makes the most intuitive sense and easily accessible to beginners even without introducing any math notations. To decide the label of an observation, we look at its neighbors and assign the neighbors’ label to the observation... Read more

An Efficient Way to Install and Load R Packages

R Tools & Languagesposted by Antoine Soetewey February 7, 2020

Unlike other programs, only fundamental functionalities come by default with R. You will thus often need to install some “extensions” to perform the analyses you want. These extensions which are are collections of functions and datasets developed and published by R users are called packages. They extend existing base R... Read more

15+ Resources to Get Started with R

Career Insights Featured Post R Tools & Languagesposted by Elizabeth Wallace, ODSC January 3, 2020

R is the second most sought after language in data science behind Python, so gaining mastery of R is a prerequisite to a thriving career in the field. Whether you’re an experienced developer or a newbie considering a career move, here are some excellent resources so you can get... Read more

Quantifying R Package Dependency Risk

R Tools & Languages dependency riskposted by John Mount December 26, 2019

We recently commented on excess package dependencies as representing risk in the R package ecosystem. The question remains: how much risk? Is low dependency a mere talisman, or is there evidence it is a good practice (or at least correlates with other good practices)? [Related Article: Data-Driven Exploration of the R User Community... Read more

Machine Learning 101: Predicting Drug Use Using Logistic Regression In R

Machine Learning Modeling R Tools & Languages Logistic Regressionposted by Leihua Ye December 24, 2019

Executive Summary Generalized Linear Models (GLM) Three types of link function: Logit, Probit, and Complementary log-log (cloglog) Building a logistic regression to predict drug use and compare these three types of GLM In Machine Learning 101 courses, stats professors introduce GLM right after linear regression as the next stepping... Read more