Python_World_Happiness_Report

For this project on WHR 2019, I used python for the data analysis and created a Tableau Storyboard.

Project Overview:

This project focuses on analyzing the World Happiness Report 2019 dataset to gain insights into the factors influencing happiness scores across different countries. Through exploratory data analysis, regression analysis, and cluster analysis, we aim to understand the relationship between socio-economic indicators and happiness levels.

Analysis:

I’ll conduct the following analyses throughout the Project:

● Exploratory analysis through visualizations (scatterplots, correlation heatmaps, pair plots, and categorical plots);

● Geospatial analysis using a shapefile;

● Regression analysis;

● Cluster analysis;

● Time-series analysis;

● Analysis narrative and final results presented in Tableau Storyboard.

Research Questions:

1.  How strongly does GDP per capita correlated with happiness scores across countries? 
   

2.  Is there a significant relationship between social support and happiness levels? 
   

3.  What is the distribution of happiness scores across different regions or continents? 
   

4.  Are there any trends or patterns in the relationship between life expectancy and happiness? 
   

5.  How does the perception of freedom to make life choices affect happiness levels? 
   

6.  Is there a notable difference in generosity scores between countries with high and low GDP per capita? 
   

7.  Do countries with lower levels of corruption tend to have higher happiness scores? 
   

8.  How do happiness scores vary between urban and rural areas within countries? 
   

9.  Are there any outliers or anomalies in the dataset that might warrant further investigation? 
   

10. How have happiness scores changed over time if longitudinal data is available? 
    

Data

The primary data source for this analysis is the World Happiness Report 2019, sourced by CareerFoundry via Kaggle. The dataset includes country-level data on various factors such as GDP per capita, social support, life expectancy, freedom, generosity, and perceptions of corruption, along with corresponding happiness scores.

• World Happiness Report 2015–2019

• World Happiness Report 2020

Tools used:

macOS | Excel | Python | Tableau

Project Deliverables

For visualizing the findings of this analysis, a Tableau dashboard has been created. You can access the dashboard here

Documents provided:

The project files are divided between the following folders:

● 01 Project Management:

• Project Brief
• WHR 2020, Statistical Appendix for Chapter 2, include information about the variables of the dataset.

● 03 Scripts:

The Jupyter notebooks containing the coding for the analysis.

● 04 Analysis:

The Visualizations subfolder contains the visualizations used for developing and explaining insights.

● 05 Sent to Client:

The final results presented in Tableau Storyboard