umangchaudhry/acled_africa

A Python Package for performing analysis on the relationships between protests and battles in Africa Nations using the ACLED data # acled_africa A Python Package for performing analysis on the relationships between protests and battles in African Nations using the ACLED data # Quick navigation Installation Instructions Dependencies Package Structure References ## Installation Instructions To use this package, please clone this repository in the working directory for your project. Once the acled_africa folder is in your working directory, copy the internal acled_africa folder to your working directory (your own code files must be outside the acled_africa folder). Once this is done, you will be able to import the package as any other python package: ```python import acled_africa ``` Additionally, each module within the package can be imported as follows: ```python from acled_africa import eda from acled_africa import maps from acled_africa import country_analysis from acled_africa import textanalysis ``` Functions in each module can be called as follows: ```python eda.region_event(params) ``` **Note**: Your repository must have a folder called 'data'. Certain files that are required to generate the maps will be stored in that folder. ## Dependencies This package uses several pacakges to run the build in functions. You will be required to install these dependencies before being able to use this package. However, once installed, you are not required to import the dependencies. The required packages are listed below: * numpy * pandas * matplotlib * seaborn * sklearn * time * wordcloud * itertools * warnings * re * json * geopandas * folium * networkx * pylab ## Package Structure This package has 4 separate modules: 1. eda 2. maps 3. country_analysis 4. textanalysis Each module has several built in functions that use given data to perform analysis. Descriptions of each of the functions within these modules can be found below: ### eda ```python region_event(data) ``` This function creates a bar plot of the regional distribution of events in the given dataset. ```python event_dist(d …