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Data Science Tutorials

Develop your data science skills with tutorials in our blog. We cover everything from intricate data visualizations in Tableau to version control features in Git.
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R Programming

Algorithmic Trading in R Tutorial

In this R tutorial, you'll do web scraping, hit a finance API and use an htmlwidget to make an interactive time series chart to perform a simple algorithmic trading strategy

Ted Kwartler

February 9, 2017

R Programming

Exploring H-1B Data with R: Part 3

Learn how to geocode locations and map them with R.
Ted Kwartler's photo

Ted Kwartler

January 26, 2017

R Programming

Exploring H-1B Data with R: Part 2

Learn even more about exploratory data analysis with R in the second part of the "Exploring H-1B Data" tutorial series
Ted Kwartler's photo

Ted Kwartler

January 19, 2017

R Programming

Web Scraping and Parsing Data in R | Exploring H-1b Data Pt. 1

Learn how to scrape data from the web, preprocess it and perform a basic exploratory data analysis with R
Ted Kwartler's photo

Ted Kwartler

January 12, 2017

R Programming

15 Easy Solutions To Your Data Frame Problems In R

Discover how to create a data frame in R, change column and row names, access values, attach data frames, apply functions and much more.
Karlijn Willems's photo

Karlijn Willems

January 10, 2017

Data Science

Learn Data Science - Resources for Python & R

Data science resources you haven't considered (yet) - The best projects, tutorials, talks, podcasts, webinars, books, and much more to learn data science.
Karlijn Willems's photo

Karlijn Willems

September 21, 2016

R Programming

Text Mining in R: Are Pokémon GO Mentions Really Driving Up Stock Prices?

Recreate your own news trends feature in R, mining Pokémon GO data from Google News Trends and Yahoo Finance.
Ted Kwartler's photo

Ted Kwartler

September 2, 2016

R Programming

Driving R Adoption in Your Company

Build a better R culture at your company with an internal meetup!
Jacob Moody's photo

Jacob Moody

August 5, 2016

Python

Preprocessing in Data Science (Part 3): Scaling Synthesized Data

You can preprocess the heck out of your data but the proof is in the pudding: how well does your model then perform?
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Hugo Bowne-Anderson

May 10, 2016