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Data Driven Journalism

Data Driven Journalism
About the project is a hub for news and resources from the community of journalists, editors, designers and developers who use data to support journalism. The website is part of an European Journalism Centre initiative dedicated to accelerating the diffusion and improving the quality of data journalism around the world. We also run the online course Doing Journalism with Data as well as the School of Data Journalism, and are behind the acclaimed Data Journalism Handbook. This intiative receives partial funding from the Dutch Ministry of Education, Culture and Science. Join the mailinglist

Related:  Data JournalismData journalismCOPU - Periodismo de datos

Discovering Gale Crater: A VR experience from the L.A. Times Best experienced over a wifi connection Loading initial data Controls: W / S: Forwards / Backwards A / D: Left / Right R / F: Up / Down Q / E: Roll left / right Up / Down: Pitch up / down Left / Right: Yaw left / right Shift: Speed up By Armand Emamdjomeh Take a virtual reality audio tour of the Gale Crater, including geological features and areas that appear to have been carved by flowing water. Narrated by Fred J.

Top ten ways to clean your data - Excel You don't always have control over the format and type of data that you import from an external data source, such as a database, text file, or a Web page. Before you can analyze the data, you often need to clean it up. Fortunately, Excel has many features to help you get data in the precise format that you want. Sometimes, the task is straightforward and there is a specific feature that does the job for you. For example, you can easily use Spell Checker to clean up misspelled words in columns that contain comments or descriptions. Or, if you want to remove duplicate rows, you can quickly do this by using the Remove Duplicates dialog box.

Data Visulization Course Materials This resource page features course content from the Knight Center for Journalism in the America's massive open online course (MOOC), titled "Data Visualization for Storytelling and Discovery." The four-week course, which was powered by Google, took place from June 11 to July 8, 2018. We are now making the content free and available to students who took the course and anyone else who is interested in learning how to create data visualizations to improve their reporting and storytelling. Discovering Gale Crater: How we did it Remember when virtual reality first became a "thing?" We loved Snow Crash and Lawnmower Man. We were pumped. Then we waited — for 20 years. Now, we finally get to play in that sandbox.

Jupyter Notebook Viewer The first three lines of code import libraries we are using and renames to shorter names. Matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. We will use it for basic graphics Numpy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array objectsophisticated (broadcasting) functionstools for integrating C/C++ and Fortran codeuseful linear algebra, Fourier transform, and random number capabilities Florence Nightingale is a Design Hero - Nightingale - Medium Founder of modern nursing. Feminist champion. Celebrity entrepreneur. Passionate statistician. Political operator. Data visualization pioneer.

How politicians poisoned statistics In January 2015, a few months before the British general election, a proud newspaper resigned itself to the view that little good could come from the use of statistics by politicians. An editorial in the Guardian argued that in a campaign that would be “the most fact-blitzed in history”, numerical claims would settle no arguments and persuade no voters. Not only were numbers useless for winning power, it added, they were useless for wielding it, too. How to Use Excel’s Descriptive Statistics Tool - dummies By Stephen L. Nelson, E. C. Nelson Perhaps the most common Data Analysis tool that you’ll use in Excel is the one for calculating descriptive statistics. To see how this works, take a look at this worksheet.

How to Filter in R: A Detailed Introduction to the dplyr Filter Function Data wrangling. It’s the process of getting your raw data transformed into a format that’s easier to work with for analysis. It’s not the sexiest or the most exciting work. In our dreams, all datasets come to us perfectly formatted and ready for all kinds of sophisticated analysis! In real life, not so much. It’s estimated that as much as 75% of a data scientist’s time is spent data wrangling. These charts clearly show how some Olympic swimmers may have gotten an unfair advantage Denmark's Pernille Blume won the gold medal in the 50-meter freestyle swimming in Lane 4 at the 2016 Summer Olympics. The rest of the women in the final race finished in descending order according to their lane number. (Dominic Ebenbichler/Reuters) A few years ago, researchers from Indiana University discovered a disturbing pattern at the 2013 Swimming World Championships in Barcelona. According to the lap-time data, athletes assigned to the outer lanes of the pool were consistently swimming faster in one direction than the other.