Creating Maps with Google Fusion Tables
If you have not read the Data Viz module from Fundamentals of Multimedia Storytelling, or need a refresher, you should do so. The link to the module can be found on the Resources page of this blog. The module will teach you how to create a Google Fusion Table map. Keep in mind that the tutorial uses the “classic view”. You can toggle between the new look or the “classic” view in the upper right corner. The features between the two are nearly identical, but the interface is just a little different. Continue reading Layering Maps
While the populous states of Texas and California reported the most on-the-job fatalities, North Dakota topped the death list when adjusted for population, according to 2011 data released by the Bureau of Labor Statistics. North Dakota’s occupational fatality rate was more than three times the national average.
Source: Bureau of Labor Statistics
Often the data that you get needs cleaning. Misspellings and data entry errors need to be fixed. Google Refine is a powerful tool that can clean datasets quickly. It also allows you to look at your data in different ways, filtering the categories. These different filters are known as “facets” in Google Refine.
Continue reading Refine Walk-Through
Delimiters and Functions with Flu Data
To review today’s spreadsheet exercise, download the data from Google’s Flu Trends. The data is just text with a lot of commas. The goal is to get your data into tidy rows and columns in a spreadsheet, so you can start looking for interesting patterns or trends.
Continue reading Spreadsheet Walk-through
In class, we used Matt S.’s data on military deaths for our Pivot Table lesson. In this walk-through, we’ll use Olympic athlete data from London’s 2012 summer olympics. Use Guardian London Olympic data — look for the “download the data” link and be sure to save a copy so you can edit it.
In Fundamentals, we used formulas to find all the country names and count the unique athlete names by country. You can do the same thing with pivot tables in Excel, Google Spreadsheets or LibreOffice Calc. The details will between software, but the basic steps are the same. Follow these steps to look at the data in pivot tables on Google Spreadsheets:
Continue reading Pivot Table Walk-through
Homework Week 1 (Due Sep 11)
Find two datasets that interest you. You’re looking for raw data, not visualizations of data. For each data set, tell us the following in not more than 100 words:
- Describe the data — what are we looking at?
- Explain why it is interesting — who cares?
- Explain the provenance — who collected this data, when? Where?
- Provide a link — how can someone get to this data? (be sure to test your URL and make sure it reliably takes you back to the data. Otherwise, find the best URL and give instructions from there.)
Begin a scrapbook on WordPress, Tumblr, Pinterest or any blog or aggregation service. If you want to use a specific tag or category on an existing blog, that’s fine, too.
Read Cairo: The Functional Art, Reading part 1: pages 25-31, 36-44, on thinking through a visualization as a tool for the reader; what graphical form best serves the goal? On e-reserve in the Library.
Make sure that Firefox is installed on your computer, with both the Web Developer Toolbar and Firebug plugins.
Email your dataset URLs and scrapbook URL to both professors under the subject “Homework Week 1″.
Google Workshops produced a map of Small Arms and Ammunition Trade Data from 1992 to 2010. It’s beautiful and mesmerizing, but fails at enabling the one task users will most likely want to do–easily compare countries. Data is listed for each country, forcing readers to remember the information and make the comparisons in their head. The vertical scale is not constant, making comparisons even harder. Finally, if this were a news story, we would need some guidance to the most interesting and newsworthy comparisons.