The exhibit Big Band Data now has moved to Madrid and I was required to adapt my project based on Barcelona in order to show data from Madrid.

That was a good opportunity to adapt my project to another city because that would let me comparing behaviors between 2 cities. It took me a few hours to obtain and transform shapefiles from Madrid, retrieve all the data again and re-run all the data transformation process but the result worth it:

In this occasion not only the city but the neighborhoods and the community of Madrid are also plotted, so you have more insight about the movements of the customers.

As customers are grouped by their origin (based on its postal code), the fact of showing the paths traveled by all the customers from its origin to the point where the purchase is done reveals that some shopping center act as ‘demographic walls’, as customers from the city don’t move to city outsides and customers from neighborhoods don’t go into the city:

Comparing data between Barcelona and Madrid, notice that the behaviors of the customers is pretty similar: the number of transactions increase to a maximum during the previous days before Christmas. It’s then when the activity falls to a minimum. For the rest of the inspected period both cities share a similar behavior. Another expected point is that the amount of expenditure is much greater in Madrid (3x for city’s citizens and around 2x for citizens living close the city)

Elastic lists is a good technique to navigate for a n-dimensional datasets, allowing to apply faceted browsing in a visual way. I believe the original idea is from Moritz Stefaner, you can see his excellent work about that here.

So far it seems there isn’t an implementation of Elastic lists with d3.js, so here it is a first approach, check it out here.

Source code is available, use it as you wish!

Recently I was asked to develop an online interactive piece for the University of La Rioja (UNIR) that allowed readers to explore the crimes in Spain on a number of different metrics.

This piece provides an interactive map, allowing the user to display the crime distribution in Spain based on different criteria such as crime type and subtype, crime status and year.

It was a funny assignment as it covered all the process: starting with preparing all the data and ending with providing visualization and interactivity of the piece.

Link: Crime distribution in Spain

The Exhibition BIG BANG DATA explores the phenomenon of the information explosion we are currently experiencing. The last five years have seen the emergence of a generalized awareness among academic and scientific sectors, government agencies, businesses and culture that generating, processing and above all interpreting data is radically transforming our society.

It was a pleasant surprise for me when I knew that my project Barcelona Commercial Footprints would be exposed there. It doesn’t happen every day to have a project sharing the same space with projects made by Aaron Koblin or Vizzuality, or with historical visualizations made by Florence Nightingale, John Snow or the famous Charles Joseph Minard.

The exhibition reflects really well the state-of-the art of the data paradigm that we are experiencing on our daily life, on how our lives are changing because of it. Worth to visit it if you are interested in data!

And here some pictures:

Another Data Visualization project made for another challenge, this time was the Innova Challenge Bidg Data, where the BBVA bank opened its real trade data for the first time in history.

I’ve been awarded with a second place in the Internation Challenge Innovada, in the Data Visualization category.

This international challenge focuses on journalists and developers and the aim is to reward the best visualizations and the best unpublished articles or reports based on the visualization of a set of data from various sources. Projects taking part in this competition will supply value in terms of information from constructive viewpoint of society and our environment.

For the competition, I developed an Interactive Data Visualization to show the migration flows in Spain. Here below the link with info about the project (spanish website):

Interactive Data Visualization: Migration flows in Spain

and here a video showing the application:

The application was developed using Processing, Unfolding Maps, Google Refine and the Geocoding API by Google. The data was obtained from the National Institute of Statistics of Spain.

The source code of the project is available in github. Check it out here or here.

R is a language and environment for statistical computing and graphics and is provided with excellent graphics and plotting capabilities. Lately I’ve been playing with R to get used at creating simple visualizations and charts, as a first step to get a quick overview when using a the dataset.

R is really powerful and with a few lines of code you can get the work done. Here I will explain how to make a thematic map (also known as choropleth map) as well as some basic charts. Here you can see the final result: