Visualization of Conflicts in Colombia and the World

The Uppsala Conflict Data Program (UCDP) has recorded ongoing violent conflicts since the 1970s. Using its dataset of 135 thousand records of organized violence globally since 1989, we can evaluate the distribution of conflicts in the world and in specific countries.
I listed here the top 10 countries:
Order Country Freq
1 Afghanistan 22,726
2 India 14,465
3 Iraq 6,488
4 Nepal 5,652
5 Pakistan 5,528
6 Turkey 4,826
7 Sri Lanka 4,576
8 Colombia 4,562
9 Algeria 4,098
10 Somalia 4,090

Since the year 2000, there are 98K records in the dataset. Again, the top 10 are:
Country Freq
1 Afghanistan 20,980
2 India 11,409
3 Iraq 6,109
4 Pakistan 5,335
5 Nepal 5,084
6 Somalia 3,664
7 Colombia 3,302
8 Russia  3,115
9 Nigeria 2,901
10 Sri Lanka 2,583

As we can see, the distribution of conflicts is highly skewed to the right since most countries are peaceful and conflicts are concentrated in certain areas of the world. In a recent working paper, we focus on the organized violence in Colombia. Applying a similar methodology to airport score, I count the number of conflicts within 50 km around each point on the map and create a measurement named conflict score.

Top 10 cities ranked by conflicts score for Colombia and the World


Visualization of conflicts in Colombia and main cities using heat map:


Another visualization using 3D column:

Animation


Both Excel and R are slow in running this amount of data (500,000 records). Shall further investigate other options.

Heat map of conflict region in the world for the 4231 cities

red: cities with at least one conflict; blue: cities with no conflict (2000 - 2015)


Comments

Unknown said…
What does it mean "conflicts are highly skewed to the right"?
Yang Liu said…
As I have revised, it means conflicts are highly long-tailed, some countries have very high values, while most countries have only a few or none conflict at all.

Popular posts from this blog

How to Draw Heatmap with Colorful Dendrogram

Power-law distribution (Pareto)& Zipf's Law: connection and how to fit the distribution of global city population

eXtreme Gradient Boosting (XGBoost): Better than random forest or gradient boosting