In this project, I used Pandas, NumPy, Matplotlib, and Seaborn to analyze and visualize data from the Women Empowerment Index (WEI) 2022. The WEI is a comprehensive tool designed to evaluate the progress of women’s empowerment across different societies. It incorporates a wide range of indicators to provide a nuanced picture of women’s status across various dimensions, such as economic participation, political representation, education, healthcare access, and social inclusion.
Visualizations & Analysis:
Histogram: Showed the distribution of WEI across countries.
Box Plot: Identified outliers and provided insight into the spread of WEI values.
Heat Map: Visualized correlations between WEI and other numerical variables in the dataset.
Bar Chart: Compared the average WEI across different Sustainable Development Goal (SDG) regions.
Scatter Plot: Explored relationships between WEI and other indices, such as the Global Gender Parity Index.
Matplotlib Visualization: Showed the proportion of countries in each women’s empowerment group.
These visualizations helped uncover patterns and relationships within the data, providing deeper insights into global gender dynamics
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