In early 2017, The New York Times published a piece titled "
A Crack in an Antarctic Ice Shelf Grew 17 Miles in the Last Two Months," examining a possible split in an Antarctic ice shelf. While it wasn't an analysis of a huge spreadsheet or thousands of tweets, the article was full of detailed numbers, illustrated graphics, and satellite imagery outlining the ice shelf's precarious situation.
As an environmental journalist, my previous work has mostly centered on reporting metrics from the oil industry's operations in the Gulf of Mexico. This information is important to millions of residents of North America but always fails to catch their eye. I was fascinated by how the Times took seemingly uninteresting data - the miles per day a crack travels, or the the amount of shelf support a location has - and turned it into a compelling narrative.
I am especially interested in a large, 10GB dataset of industry regulations that is published each year. While it won't fit in Excel, I am have been told that using Python would be an effective way to analyze this dataset. With the tools I learn in the Lede Program, I will finally be able to open up and explain this data to all residents of the Gulf.