Here is the latest bag of tweets^*, which covers March 2014.

(*) These are interesting news that I found on Twitter and that I archive periodically.

• michaelwaskom: Seaborn 0.3 is out! Check out the release notes: http://t.co/JjvR0Fc8ov and shiny new example gallery: http://t.co/3AYH4d5QQ4 (24 Mar)
• stephensenn: @inductivestep @david_colquhoun “The first t-test” http://t.co/8r9Hf62DzX and also “A century of t-tests” http://t.co/J20ESbYID6 (24 Mar)
• WiringTheBrain: Publication and other reporting biases in cognitive sciences: detection, prevalence (high!), and prevention http://t.co/tJPixML4lZ (24 Mar)
• YhatHQ: THE DATA ANALYTICS HANDBOOK - Interviews with several top data scientists | http://t.co/up4ozO3Msq (24 Mar)
• alexrothenberg: I love these visual explanations: Explain Git with D3 http://t.co/1WMaFKbW21 (24 Mar)
• Biff_Bruise: MT @epistatistic: Free book: Learning Statistics with R… also the assoc. lsr package available on CRAN. http://t.co/krZo8MJmrv #rstats (24 Mar)
• Billare: Differences. SVM trained on connectivity data predicted sex correctly 71% of the time. http://t.co/QDWiot1iMZ http://t.co/C3hnXwv7HG (24 Mar)
• HNTweets: Simple recommendation system written in Ruby: http://t.co/AGmfnqkrS6 Comments: https://t.co/zssfoxK23Y (24 Mar)
• Atabey_Kaygun: Create Twitter Wordcloud with Sentiments http://t.co/PVbyu234XZ via @Prismatic (24 Mar)
• danielszmu: Good overview of sane Repl practices with #Clojure. http://t.co/csb2kwIypg (24 Mar)
• Soc_Net_Intel: RT @KirkDBorne: Some Useful #MachineLearning Libraries for #BigData #DataScientists : http://t.co/L7ig6XPfld #DataMining (24 Mar)
• theory: Read the new forthcoming Postgres 9.4 JSON docs — including the new JSONB type — here: http://t.co/cHJNY062CL (23 Mar)
• tristanzajonc: Ten Simple Rules for Reproducible Computational Research http://t.co/3cgkbv5Vns (23 Mar)
• newsycombinator: Principles of good data analysis http://t.co/57CigfOAoM (23 Mar)
• astrieanna: Here’s how to use my favorite #julialang plotting package: ASCIIPlots http://t.co/KXNKDtg6X3 (with suggestions for pull requests :) (23 Mar)
• fastml_extra: Online Learning for Matrix Factorization and Sparse Coding / SPArse Modeling Software: paper, description, code: http://t.co/HPOXagN8xI (23 Mar)
• christian_stamm: thanks @cemerick! Your Starting clojure screencast made a perfectly relaxing sunday afternoon entertainment. https://t.co/ttbFBHranE (23 Mar)
• kevinkeenan_: Nice dedication in the #rstats book, “Guide to Programming and Algorithms Using R”: (http://t.co/kPrAEBOIrB) http://t.co/bkNXYvqZJ0 (23 Mar)
• Billare: Best blog ever? Relating reads, assemblies, coverage, variant calling & inference. With an explicit workflow given. http://t.co/NKaR8yFuPh (22 Mar)
• EMR_research: Measuring satisfaction with electronic medical record systems in U.S. dialysis facilities. http://t.co/xjRcDWd1Dk (22 Mar)
• rasbt: Emacs for computational Biology - Part 1 Emacs as a Lab Notebook http://t.co/ixu2VOzanX (22 Mar)
• simplystats: .@LorenaABarba @fperez_org No problem. Our whole Data Science Specialization is on github https://t.co/IzF6KY8W2E (22 Mar)
• ananelson: Causal roles, supporting factors, and how to use evidence from RCTs. Great book on how to think: http://t.co/Nu9Q7FztiE (21 Mar)
• Susan2013NY: A good example of visually pleasant data analysis #DataVizQMSS check out http://t.co/7x4uNnH1o4 (21 Mar)
