Most liked R-bloggers’ posts from last week (2018-10-07 till 2018-10-13 – based on twitter)

I’ve recently added new bloggers to the site, leading to an influx of posts (142 new posts on the site, just last week). And while I love R, I do not have the time to read them all. Luckily, these posts are also published on R-bloggers twitter page, where over 62K followers see the new posts and decide if to give them a “like” or not. So I thought it might be helpful to sort all of last weeks posts (that got at least 15 likes), just to make sure I will not miss out on reading a particular popular post. I’m posting it here in the hopes that this would be helpful to others as well. Here is the list:  
Title Number of likes
R and Python: How to Integrate the Best of Both into Your Data Science Workflow 223
How to build your own Neural Network from scratch in R 209
Introduction to ggplot2 110
Making Calendar with ggplot + Moon Phase Calendar for fun 105
How to import a directory of csvs at once with base R and data.table. Can you guess which way 99
Geocoding with ggmap and the Google API 99
neuralnet: Train and Test Neural Networks Using R 86
Some R Guides: tidyverse and data.table Versions 80
Optimize your R Code using Memoization 79
The Economist’s Big Mac Index is calculated with R 78
Running the Same Task in Python and R 76
Working with panel data in R: Fixed vs. Random Effects (plm) 76
New Course: Mixture Models in R 69
In regression, we assume noise is independent of all measured predictors. What happens if it 68
The “Gold Standard” of Data Science Project Management 62
First steps of data exploration and visualization with Tidyverse 61
Monte Carlo techniques to create counterfactuals 52
Announcing MCHT: An R Package for Bootstrap and Monte Carlo Hypothesis Testing 51
Modeling Airbnb prices 49
RStudio 1.2 Preview: Reticulated Python 48
Applications of DAGs in Causal Inference 45
Scraping Tables from Wikipedia for Visualizing Climate Data 43
Machine Learning as a Service 42
Mining Sent Email for Self-Knowledge 39
Data Science With R Course Series – Week 4 38
New Course: Developing R Packages 37
Partially additive (generalized) linear model trees 36
Open Workshop: Deep Learning in R and Keras, November 14th in Frankfurt 34
Project Euler in R 34
Reading in an epub (ebook) file with the pubcrawl package 33
Deep Learning with Keras – using R (talk) 33
How R gets built on Windows 32
Prettify your Shiny Tables with DT: Exercises 32
Experiments with count(), tally(), and summarise(): how to count and sum and list elements of 32
RStudio 1.2 Preview: C/C++ and Rcpp 31
Dashboard 2.0 30
Add value to your visualizations in R 29
Big Data-2: Move into the big league:Graduate from R to SparkR 28
Analyzing the Greatest Strikers in Football II: Visualizing Data 28
Custom set up of keras and TensorFlow for R and Python 28
Using R to help plan the future of transport. Join MünsteR for our next meetup! 27
Parsing Metadata with R – A Package Story 27
The myth of interpretability of econometric models 26
Combining automatically factor levels in R 26
Fast Random Numbers for R with dqrng 25
Review: Excel TV’s Data Science with Power BI and R 24
Bayesian Experimental Design through An Drug Study Example 24
Open Workshop: Data Visualization in R and ggplot2, November 8th in Frankfurt 24
Testing Entry with R Rmarkdown File 24
Drilling into non-rectangular data with purrr 24
dqsample: A bias-free alternative to base::sample() 23
Andrew Gelman discusses election forecasting and polling. (Transcript) 23
Using UMAP in R with rPython 23
Are you buying an apartment? How to hack competition in the real estate market with data 22
New package in CRAN: PkgsFromFiles 18
A question and an answer about recoding several factors simultaneously in R 18
Acquiring data for language research (3/3): web scraping 17
Make more useless packages! 17
Subsetting in the presence of NAs 16
daqana’s R style guide is online 15
The world (population) is changing 15
Understanding the limitations of group-level inequality data by @ellis2013nz 15

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