Monthly Archives: March 2017

Data Science Job Report 2017: R Passes SAS, But Python Leaves Them Both Behind

March 1, 2017
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Data Science Job Report 2017: R Passes SAS, But Python Leaves Them Both Behind

I’ve just updated another section of The Popularity of Data Science Software. It is reproduced below to save you the trouble of reading the entire article. If your organization is looking for training in the R language, you might consider my … Continue reading →

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Using PostgreSQL and shiny with a dynamic leaflet map: monitoring trash cans

March 1, 2017
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Using PostgreSQL and shiny with a dynamic leaflet map: monitoring trash cans

When there is increased social activity, trash cans can get full quicker. On the contrary, during very cold weather, trash cans can take one or a couple of more days to get full. Therefore, knowing when trash cans are full is important to pick them up right away rather than waiting for a specific day PostgreSQL and shiny with...

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Three R Shiny tricks to make your Shiny app shines (3/3): Buttons to delete, edit and compare Datatable rows

March 1, 2017
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Three R Shiny tricks to make your Shiny app shines (3/3): Buttons to delete, edit and compare Datatable rows

In this tutorials sequence, we are going to see three tricks to do the following in a Shiny app: Add Next and Previous buttons to navigate in a tabBox Build a non completely collapsible sidebar to keep the icon visible on collapse Add button on a datatable output to delete/modify/ do an action on a

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Playing with dimensions: from Clustering, PCA, t-SNE… to Carl Sagan!

March 1, 2017
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Playing with dimensions: from Clustering, PCA, t-SNE… to Carl Sagan!

Explore the intersection of concepts like dimension reduction, clustering, data preparation, PCA, HDBSCAN, k-NN, SOM, deep learning...and Carl Sagan!

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R-Lab #1: hands on R code! | Milan, March 14th

March 1, 2017
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R-Lab #1: hands on R code! | Milan, March 14th

Great news for the MilanoR community: we are launching R-Lab, a monthly R project of co-working with R on real data science projects. Either if you are an R expert, a beginner, or you just curious, you are welcome to join us! The first event will be on March 14th, in Mikamai, Milano. We will introduce the R-Lab project and...

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Sentiment Analysis of The Lord Of The Rings with tidytext

March 1, 2017
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Sentiment Analysis of The Lord Of The Rings with tidytext

You got me thinking about Watson and its unprecedented flexibility in analyzing different data sources (at least according to IBM). So how difficult it would be to analyse sentiment of one of my favorites books using R? Pretty easy actually - all thanks to new package tidytext by Julia Silge and David Robinson… The tidy text format Tidy text format is...

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R Quick tip: Microsoft Cognitive Services’ Text Analytics API

March 1, 2017
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R Quick tip: Microsoft Cognitive Services’ Text Analytics API

Today in class, I taught some fundamentals of API consumption in R. As it was aligned to some Microsoft content, we first used HaveIBeenPwned.com‘s API and then played with Microsoft Cognitive Services‘ Text Analytics API. This brief post overviews what you need to get started, and how you can chain consecutive calls to these APIs … Continue reading "R...

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ccafs – client for CCAFS General Circulation Models data

March 1, 2017
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ccafs – client for CCAFS General Circulation Models data

I've recently released the new package ccafs, which provides access to data from Climate Change, Agriculture and Food Security (CCAFS; http://ccafs-climate.org/) General Circulation Models (GCM) data. GCM's are a particular type of climate model, used for weather forecasting, and climate change forecasting - read more at https://en.wikipedia.org/wiki/General_circulation_model. ccafs falls in the data client camp - its focus is on getting users data - many rOpenSci packages fall...

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