• RevolutionR: Handling character data in #R free e-book: http://t.co/t4YmBjbU3p (21 Mar)
• DrVes: Twitter: a good place to detect health conditions (study) http://t.co/uqRplmgO8P (21 Mar)
• timelyportfolio: from forestry to finance with #rstats, #rCharts, #d3js, #angularjs Timely Portfolio: … #bfast breakpoints http://t.co/97CrmXoVbn (21 Mar)
• ericnormand: Happy to announce that http://t.co/XYKr7uBn3K is “good enough” now to sell. A short list of tweaks and I will release before @ClojureWest (20 Mar)
• simplystats: The 80/20 rule of statistical methods development http://t.co/GGGYwVqBeR (20 Mar)
• analyticbridge: Machine Learning in Parallel with Support Vector Machines, Gener…: http://t.co/uSWXCbAmlp (20 Mar)
• jwbelmon: Data visualization is the key to efficient clinical utilization of genomic data http://t.co/UTqIeII6zm (20 Mar)
• Atabey_Kaygun: MCMC for Econometrics Students http://t.co/RcuSfcRHqr (20 Mar)
• aphyr: The Lisp-1 manual jumps immediately to SYMBOLIC CALCULUS OVER CODE EXPRESSIONS. That’s what “code as data” means. http://t.co/znhh6dDHmV (19 Mar)
• fogus: There’s a fun port of my Functional JavaScript code examples to CoffeeScript in the works by @joyrexus https://t.co/TGDWLlaSmT (19 Mar)
• moorejh: #bioinformatics RT @kennamshaw: Data integration in the era of “omics”: current and future challenges http://t.co/yZA27JN1tg #genomics (19 Mar)
• egonwillighagen: a human readable tutorial on what is new in Java 8 http://t.co/l8luZBHv9i (19 Mar)
• StatsPapers: On the Sensitivity of the Lasso to the Number of Predictor Variables. http://t.co/3OVGnBHJGf (19 Mar)
• DavidWLawson: Our new book on Applied Evolutionary Anthropology is finally published! Info and sample chapters here: http://t.co/UUaJimbqza (19 Mar)
• AndrewCassidy89: Java, R, and Scala all in one!?! http://t.co/ubDRgk5sFS worked wonders for me today!! (19 Mar)
• Rbloggers: Secrets of Teaching R: (This article was first published on Revolutions, and kindly contributed t… http://t.co/IFE8Of1gTD #rstats (19 Mar)
• ramnath_vaidya: @hadleywickham data.table(mtcars)[,.SD[sample(.N, 5)],gear]. See this <http://t.co/mINElJaqO6 @MattDowle @arun_sriniv (18 Mar)
• java: Java SE 8 is Now Available #java8 #JDK8 http://t.co/NzQ75DVl5g (18 Mar)
• simplystats: . @hcorrada epivizr for interactive, reproducible genomic graphics http://t.co/PYQ2iANbDS #ENAR2014 (18 Mar)
• rdpeng: .@hmason See here: http://t.co/LQS88X7ulw (18 Mar)
• YhatHQ: Introduction to Python for Econometrics, Statistics and Data Analysis by Kevin Sheppard | http://t.co/wg7KtXDBsO (PDF) (18 Mar)
• radar: Thinking with data http://t.co/aKnPeYhmci > new @Radar podcast w/ @JonBruner, @mshron & @jakeporway (18 Mar)
• EffyVayena: “Personal Data for Public Good” report of the #healthdata exploration project http://t.co/3J637Xw8Dp @DatenundGesundh (18 Mar)
• JMP_software: #JMP #Clinical 5.0 launches today! Here are 7 things to love about it, courtesy of @rczink: http://t.co/XIlidnPhGG #clinicaltrials (18 Mar)
• JanWillemTulp: the #dataviz revolution on @sciam http://t.co/NtxErU9ATL #macroscope /cc @moritz_stefaner Nice work @alialmossawi ! (18 Mar)
• mja: How to fit and evaluate a Bayesian Pearson correlation, and why you might want to do so http://t.co/TtO3TvaNAR (18 Mar)
