How to import tweets to CartoDB with Python

I have been quite busy these last couple of weeks. On the 3rd of December I attended to the CartoDBeers and Workshop for data journalists at CartoDB Headquarters to be prepared for the next Spanish general elections. Then on the 5th of this month, Carmen Langa and me organized a kids map workshop at Medialab-Prado. But this requires a whole blog post to explain how much fun we had! Finally, last thursday I went to Campus Madrid at the last stop of the LocationTech Tour. It was quite interesting to listen to all the people from CartoDB, QGIS, Glob3mobile and Boundless.

And in the meantime I manage to figure out how to import tweets from twitter to CartoDB using Python:

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Humanitarian OSM Team Mapathon 2015

There have been a lot going on in the GIS world since my last post. Several weeks ago I attended to the The state of mapping on the web: Esri, CartoDB and Mapbox. In this meeting, Raúl Jimenez from Esri, Jorge Sanz from CartoDB and Johan Uhle from Mapbox presented their webmapping platforms and discussed the beautiful moment the geospatial industry is having (you can watch the talk here). Then it was the 2015 Spanish ESRI Conference, the #GISday, #PostGISday and finally, this saturday we celebrate the #OSMgeoWeek running a HOT (Humanitarian OSM Team) mapathon. One of more than 100 around the world.

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Cartographic tools for data journalists

Last Saturday I attended the Jornadas de Herramientas Cartográficas organized by Geoinquietos and the Periodismo de Datos group in Medialab-Prado. Several professionals, cartographers and journalists mostly, gave an insight of their work and the tools they most commonly use. The event was focused on election maps (#electionmaps) and you can find a GitHub repository with all the slides and scripts which were displayed during the workshop.

Thanks to Xosé Manuel Vilán and Jesús García we learnt how to make hex maps with Quantum GIS, Graeme Herbert showed us how to make prediction models applying the not-well-called D’Hont Law and a couple of epidemiologists from the Instituto de Salud Carlos III, Rebeca Ramis and Diana Gómez, explained to us how to analyze spatial data with Geoda software. Carlos Gil and Beatriz Martinez also introduced us into mapping with R. A very interesting talk was given by Jorge Sanz from CartoDB.  He showed us how to solve the eternal geographical problem of the Spanish geography: putting the Canary Islands on the map. And he did it with just a few lines of SQL:

You can observe the result thanks to the following map. Before and after running the code.

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Accessibility Mapping Party – Tetuán 5.0

Last weekend I went to the Accessibility Mapping Party 5.0 in Tetuán (Madrid). An event created by Alejandro Zappala and the Geoinquietos group -which I have recently joined- which consisted in a collaborative mapping workshop carry out by local people and some gisters. It was fun to meet a very concerned group of neighbors, users and professionals. The aim of this party was to map the accessibility of the Ventilla’s local business. Something that brought me memories of lots of mornings walking the streets of my hometown. First we walked, then we mapped:


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Catalonian election maps on the news

Yesterday more than 4 millions of Catalans cast their vote. An incredible record of participation: 77% of the Catalonia total population were to decide their future. A future than in my humble opinion is not far from clear. Although the Catalan separatist coalition Junts pel Sí (Together for Yes) won in parliamentary seats, almost every Spanish newspaper agree that this victory is useless because they do not have the support of the majority of the population. In fact, Junts and the other nationalist party, CUP –Candidatura d’Unitat Popular– add just 47% of the voters.

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How to geocode and visualize your data with CartoDB

In the last post we geocode our data with R. But the geocoding process did not work enterely right. Some points were badly geolocated. In this post, I will explain how to subset these outliers, correct their coordenates and finally, visualize the entire dataset both using R and CartoDB.

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How to geocode your data with R

In my first post I would like to introduce you one of the easiest ways to geocode your data. Geocoding is one of the most essential functionalities within the spatial analysis. It allow us to transform a description of a location, generally an address, postcode or similar, into a pair of coordinates -longitude, latitude or X, Y-. Then we can map our data.

worldmapgreen

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