Articles by paoloeusebi

Causal inference with DAGs in R

August 6, 2019 | paoloeusebi

Directed cyclical graphs (DAGs) are a powerful tool to understand and deal with causal inference. The book “Causal inference in statistics: a primer” is a useful reference to start, authored from Pearl, Glymour, and Jewell. Directed cyclical graphs (DAGs) are a powerful tool to understand and deal with causal inference. ...
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R – Paolo Eusebi 2019-06-24 03:28:36

June 24, 2019 | paoloeusebi

Wow! I was listening a recent episode of the “Storytelling with data” podcast by Cole Nussbaumer Knaflic. It was an interview with Alberto Cairo who came up recommending an awesome tool for data visualization: iNZight! Interestingly iNZight is entirely based on R code and in its latest releases it speaks ...
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Using R in the pharmaceutical industry

March 27, 2019 | paoloeusebi

Although SAS is the main player in the pharmaceutical industry, R is gaining popularity. In this post I will just mention some initiatives, documents and podcast episodes dealing with using R in pharmaceutical research and development programs. Recently, it was a pleasure to listen the episode of the Effective Statistician ... [Read more...]

Working with big SAS datasets using R and sparklyr

February 13, 2019 | paoloeusebi

In general, R loads all data into memory while SAS allocates memory dynamically to keep data on disk. This makes SAS a better solution for handling very large datasets. I often need to work with large SAS data files that are prepared in the information system of my department. However, ...
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ELK+R Stack

January 24, 2019 | paoloeusebi

Elasticsearch is a search engine based on the Lucene library. It provides a distributed full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is becoming the bigger player in the technology for documents search in the noSQL space and is actually experiencing a great development phase (6 ...
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My fi(R)st day with Jupyter Lab

October 25, 2018 | paoloeusebi

Today was my first day with Jupyter Lab . I knew about Jupyter Lab listening episode 44 of  DataFramed, the DataCamp‘s official podcast presented by Hugo Bowne-Anderson. In this episode, Project Jupiter was described in the context of interactive computing by Brian Granger, professor of physics and data science at Cal ...
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