Per the Part 1 post, we now have two data files – one with storm-level information and another larger file with path-level information. Now let’s build some visualizations and try to answer our questions about Atlantic hurricanes. For my workbook, I joined the two files on the field … Read the rest
I live in Jacksonville, FL, and as of this writing most of the state’s residents are anxiously watching a monster hurricane named Irma execute a slow turn off the Cuban coast and toward the Keys, Naples, and Tampa. The west side of the state appears likely to bear the brunt … Read the rest
I was playing around recently with the Social Security baby names historical data set. You can download it either at the state or national level, and it goes back well over a hundred years. It lists all names and frequencies except for any where the number is under 5. Those … Read the rest
The longer I work as a data analyst the more I appreciate screen scraping, especially in cases where I’ll need to pull the same data more than once.
The matchup guide for this year’s tournament is live. The method is similar to last year’s dashboard – scraped all the data with python scripts, shaped and computed the metrics in Alteryx, and then visualized the results in Tableau Public.
Using a pair of python scripts, I scraped the user rating distributions of over 34,000 IMDb films stretching from 1915 to February of 2017. This included just under 5.8 billion individual ratings on IMDb’s 1 to 10 scale for all movies in that timespan. Rating distributions can be a useful … Read the rest
For this year’s NCAA rankings, I’ve set up python web crawlers to grab Joe Lunardi’s latest bracket projections as well as game log statistics from sports-reference.com. From there, I built an Alteryx workflow recomputing rankings to reflect margin of victory and to reward stronger performance in recent games. Methodology … Read the rest
I follow Andy Kriebel and Eva Murray’s Makeover Monday series on Twitter where people are encouraged to remake data visualizations from the news. This week’s data source was a meaty one, an export of over 30,000 tweets courtesy of the Trump Twitter Archive.
A big part of doing analysis … Read the rest
Ever wondered what the temperature data progression looks like for a 17-hour pork shoulder or a 15-hour brisket? As a backyard barbecue nerd, I know I have, so I captured the data and visualized the results. Background and process writeup below.
When I was in Austin last fall for the … Read the rest
I’ve been learning the basics of D3.js recently and decided to try my hand at chord diagrams. It’s a niche chart type with limited utility, but for a first foray, I took the chart name literally and plotted the chord-to-chord movements in David Bowie’s Life on Mars. It seemed … Read the rest