100 “must read” R-bloggers’ posts for 2015

January 20, 2016

The site R-bloggers.com is now 6 years young. It strives to be an (unofficial) online news and tutorials website for the R community, written by over 600 bloggers who agreed to contribute their R articles to the website. In 2015, the site served almost 17.7 million pageviews to readers worldwide.

In celebration to R-bloggers’ 6th birth-month, here are the top 100 most read R posts written in 2015, enjoy:

  1. How to Learn R
  2. How to Make a Histogram with Basic R
  3. How to Make a Histogram with ggplot2
  4. Choosing R or Python for data analysis? An infographic
  5. How to Get the Frequency Table of a Categorical Variable as a Data Frame in R
  6. How to perform a Logistic Regression in R
  7. A new interactive interface for learning R online, for free
  8. How to learn R: A flow chart
  9. Learn Statistics and R online from Harvard
  10. Twitter’s new R package for anomaly detection
  11. R 3.2.0 is released (+ using the installr package to upgrade in Windows OS)
  12. What’s the probability that a significant p-value indicates a true effect?
  13. Fitting a neural network in R; neuralnet package
  14. K-means clustering is not a free lunch
  15. Why you should learn R first for data science
  16. How to format your chart and axis titles in ggplot2
  17. Illustrated Guide to ROC and AUC
  18. The Single Most Important Skill for a Data Scientist
  19. A first look at Spark
  20. Change Point Detection in Time Series with R and Tableau
  21. Interactive visualizations with R – a minireview
  22. The leaflet package for online mapping in R
  23. Programmatically create interactive Powerpoint slides with R
  24. My New Favorite Statistics & Data Analysis Book Using R
  25. Dark themes for writing
  26. How to use SparkR within Rstudio?
  27. Shiny 0.12: Interactive Plots with ggplot2
  28. 15 Questions All R Users Have About Plots
  29. This R Data Import Tutorial Is Everything You Need
  30. R in Business Intelligence
  31. 5 New R Packages for Data Scientists
  32. Basic text string functions in R
  33. How to get your very own RStudio Server and Shiny Server with DigitalOcean
  34. Think Bayes: Bayesian Statistics Made Simple
  35. 2014 highlight: Statistical Learning course by Hastie & Tibshirani
  36. ggplot 2.0.0
  37. Machine Learning in R for beginners
  38. Top 77 R posts for 2014 (+R jobs)
  39. Introducing Radiant: A shiny interface for R
  40. Eight New Ideas From Data Visualization Experts
  41. Microsoft Launches Its First Free Online R Course on edX
  42. Imputing missing data with R; MICE package
  43. Variable Importance Plot” and Variable Selection
  44. The Data Science Industry: Who Does What (Infographic)
  45. d3heatmap: Interactive heat maps
  46. R + ggplot2 Graph Catalog
  47. Time Series Graphs & Eleven Stunning Ways You Can Use Them
  48. Working with “large” datasets, with dplyr and data.table
  49. Why the Ban on P-Values? And What Now?
  50. Part 3a: Plotting with ggplot2
  51. Importing Data Into R – Part Two
  52. How-to go parallel in R – basics + tips
  53. RStudio v0.99 Preview: Graphviz and DiagrammeR
  54. Downloading Option Chain Data from Google Finance in R: An Update
  55. R: single plot with two different y-axes
  56. Generalised Linear Models in R
  57. Hypothesis Testing: Fishing for Trouble
  58. The advantages of using count() to get N-way frequency tables as data frames in R
  59. Playing with R, Shiny Dashboard and Google Analytics Data
  60. Benchmarking Random Forest Implementations
  61. Fuzzy String Matching – a survival skill to tackle unstructured information
  62. Make your R plots interactive
  63. R #6 in IEEE 2015 Top Programming Languages, Rising 3 Places
  64. How To Analyze Data: Seven Modern Remakes Of The Most Famous Graphs Ever Made
  65. dplyr 0.4.0
  66. Installing and Starting SparkR Locally on Windows OS and RStudio
  67. Making R Files Executable (under Windows)
  68. Evaluating Logistic Regression Models
  69. Awesome-R: A curated list of the best add-ons for R
  70. Introducing Distributed Data-structures in R
  71. SAS vs R? The right answer to the wrong question?
  72. But I Don’t Want to Be a Statistician!
  73. Get data out of excel and into R with readxl
  74. Interactive R Notebooks with Jupyter and SageMathCloud
  75. Learning R: Index of Online R Courses, October 2015
  76. R User Group Recap: Heatmaps and Using the caret Package
  77. R Tutorial on Reading and Importing Excel Files into R
  78. R 3.2.2 is released
  79. Wanted: A Perfect Scatterplot (with Marginals)
  80. KDD Cup 2015: The story of how I built hundreds of predictive models….And got so close, yet so far away from 1st place!
  81. Analyzing 1.1 Billion NYC Taxi and Uber Trips, with a Vengeance
  82. 10 Top Tips For Becoming A Better Coder!
  83. James Bond movies
  84. Modeling and Solving Linear Programming with R – Free book
  85. Scraping Web Pages With R
  86. Why you should start by learning data visualization and manipulation
  87. R tutorial on the Apply family of functions
  88. The relation between p-values and the probability H0 is true is not weak enough to ban p-values
  89. A Bayesian Model to Calculate Whether My Wife is Pregnant or Not
  90. First year books
  91. Using rvest to Scrape an HTML Table
  92. dplyr Tutorial: verbs + split-apply
  93. RStudio Clone for Python – Rodeo
  94. Time series outlier detection (a simple R function)
  95. Building Wordclouds in R
  96. Should you teach Python or R for data science?
  97. Free online data mining and machine learning courses by Stanford University
  98. Centering and Standardizing: Don’t Confuse Your Rows with Your Columns
  99. Network analysis with igraph
  100. Regression Models, It’s Not Only About Interpretation 

    (oh hack, why not include a few more posts…)

  101. magrittr: The best thing to have ever happened to R?
  102. How to Speak Data Science
  103. R vs Python: a Survival Analysis with Plotly
  104. 15 Easy Solutions To Your Data Frame Problems In R
  105. R for more powerful clustering
  106. Using the R MatchIt package for propensity score analysis
  107. Interactive charts in R
  108. R is the fastest-growing language on StackOverflow
  109. Hash Table Performance in R: Part I
  110. Review of ‘Advanced R’ by Hadley Wickham
  111. Plotting Time Series in R using Yahoo Finance data
  112. R: the Excel Connection
  113. Cohort Analysis with Heatmap
  114. Data Visualization cheatsheet, plus Spanish translations
  115. Back to basics: High quality plots using base R graphics
  116. 6 Machine Learning Visualizations made in Python and R
  117. An R tutorial for Microsoft Excel users
  118. Connecting R to Everything with IFTTT
  119. Data Manipulation with dplyr
  120. Correlation and Linear Regression
  121. Why has R, despite quirks, been so successful?
  122. Introducing shinyjs: perform common JavaScript operations in Shiny apps using plain R code
  123. R: How to Layout and Design an Infographic
  124. New package for image processing in R
  125. In-database R coming to SQL Server 2016
  126. Making waffle charts in R (with the new ‘waffle’ package)
  127. Revolution Analytics joins Microsoft
  128. Six Ways You Can Make Beautiful Graphs (Like Your Favorite Journalists)


p.s.: 2015 was also a great year for R-users.com, a job board site for R users. If you are an employer who is looking to hire people from the R community, please visit this link to post a new R job (it’s free, and registration takes less than 10 seconds). If you are a job seekers, please follow the links below to learn more and apply for your job of interest (or visit previous R jobs posts).



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