• plotlygraphs: @rasbt @muraii Cool! 1-line to plotly-ize a MPL figure: fig_to_plotly(fig1, username, api_key) Docs here: http://t.co/1c5qrrsJgB Let us kno! (18 Mar)
• plotlygraphs: @muraii @rasbt Tx for the shout-out! We also have a MPL figure –> Plotly publisher, should work for most of these: https://t.co/0tnitxzVLj (18 Mar)
• rasbt: Just recently moved to matplotlib and started to built a small gallery. It’s still very rough, but it’s growing :) https://t.co/wHgSAETeZS (18 Mar)
• hmCuesta: All the Code Examples of Practical Data Analysis Book is available on Github https://t.co/hqTBWvI3bc #datascience #python cc. @KirkDBorne (18 Mar)
• rasbt: Almost a year old but still a nice reference: Be Pythonic: init.py (How to use it the right way) http://t.co/Z8b6IOdq24 (18 Mar)
• kaz_yos: #rstats powerSurvEpi: Power and sample size calculation for survival analysis of epidemiological studies http://t.co/6qCjX10Dh8 (18 Mar)
• PhilipDBest: Hierarchical Linear Regression in PyMC3 http://t.co/aHFWrXdE5b (17 Mar)
• kinggary: “Archiving Reproducible Research with R and Dataverse” http://t.co/jxcg6ngZtD (17 Mar)
• genetics_blog: Nice. Command line tool to manipulate flat text files with #SQL https://t.co/Dvz2W2O25W (17 Mar)
• HNTweets: Open source git frontend based on Symfony2: http://t.co/B7gFL6N3tN Comments: https://t.co/nUURS1no93 (17 Mar)
• robjhyndman: Fast computation of cross-validation in linear models http://t.co/U8ZDgsonG7 (17 Mar)
• stephensenn: @zentree @HelSouth #statistics A tribute I wrote for John Nelder on his 80th now up on the web http://t.co/7dD0uRHDBj (17 Mar)
• adaptive_plant: Convert to google docs to Markdown - sweet! http://t.co/nBHoi7bzrY (17 Mar)
• adaptive_plant: @mkasumovic @RobLanfear @phylorich Could also use bibbase http://t.co/xcQKnRivf1 to display items from certain folder in zotero collection (17 Mar)
• diana_clarke: I read the pip/six/importlib source & http://t.co/EGdPSbnmN2 before going to bed… so it’s no wonder that I dreamt about python imports… (15 Mar)
• hmCuesta: Instrumenting collaboration tools used in data projects http://t.co/9rUPDBSJNn (15 Mar)
• ogrisel: Very nice write-up of the 2014 workshop on Stochastic Gradient Methods by Yaroslav Bulatov: http://t.co/2Cop7Bo3wq (via @zaxtax) (13 Mar)
• stephensenn: #Statistics #Course Statistical Issues in Drug Development http://t.co/4vclWjWRk0 14-15 May 2014 #Luxembourg http://t.co/Ig3zwc1AHa (13 Mar)
• ogrisel: @mblondel_ml any thoughts on: Accelerated, Parallel and Proximal Coordinate Descent by O. Fercoq & P. Richtárik http://t.co/hRBOwW68ZT ? (13 Mar)
• ramnath_vaidya: @_inundata It is just a single file for now http://t.co/QUlWSumoDV. I will convert to a package and push to github tonight. (13 Mar)
• biocs: Nice intro on Bayesian vs. frequentist statistics http://t.co/REG7m16OS5 but I’m still confused on picking priors and thus stay frequentist (13 Mar)
• dkvasnickajr: Yay, #Racket has a shiny new website! http://t.co/EYwmbbf4Zp (13 Mar)
• mbostock: Many recent improvements to Gistup. Please npm update -g gistup! https://t.co/Cnx9mF2QiM (13 Mar)
• hadleywickham: a review of density estimation packages in #rstats: http://t.co/VKgiz07wSt. From 2011 but forgot to promote it, still applicable today (13 Mar)
• YhatHQ: R and Open Science - awesome slides by Karthik Ram http://t.co/BPmV0ZUUQl (13 Mar)
• Biff_Bruise: RT @paulbanoub: Nice post on small multiples in #Tableau from @jimmwahl https://t.co/pCFcrSc9He (12 Mar)
• mikiobraun: My “Data Science: The Hard Parts” post is still going strong after 3 weeks. That’s a first! Thx for all the reads! http://t.co/3XfgjYQmAw (12 Mar)
• statsepi: Creating Mplus.inp files in R http://t.co/BaiBRnApbk (12 Mar)
• introspection: GoCognitive | Free Tools for Learning~Teaching Psychology & Cognitive Neuroscience http://t.co/ntmH20gfpP #Interactive #Education (12 Mar)
• paulblaser: Real-time Reporting with the Adobe Analytics API | (R news & tutorials) - http://t.co/qo313pBqxX (12 Mar)
• boblemarin: Visualizing sort algorythms #nice http://t.co/8RLjwoy4iK via @_3000d /cc @dwmheaj #dwmdataviz (12 Mar)
• zentree: “Less wordy #rstats’ in Quantum Forest. http://t.co/NjLfoiaAn2 (12 Mar)
• bayesian_stats: Relabelling Algorithms for Large Dataset Mixture Models http://t.co/OVVXEBnmwl – via http://t.co/tjyKW22WFA (12 Mar)
• kwbroman: Next Tools4RR lecture: Writing #rstats packages http://t.co/14pHVf3yQu http://t.co/0TYCu36w55 (11 Mar)
• sjmgarnier: Heads up @Quandl RT @randal_olson: Latest round of #Rstats vs #Python: Linear regressions. http://t.co/l3f7ytCeDp http://t.co/GpZQEuPwPn (11 Mar)
• ghoseb: thing-geom is a very interesting Clojure lib for 2D/3D graphics. Bonus: it’s written completely in literate style! https://t.co/OeGr8zt5lf (11 Mar)
• kwbroman: I put my poster @GitHub as well as on my web page; suggestions would be appreciated. http://t.co/XbIuOvfTIW http://t.co/BihVYaI2cc (11 Mar)
• freakonometrics: Definition of “fit” in http://t.co/8zgs7nzJAn “how sexually attractive you find a statistical test” and “Glossary” http://t.co/EunAAc9aJh (10 Mar)
• freakonometrics: Definition of “crying” in ‘Discovering Statistics Using R’ http://t.co/kLtJbl2Wrv see http://t.co/rizSNrm6yw (10 Mar)
• freakonometrics: Footnotes are always interesting http://t.co/TF5HrqvbL0 ht @GeluleMD see http://t.co/imYMa55DhL (10 Mar)
• sachac: How have I not read http://t.co/n7fgT2Xp44 before? Fascinating Org Mode workflow. (10 Mar)
• freakonometrics: “A Brief History of Databases” http://t.co/L3LYXfEZAy (10 Mar)
• rasbt: Another nice one: http://t.co/wKim4fCGwm is an easy non-intimidating way to get introduced to Python. http://t.co/SMnEaEDuCu (10 Mar)
• HNTweets: Wolfram Programming Cloud: http://t.co/KIN9CaIGMt Comments: https://t.co/EGgbtfAHLc (10 Mar)
• WinVectorLLC: New Win-Vector #machinelearning article: Can a classifier that never says “yes” be useful? http://t.co/Invdtpl827 #datascience #statistics (9 Mar)
• shoha99: #datavizqmss once you know #r #ggplot2 & #d3 , u may like to look at #ggvis now http://t.co/gERLzXiqMN #dataviz #rstats (9 Mar)
• moorejh: #visualization of the best squares on the chessboard http://t.co/kZq1JfSRx0 #chess #dataviz http://t.co/Fi1apgJp5h (9 Mar)
• dkvasnickajr: How about a small Swank server for @racketlang? https://t.co/ZbVDqC8Lsk #Racket #Vim #Emacs #Scheme (9 Mar)
• planetpython: Pypix: Machine Learning With Python http://t.co/quqMMIwIDF (9 Mar)
• Billare: Wow. Why are p-values de rigueur in science vs. CIs? Historical reasons due to skewness of non-central distributions. http://t.co/WgEgty8njH (8 Mar)
• michaelwaskom: On a mac and wanna know how many words something is? Copy it and then do pbpaste | wc -w in your terminal. (8 Mar)
• ptaoussanis: Okay, I’m all-in: Cljx is the way to do Clojure+ClojureScript https://t.co/X4viCauUJw It’s rough to get going, but it’s the only sane choice (8 Mar)
