Introduction
According to Statista’s Ranking of the most dangerous countries in the world in 2021, by murder rate report released in April 2021. Mexico is included as one of the top 20 most violent countries worldwide. The Mexican War on Drugs, a fighting war between the Mexican government and drug cartels since December 2006, has led to the exponential growth of homicides throughout the years. The expansion and creation of new subgroups of cartels have resulted in widespread human rights violations which include torture, extrajudicial killings, and forced disappearances.
I was inspired by Diego Valle-Jones visualizations on Crime in Mexico. This project seeks to explore the following questions. What are the names of the drug cartels in Mexico? What influence/power do they have in municipalities by states? What and where did the crimes occur in? How many civilians were effected (injured/death)?
Methodology
Dataset
The dataset I chose for this assignment was Mexico – Data on Conflict Events, published by Humanitarian Data Exchange. It covers individual events of organized violence throughout Mexico between 1989-2019. The dimensions of the dataset were 52 features by 3,904 observations. I focused on the following features:
- Year
- DYAD Name
- Municipality
- Source Article
- Deaths of Civilians
- Latitude
- Longitude
For my geographic shape file, I found Mexico’s Municipios from Carto.
Tools
For this assignment, I used OpenRefine to clean/organize the dataset. The municipality column had the word municipality after the name for every cell. I utilized value.replace function to remove them all and clear any white trail spaces afterwards.
For my visualization, I utilized Tableau Public. I first uploaded my shape file and made an inner join with my csv dataset’s Municipality name. I created two separate layers for this visualization below. The first was with the shape file for all Municipalities in Mexico. I then color coordinated it by the Aggressors Name and Municipality name. The second layer was the longitude and latitude of the crime events, I labeled it with the Source Article, it gives a description of the crime and the year it took place. This multilayer makes it easier to then observe the level of power a particular Aggressor, typically a drug cartel organization has on the Municipality.
Results
The visualization came out with some interesting findings. The first observation I made was the subgroups of cartels that are an extension of larger cartels. I was only aware of Sinaloa Cartel, Jalisco New Generation Cartel, Knights Templar Cartel, Los Zetas, Beltran Levya Cartel, and Tijuana Cartel. With the nodes of longitude and latitude pointing to the specific area where the conflict was registered in, I included Source Article feature, which usually describes the headline of the news article, source, and the year.
Future Direction
Due to time constraints, I hope that I can come back to this project and clean the source article feature by splitting the information to several columns for a cleaner description for the user. In addition, I’d also would like to discover a dataset on LGBTQ migrants who become vulnerable targets while they are journeying into the northern border of Mexico.