#Project Title: 
Analysis of Happiness Score and Social Factors

This project aims to detect the correlation between trust, freedom, openness and happiness, and how happiness and openness scores are distributed throughout the world, and how these three social factors effected the happiness score in different regions (espeically in the 10 countries that have the highest and lowest happiness scores.)

##Data

The happiness datasets from Gallup World Poll for each country within a 3-year period (2015-2017) and openness dataset from the 2015 Global Open Data Index were used for analysis. They are all CSV files. Happiness datasets contained 13 variables for each country in the world. The openness dataset contained openness data each year for each country. 

##What this code does

##Getting Started

###Prerequisites
Python and Python packages are pandas, numpy, matplotlib.pyplot and seaborn 


###Installing
import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

import seaborn as sns

##Authors

Xi Qian - graduate student at The George Washington University 

##License

This project is licensed under the MIT License.

##Acknowledgments

Datasets:

Risdal, M.(2016). 2015 Global Open Data Index.(V1)[CSV] Retrieved from https://www.kaggle.com/mrisdal/happiness-and-open-data/data

Sustainable Development Solutions Network. (2017) World Happiness Report (V2)[CSV]. Retrieved from https://www.kaggle.com/unsdsn/world-happiness