We analyzed the geographical distribution of fatalities using the ACLED dataset. A scatter geo plot was created to visualize the concentration of fatalities across different locations. The plot shows the size of fatalities in relation to their geographical coordinates, providing a clear view of where the highest fatalities are concentrated geographically.

We analyzed the trend of fatalities over time using the ACLED dataset. A line plot was created to visualize the sum of fatalities each month. The plot highlights how the number of fatalities has changed over the years, providing insights into periods of increased or decreased violence.

To perform a regression analysis on fatalities, we'll first need to prepare the data by selecting relevant features that could influence fatalities, such as event type, location, and year. Then, we'll split the data into training and testing sets, choose a regression model, train the model on the training set, and evaluate its performance on the test set. Let's start by preparing the data.

To investigate the impact of location on fatalities, we'll analyze fatalities by admin1 (first-level administrative division, like a state or province) and admin2 (second-level administrative division, like a city or district). This approach helps us understand how fatalities are distributed across different regions and identify areas with higher incidences of violence. We'll start by aggregating fatalities by these administrative divisions.