Monthly Archives: April 2019

Data Science Software Used in Journals: Stat Packages Declining (including R), AI/ML Software Growing

April 1, 2019
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Data Science Software Used in Journals: Stat Packages Declining (including R), AI/ML Software Growing

In my neverending quest to track The Popularity of Data Science Software, it’s time to update the section on Scholarly Articles. The rapid growth of R could not go on forever and, as you’ll see below, its use actually declined … Continue reading →

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Gravity Falls and Tidy Data Principles (Part 2)

April 1, 2019
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Gravity Falls and Tidy Data Principles (Part 2)

Motivation The first part left an open door to analyze Gravity Falls contents using tf-idf, bag-of-words or some other NLP techniques. Here I’m also taking a lot of ideas from Julia Silge’s blog. Note: If some images appear too small on your screen you can open them in a new tab to show them in their original size. Term Frequency The most basic...

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A unified syntax for accessing models’ information

April 1, 2019
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The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, this diversity makes it hard for developpers that want to create tools that work with different types of models. Indeed, the way to access models’ internal information (such as parameters names, formulae, data, etc.) is...

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A unified syntax for accessing models’ information

April 1, 2019
By

The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, this diversity makes it hard for developpers that want to create tools that work with different types of models. Indeed, the way to access models’ internal information (such as parameters names, formulae, data, etc.) is...

Read more »

Getting your toes wet in R: Hydrology, meteorology, and more

Getting your toes wet in R: Hydrology, meteorology, and more

Importance of Hydrology Given that liquid water is essential to life on Earth, water research cuts across numerous disciplines including hydrology, meteorology, geography, climate science, engineering, ecology, and more. Numerous R packages have emerged from this diversity of approaches, and we recently gathered many of them into a new rOpenSci task view which we broadly titled ‘Hydrology’ and published to...

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A unified syntax for accessing models’ information

April 1, 2019
By

The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, this diversity makes it hard for developpers that want to create tools that work with different types of models. Indeed, the way to access models’ internal information (such as parameters names, formulae, data, etc.) is...

Read more »

Musings on missing data

April 1, 2019
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Musings on missing data

I’ve been meaning to share an analysis I recently did to estimate the strength of the relationship between a young child’s ability to recognize emotions in others (e.g. teachers and fellow students) and her longer term academic success. The study itself is quite interesting (hopefully it will be published sometime soon), but I really wanted to write about it here...

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Data Science R&D at TD Ameritrade

April 1, 2019
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Data Science R&D at TD Ameritrade

Hugo Bowne-Anderson, the host of DataFramed, the DataCamp podcast, recently interviewed Sean Law, a Senior Applied Researcher and Data Scientist at TD Ameritrade. Introducing Sean Law Hugo: Hi there, Sean, and welcome to DataFramed. Sean: ...

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Bingo analysis, a tutorial in R

April 1, 2019
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Bingo analysis, a tutorial in R

I'm toying with the idea of writing a book about statistical analyses of classic games. The target audience would be mathematically interested laypeople, much like Jeffrey Rosenthal's book Struck by Lightning ( https://www.amazon.ca/Struck-Lightning-Jeffrey-S-Rosenthal/dp/0006394957 ). The twist would be that chapter would contain step-by-step R code or Python code so that the reader could do the same analysis and make...

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One week EARL London abstract extension – 8 April

April 1, 2019
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Due to quite a few panicked email requests over the weekend we have decided to extend the EARL London abstract deadline until 8 April.  Thank you so much to all the people that have already submitted, we can’t wait to look through all of the brilliant submissions. Submit your abstract here.

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