R for Journalists
Tools for using and learning R, mostly for computational and data journalists, but everyone's welcome!
Curated by M. Edward (Ed) Borasky
Quandl is the easiest way to find data on the internet. It offers millions of free and open financial, economic, and social datasets, aggregated from hundreds of top sources, in a user friendly format, including options for embeddable charts and data transformations.
In this interactive tutorial you will learn how to effortlessly pull any of Quandl's data into R for quick and easy analysis!
In this course you are introduced to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
The course was originally developed as a complement to the similarly-titled Coursera course, and based on the material covered in the open-source book OpenIntro Statistics (Second Edition). So if you prefer to go through the material at your own pace and speed, the latter will be a perfect source for supplementary material.
No formal background is required for this course, but some basic mathematical skills will come in handy. A genuine interest in data analysis is a plus!
With over 2 million users worldwide R is rapidly becoming the leading programming language in statistics and data science. Every year, the number of R users grows with over 40%, and an increasing number of organizations start to use it in their day-to-day activities.
In this introduction to R, you will master the basics of this beautiful open source language. We'll take you on trips to Las Vegas and galaxies far far away. Basic topics such as factors, lists and data frames will be covered. After finishing this introductory R course, you'll master some very valuable R skills and are ready to undertake your first very own data analysis.
This course is aimed at people who'd like to start using R for their study assignments, research projects or professional endeavors. No previous experience in programming languages or data science is required.
Hadley Wickham (perhaps you’ve heard of his work) presented a 2 hour workshop on dplyr at this year’s useR! conference at UCLA. This tutorial was definitely a highlight of the week-long conference for me, and working on this tutorial video has also made me very appreciative of how versatile the dplyr package can be. It clearly is the chef’s knife of data science tools. Hadley’s presentation was just under 2 hours long, and the edited footage where we omitted breaks gives us 90 minutes of wisdom