Read the blog post accompanying this repository here: https://gecheline.medium.com/infographic-do-more-guns-more-freedom-d38980fa23f7
This repository contains data, its transformation and exploration in terms of firearm ownership rates, firearm and police death rates and freedom indices per country for 2017. The goal with this little project is to search for potential global trends that relate firearm ownership, violence and personal freedom. The analysis is strictly descriptive, as the data, in the format used, is too diverse to grant any robust modeling. However, the simple bar and scatter plots and correlation heatmaps still help us answer the main questions posed:
- Is there evidence for correlation between the firearm and police death rates with firearm ownership rates? - Short answer: NO.
- Are there trends in the death rates by firearm and police with respect to how developed a country is? - We find that three "freedom index" groups can be distringuished in terms of the range of recorded rates, with the US being a strong outlier among high-freedom index countries.
- Does firearm ownership grant more personal freedom? - The data does not show significant correlation between firearm ownership and freedom indices. However, some interesting insights are made regarding the US, which prompt further analysis.
The raw data sets used can be found in raw_data/ and include the follwing:
- IHME-GBD data set - the data set is generated using the GBD Results tool, (citation: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Available from http://ghdx.healthdata.org/gbd-results-tool.). Contains firearm-related, police-related and other death rates per country, per year for years 2013-2019, grouped by age group, sex and cause.
- global gun ownership - downloaded from Wikipedia https://en.wikipedia.org/wiki/Gun_ownership / the Small Arms Survey for 2017
- freedom index - data from the latest report of the Cato Institute, downloaded from Kaggle https://www.kaggle.com/gsutters/the-human-freedom-index?select=hfi_cc_2020.csv (most recent year available in the data set is 2017)
These are transformed into the project_data/ set which contains rates and values from each dataset for 2017, transformed such that each country has a unique country code and value per column.
All code is contained in the firearmStats_world notebook, which requires
- numpy
- pandas
- matplotlib
- seaborn
- itertools for successful execution.
The conclusions of this exploratory analysis are the following:
- There are no clear correlations between firearm ownership, firearm-caused deaths and police-caused deaths on a global level. This is understandable because a lot of these incidents are driven by the laws, politics, economy and stability within a country and these differ greatly on a global scale.
- Personal freedom index (PFI): firearm-caused deaths show the widest range in medium-PFI countries (6 < PFI < 8), while police-caused deaths are highest for low-PFI (PFI < 6) countries. This is logical if we take into account access to firearms and political instabilities in both of these groups.
- USA is a clear outlier in all of these categories within the high PFI group. Its firarm-caused death rates are closer to the mid-PFI countries (with much lower firearm ownership rates), while police-caused death rates fall on the boundary of the values spanned by mid-PFI and low-PFI countries.
- The firearm ownership rate in the US does not follow the trends of the rest of the countries with high PFI. Its removal from the dataset significantly decreases the correlation between firearm ownership and firearm/police fatalities, but slightly increases the correlation between firearm ownership and personal freedom.