• rasbt: After mentioning scikit, here a short article about “Generating Machine Learning Models with Python’s Scikit-Learn” http://t.co/3dz2zlsp7u (8 Mar)
• SciPyTip: Scaling lessons learned at Dropbox (using Python) http://t.co/hiA55Dm4A3 (8 Mar)
• DashingD3js: #Python #Beginners #CoolThings » Beautiful Python: Some Cool Language Constructs and Tricks for Beginners - Part 1 http://t.co/WxhvmuBEIw (8 Mar)
• revodavid: Getting Started with Hidden Markov Models in R - new blog post from @revojoe http://t.co/0FKNjl3q7s #rstats (7 Mar)
• Stata: #NetCourse 101 and 151 start back up tomorrow! Convenient web-based courses for learning #Stata. Enroll today at http://t.co/w8KxNaFV7T (6 Mar)
• CompSciFact: FQL: A Functorial Query Language http://t.co/dEnHFuLKwu (6 Mar)
• rasbt: Python Class Attributes - An overly thorough guide. http://t.co/Q3BBf0GWKe http://t.co/ji0OyBt9pG (6 Mar)
• kwbroman: My next lecture: writing clear code (focusing on #rstats) http://t.co/p6EQENGcv3 http://t.co/xaBIVjoyqH (6 Mar)
• ogrisel: New random forests benchmarks by @iskander http://t.co/bT7KNNjC0l sklearn vs WiseRF vs CudaTree #machinelearning (5 Mar)
• kwbroman: I learned about \ifx in LaTeX, to allow versions of slides with dark or light backgrounds. https://t.co/5lMLp79QLL http://t.co/e4FqNWUKUF (5 Mar)
• planetclojure: Recommended Reading : Building a Database-backed Clojure Web App On Top of Heroku Cloud App Platform http://t.co/BtlNqtevmu (5 Mar)
• timelyportfolio: found this through #angularjs site; simply amazing http://t.co/G2RygDirbs drag fonts from your files and apply to any website (5 Mar)
• mojombo: Want to make animated GIF screencasts on Mac/Windows super easily? This app changed my life: http://t.co/fusH9tQEpJ (4 Mar)
• kaz_yos: #Emacs, #ESS and #R for Zombies http://t.co/ueuhVr0cLG (3 Mar)
• DataRobot: Machine learning explained in 10 pictures http://t.co/HEjPM0oj5e #machinelearning (3 Mar)
• HNTweets: Clear-Sans | A nice clean font from 01: https://t.co/x8rbGJm2eF Comments: https://t.co/4v8TSIvGNU (3 Mar)
• dancow: This JS visualization of pathfinding algorithms is awesome. Dijkstra u so funny: http://t.co/7GM9Bp6AjN (3 Mar)
• cpsievert: Animation of the Law of Large Numbers and repeated sampling with #shiny. Thanks @rstudioapp! http://t.co/XqkJ6ZAuSP #rstats (3 Mar)
• kaz_yos: #emacs All of alt, meta, super, hyper keys on Mac http://t.co/FrfiztYC2C http://t.co/uOb0Y01BWj (3 Mar)
• DrLabRatOry: Reading notes from last @swcarpentry session on student & teacher motivation, too good not to share: http://t.co/ESAdfZkrXh (3 Mar)
• emacs_knight: 2 and a half years after the last stable release, SLIME 2.4 is released http://t.co/42LfQ4OQfb #emacs #commonlisp (4 Mar)
• HNTweets: Implementing a JIT Compiled Language with Haskell and LLVM: http://t.co/aFuVl1LN7C Comments: https://t.co/PPjkZDvGD6 (4 Mar)
• M_T_Patterson: Stirling has a nice summary of a recent conference on measuring subjective well-being: http://t.co/KHlBP7Mo24 (3 Mar)
• WinVectorLLC: Please re-tweet,share: Zumel, Mount “Practical Data Science in R” preview now has all chapters! http://t.co/JUbHlLRTL5 #datascience (3 Mar)
• jedisct1: RT @rgaidot: JSON5 looks promising http://t.co/3fk3Ml8E06 (3 Mar)
• JeromyAnglim: I agree. What’s the “fuss over making your data public and accessible?” http://t.co/aMeG4iLtMy (3 Mar)
• jakevdp: Just released mpld3 v0.1: completely refactored JS & some cool new examples. Take a look! http://t.co/YUKrycF7MD https://t.co/xhJHXiVQNC (3 Mar)
• StrictlyStat: Really like this tutorial for git: http://t.co/jlosjSJGvJ (3 Mar)
• moorejh: FAQ for the new PLoS Data Policy http://t.co/S6nnX6QJXn #kudos #openaccess #publishing #research #scichat (3 Mar)
• jakevdp: So I heard you wanted linked brushing in matplotlib / mpld3. Here you go: http://t.co/OMSTJEq24p (3 Mar)
• mshron: I’m giving an hour-long webcast on March 13th to talk about Thinking with Data. It’s free! http://t.co/o6pas5WhoQ (3 Mar)
• blebeau11: Following my last #rcharts post with the raw Javascript and HTML for a slidy presentation: http://t.co/NfjciATKWv #rstats (3 Mar)
• simonw: My new favourite Python module: tqdm - a function that adds a command-line progress bar to anything you can iterate https://t.co/iSa905NbRw (3 Mar)
• siah: Conditional Random Fields: An Introduction http://t.co/HVKCaM3UOp (3 Mar)
• ramnath_vaidya: Convert R Markdown to #IPython Notebook http://t.co/w0YS21mnCh. Short writeup here https://t.co/lHhiN9oJlw #rstats (3 Mar)
• ContinuumIO: Check out new categorical axes plots with @BokehPlots! http://t.co/pAkwvRHvp0 #Python #PyData #Bokeh http://t.co/oGey14Keyu (3 Mar)
• timelyportfolio: rough prototype to use pivot.js from #rCharts example: http://t.co/aZOHU38a1D repo: https://t.co/BFt4WVl2wK (3 Mar)
• BestGit: Magit just got git-flow support, nice. #emacs #git-flow https://t.co/YushyXC7xc (3 Mar)
• vlandham: @arnicas quicktime and gifsicle : https://t.co/b21n7pRkIv - works pretty well! (3 Mar)
• communicating: Wish I had known about this sooner - Gitsh is an interactive dedicated shell for Git: https://t.co/V4AH8P8s56 (3 Mar)
• KirkDBorne: Why #Medicine Needs #BigData: http://t.co/J1WRkEiI7r » Medical Informatics = #DataScience for Science (2 Mar)
• scheidegger: Go read @moritz_stefaner stellar post on why “story-telling” in vis is ultimately a wrong idea. Worlds, not Stories: http://t.co/3cvsmn8KMv (2 Mar)
• benhowdle: New on the blog: http://t.co/ajQjCLtYBz “Building a Backendless Web App in 2 Hours” (2 Mar)
• strataconf: #Strataconf video interview: @hadleywickham of @rstudioapp on exploring vs. communicating #BigData w/ @jsteeleeditor http://t.co/kkdHiXgbWT (2 Mar)
• Atabey_Kaygun: Is Julia the Future for Big Data Analytics? http://t.co/qOk0fRbjIz (2 Mar)
• Atabey_Kaygun: MITx and HarvardX release MOOC datasets and visualization tools http://t.co/7Ji02Tad4z (via @MITnews) http://t.co/ReLsflBhpZ (2 Mar)
• StatModeling: New post: “We are moving from an era of private data and public analyses to one of public data and private analyses. http://t.co/tmLWYCduJH (1 Mar)
• fperez_org: “peer review is hindering science […] it has become a completely corrupt system”, S. Brenner, 2002 Nobel @LizDzeng http://t.co/SFoZlcxoqe (1 Mar)
• dataJujitsu: Book review: Big Data Analytics with #Rstats and Hadoop http://t.co/7HXkrarwv4 Some good information, little R code and lots of Jargon (1 Mar)
• JohnDCook: Software find of the day: http://t.co/lmBbdtLQgV Mercurial and Git client for Windows and Mac (1 Mar)
• ramnath_vaidya: @jaredlander Here it is http://t.co/WWdVWSONnS. It requires versions of rCharts/Slidify that I haven’t pushed to github yet. (1 Mar)