Motivation Behind This Project:
Growing up as the only daughter of a single mother, I developed independence and resilience at a young age. Taking care of my mother alone while fighting for my own needs taught me the value of self-advocacy. This personal experience has fueled my passion for women's empowerment. That's why I'm deeply motivated to contribute to a data science project focused on exploratory analysis of domestic violence against women and girls. By delving into the data, I aim to uncover insights that can drive prevention, intervention, and support strategies. My goal is to give a voice to the silenced, raise awareness, and create positive change for those affected by domestic violence.
Technical Analysis:
While browsing through thousands of datasets on the internet, I finally came across a dataset of my interest. I sourced my dataset from Kaggle.
This dataset contains data from 70 different developing countries. I decided to focus on developing countries because I feel that these regions require more focus and attention currently.
I also did not want to mix data from developed nations into this analysis because I feel that the conditions and the psychology behind domestic violence in these countries would differ vastly and it should be dealt with as a separate topic for analysis.
The data collected from female and male correspondents was analyzed and plotted separately in hopes to understand what reasons for domestic violence women relate to the most and what reasons men feel are justified for domestic violence against women.
Pandas was primarily used here for analyzing most of the data. Fancier libraries like Plotly were used to map geospatial data toward the end of our analysis.
The whole analysis was done using Google Colaboratory.
Link to the code: Domestic Violence against Women and Girls
Analysis & Key Takeaways:
Obstacles & Learnings:
While analyzing the domestic violence trend country-wise, we ended up focusing on extreme cases like War/Conflict ridden countries, unstable economies etc. which could seem to be obvious cases. Instead, we should have focused on dissecting and analyzing average cases and the reasons for domestic violence in those countries. A war/Conflict ridden country will be bound to have inadequate living conditions with negligible Human Right Laws. The true reasons for violence against women will show up if we had focused more on stable peaceful countries. We try to tackle this issue towards the end of our paper but the analysis is still a bit lacking there.
There are some scenarios we wanted to analyze but couldn't due to the format of our dataset.