Monday, August 29, 2016

Aggregate homeownership rates for different countries

Quartz has an interesting piece on why most Germans prefer renting instead of buying their homes. (via Simon Kuestenmache). The data in this chart is a bit outdated but homeownership rate was still relatively low in Germany in 2013, at 43%. In Brazil, this rate was 75% in the year 2011.


Friday, August 26, 2016

Most popular R packages in the tweetosphere

David Robinson has done a great work scraping twitter data to find the most popular packages in R based on the #7FavPackages hashtag.

My personal take: a lot of people don't know what they're missing out with the package data.table, which I would place in top1 in my list.

In short, data.table has extremely simple syntax and unprecedented speed when working with large datasets (it takes me just a few seconds to generate several aggregated columns from a dataset with ~200 million rows).



Thursday, August 25, 2016

Top 10 Craziest Intersections

Oh, humans and our monstrous creativity to deal with self-inflicted problems.

ps.the magic roundabout (3:40min) is definitely one of my favourites.


Monday, August 22, 2016

Monocentric and Polycentric cities as a continuum scale

In 2013, some colleagues and I published a paper in which we proposed the Urban Centrality Index (UCI). This index measures the centrality of a defined area (city, metropolitan area, region, country etc) considering a continuum scale that varies from extreme monocentric to extreme polycentric, and it can be applied to the spatial distribution of population, jobs, hospitals, economic activities in general etc.

I have recently shared on Github the script in R we have used to calculate UCI in our paper as well as the published study and working-paper versions. In case you're interested, here is the paper.


Pereira, R. H. M., Nadalin, V., Monasterio, L., & Albuquerque, P. H. M. (2013). Urban Centrality: A Simple Index. Geographical Analysis, 45(1), 77–89. doi:10.1111/gean.12002

Abstract
This study introduces a new measure of urban centrality. The proposed urban centrality index (UCI) constitutes an extension to the spatial separation index. Urban structure should be more accurately analyzed when considering a centrality scale (varying from extreme monocentricity to extreme polycentricity) than when considering a binary variable (monocentric or polycentric). The proposed index controls for differences in size and shape of the geographic areas for which data are available, and can be calculated using different variables such as employment and population densities, or trip generation rates. The properties of the index are illustrated with simulated artificial data sets and are compared with other similar measures proposed in the existing literature. The index is then applied to the urban structure of four metropolitan areas: Pittsburgh and Los Angeles in the United States; São Paulo, Brazil; and Paris, France. The index is compared with other traditional spatial agglomeration measures, such as global and local Moran's I, and density gradient estimations.

Thursday, August 18, 2016

Rio in time-lapse 8K

Joe Capra (aka SCIENTIFANTASTIC) has one of the most seriously awesome time-lapse videos in high definition. Since were in Olympics season, here are two of his videos of Rio.

Best viewed in HD, fullscreen

RIO - 8K from SCIENTIFANTASTIC on Vimeo.


And




ps. Here are some other great time-lapse videos we've posted before

Monday, August 15, 2016

Don't trust summary statistics

Always visualize your data! Wise words, by Alberto Cairo


Sunday, August 14, 2016

Playing around with (messy) GPS data of the bus routes in Rio using R

click on the image to enlarge it

Here is a snippet of the code I've used to create this plot in R using ggmap. I've also created a gist with a fully reproducible example of how to make flow maps in R using another dataset, in case you're interested.

Tuesday, August 9, 2016

Air quality in world cities by hour of the day

This comes from The Economist's Daily chart, where you can find other indicators and more information on the methodology (more here).

click on the image to enlarge it