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Visualizing the happiness of countries against their Health (Life Expectancy) as well as against their Wealth (GDP per capita). Used scatter plot, geospatial graph, and waffle chart to visualize the association.

SirivellaAnjani/World-Happiness-Visualization

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World Happiness Visualization

Exploring the relationship between the happiness (Happiness Score) of countries against their health (Life Expectancy) and wealth (GDP per capita).

Using a survey of 158 out of 195 countries in 2015, we focus on whether health and wealth affect the happiness of citizens in a country, and if so, explore the direction and strength of their correlation. We identify trends and outliers without delving into the social/political/economical causes for them.

Overview:

  1. Scatterplot:
    • Visualize the relationship between happiness and wealth.
    • Explore seaborn, matplotlib, plotly.express libraries.
    • Add dimensions to data using color and size of circle.
  2. GeoSpatial Graphs:
    • Analyze the geographical relationships using folium choropleth maps
    • Examine map styles: cartodb positron, Stamen Watercolor, Stamen Toner, Stamen Terrain
  3. Waffle Charts:
    • Answer the question "How happy is the world?" using Waffle from pywaffle library
  4. Experiments:
    • Investigate different division of data and its corresponding visualization
    • Explore features of the Waffle library, such as icons

World_Happiness_Visualization

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Visualizing the happiness of countries against their Health (Life Expectancy) as well as against their Wealth (GDP per capita). Used scatter plot, geospatial graph, and waffle chart to visualize the association.

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