This project is about the crime incidence that occurs in Mexico City. This particular piece addresses the problem to tica of the stolen cell and is one of the five cap í titles comprising the project.
The objective was to identify geospatial and temporal patterns (places and schedules) where cell theft occurs most frequently. The set data were obtained from the official source of the government of the City of M é xico and includes data from 2015 to 2019, which gives us confidence about the predictive and preventive capabilities have our tool.
The true impact of this project revolves around people and their safety. The data contain information that we occupy or n very accurate, is to n georeferenced street level and have the exact time that occurred was or each offense. This enabled us or generate a visualization tool it or n data where we could, for the first time, show the level of Criminality of each delegation, street or colony of Mexico City; as the exact times in which these spaces become more dangerous. We believe this information or it n is extremely valuable for people, because you make changes in your daily life that will increase your safety and therefore their quality of life.
For an to analysis of the data we use Phyton. For creating the map we ended up taking MapBox, what allowed or raise the quality of the design of our tool. Aspects of design were made in Illustrator and XD.
What was the hardest part of this project?
the hardest part was the tool design, we strive to generate something quite managed to be highly usable by the average user through the city. Several discussions took place in the office before they arrived to branches to a newer version or No to grant delegation level trends or n and at the same time geolocalizaci or n specifies for each offense.
In the design ñ ar this tool, also é n we had to consider a design ñ or could be reused for the 4 chapters of following project: Kidnapping, Robbery houses Theft Auto or robbery in public
What can others learn from this project?
We liketo thonk the lesson to learn is about the potential of DataViz and data journalism to impact so r to ask and abrupt in our daily lives, in this case all term effort can choose a route safer to get to work or home, but in a same way there are countless changes and decisions that people could í do based on data.