1592. Data Vis Dispatch: January 4, January 11, January 18, January 25, February 1, February 8, February 15, February 22, March 1, March 15, COVID Trackers Special, March 29, April 5, April 12 April 19, April 26, May 3, May 10, May 17, May 24, May 31, June 7, June 14, June 21, June 28, July 5, July 12, July 19, July 26, August 2, August 9, August 16, August 23, September 6, September 20, October 4, October 11, October 18, October 25, November 1, November 8, November 15, November 22, November 29, December 6, December 13, December 20, December 27
1593. Causal Inference | Hypothesis Testing | All at Once
1594. Build a Shiny App Demo
1595. Animated population tree maps
1596. Type inference in readr and arrow
1597. How I learn machine learning
1598. Wrangling data in JavaScript with Arquero: a primer for R users
1599. How To R: Visualizing Distributions, Making Better Histograms
1600. Analyzing All Recipes
1601. Philosophy of Statistics
1602. Webscraping with RSelenium: Automate your browser actions
1603. Generalized Visual Language Models
1604. Open source is a hard requirement for reproducibility
1606. Reproducibility with Docker and Github Actions for the average R enjoyer
1606. Learning Excel as an R user
1607. Analyzing Projected Calculations Using R
1608. Bar plot checklist
1609. Panel Data (DiD, Synth, MC) Causal Inference
1610. A Visual Bibliography of Tree Visualization 2.0
1611. I’m not a real statistician, and you can be one too
1612. R package reviews {gtsummary} Publication-Ready Tables of Data, Stat-Tests and Models!
1613. Understanding The Harmonic Mean
1614. Some notes about improving base R code
1615. Model Calibration
1616. Monitoring quarto-dev repositories: Creating a workflow with GitHub Actions for R users
1617. Automated Tufte-style weather graphs
1618. Automatically deploying a Shiny app for browsing #RStats tweets with GitHub Actions
1619. Weird & wonderful: Hungarian data graphics
1620. Building a ggplot2 rollercoaster: Creating amazing 3D data visualizations in R
1621. The WorldStrat dataset
1622. NormConf: Lightning Talks
1623. Which R packages do scientists use?
1624. Read and Visualize your Twitter Archive
1625. Practical Deep Learning for Coders
1626. How to use natural and base 10 log scales in ggplot2
1627. Hillshade, colors and marginal plots with tidyterra: I: How to overlay SpatRasters, II: The rain in Spain does not stay mainly in the plain
1628. NLP Demystified
1629. On Probability versus Likelihood
1630. ChatGPT Resources
1631. High-Dimensional Probability and Applicaitons in Data Science
1632. Introducing the googletraffic R Package: A new tool to measure congestion across large spatial areas
1633. Historical analogies for large language models
1634. Extended Two-way Fixed Effects (ETWFE)
1635. How The Economist makes the best charts on the internet
1636. Random Forests for Complete Beginners
1637. Terrorism and Counterterrorism Datasets: An Overview
1638. Scaling down Deep Learning
1639. Annotated Forest Plots using ggplot2
1640. Applied Causal Analysis (with R)
1641. Simpson’s paradox all the way down
1642. Data Science in Julia for Hackers
1643. R packages for visualising spatial data
1644. A Short Guide for Feature Engineering and Feature Selection
1645. Modeling Key World Cup Moments with Machine Learning
1646. The Turing Way
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