Inspiration
The inspiration for this project was drawn from the ever-evolving global geopolitical landscape. In an era marked by profound changes, the world is witnessing a significant shift in power dynamics, with emerging and developing countries like India playing pivotal roles. These nations are increasingly becoming economic powerhouses, influencing international policies, and shaping the world's socio-economic fabric.
What it does
It performs data analysis on various indicators of large dataframes, in order to measure correlations and find causalities between those indicators.
How we built it
We subdivided the task into regions and countries, and used the data we found to apply data analysis in a illustrative way with the help of pandas, numpy and matplot. We would`ve like to use scikit learn but the datasets weren´t sufficient and easy to find such that we did not have enough time.
Challenges we ran into
The main problem was finding enough data, which was usable and comparable. Another problem was to figure out the whole Data Science topic, concept and the deliverable/result we want to submit.
Accomplishments that we're proud of
We are proud of being able to deliver a finished notebook, which shows the analysis of the data sets in an understandable and illustrative way
What we learned
We learned how to manage time efficiently and to set first accomplishable goals but which can be easily redefined into more complex problems. Additionnaly, we learned how to split the work reasonably and gaining experience of participating in a Datathon. Finally, we've deepen our knowledge in various libraries and frameworks like pandas and got the interesting and incredible experience of working with one of the most powerful mainframe.
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