Similar to this post, but with "julia-lang" added: https://stackoverflow.blog/2017/09/06/incredible-growth-python/
Response to a tweet
Live code from the 2017-02-20 Denver R User Group meetup
Some simulation of logistic regression with a known rate of mislabeled outcomes. How can the bias be reduced
Some quick notes leading to some of my tweets. Not reproducible from outside of Stack Overflow
Analyzing Trump speeches with tidytext
Some processing of election results to add population and area
Cross validation with linear modeling and ISLR stock market data
Analysis of 12 songs
Analysis of CrowdFlower Airline tweet sentiment data
Drawing a multi-panel spaghetti plot in R
Network of packages that tend to be SUGGESTS/IMPORTS/DEPENDS on together
Short analysis of #7FavPackages hashtag, still in progress
This is an adaptation of the code I used to demonstrate broom in the Portland PDXR meetup.
Sentiment analysis of quotes about R in the fotunes package using the tidytext package.
Tidying an untidyable dataset from the Enron corpus
Using sentiment analysis with Pride and Prejudice to annotate it with emotions, Trump-style. Great!
How does Donald Trump end tweets? Interesting!
#rstats valentine made with gganimate
Based on Joshua Kunst's post here: http://jkunst.com/r/visualizing-chess-data-with-ggplot/
A speed comparison building on Stephen Turner's.
This plots Anscombe’s quartet using the tidy tools of dplyr, tidyr and ggplot2.
Effect of compression type and file complexity on saveRDS size and speed
Voting blocs in the UN
Using tidyr and dplyr to compare values across multiple variables
Demonstration and application of subSeq software (https://github.com/StoreyLab/subSeq)
Covers basic statistical analysis, and using data.table on a practical example.
Slides for Lesson 2 of the Wintersession 2014 Princeton course, on using ggplot2 for data visualization (including scatterplots, histograms, boxplots, and violin plots). Also covers writing functions in R and the list data type.
Slides for Lesson 1 of the Wintersession 2014 Princeton course, on variables and data structures in R.