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https://github.com/saiteja-talluri/data-analytics-assignement

Report on World Happiness Data (Data Analysis and Visualisation of the data)
https://github.com/saiteja-talluri/data-analytics-assignement

data-analysis data-visualization ipynb-jupyter-notebook

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Report on World Happiness Data (Data Analysis and Visualisation of the data)

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README 

        
# Data-Analytics-Assignement (Report on World Happiness Data)



## 1. Introduction



The happiness scores and rankings use data from the Gallup World Poll. The scores are

based on answers to the main life evaluation question asked in the poll.

The scores are from nationally representative samples for the years 2013-2016 and use the

Gallup weights to make the estimates representative. The columns following the

happiness score estimate the extent to which each of six factors – economic production,

social support, life expectancy, freedom, absence of corruption, and generosity –

contribute to making life evaluations higher in each country than they are in Dystopia, a

hypothetical country that has values equal to the world’s lowest national averages for each

of the six factors. They have no impact on the total score reported for each country, but

they do explain why some countries rank higher than others.



What is Dystopia?

Dystopia is an imaginary country that has the world’s least-happy people. The purpose in

establishing Dystopia is to have a benchmark against which all countries can be favorably

compared (no country performs more poorly than Dystopia) in terms of each of the six key

variables, thus allowing each sub-bar to be of positive width. The lowest scores observed

for the six key variables, therefore, characterize Dystopia. Since life would be very

unpleasant in a country with the world’s lowest incomes, lowest life expectancy, lowest

generosity, most corruption, least freedom and least social support, it is referred to as

“Dystopia,” in contrast to Utopia.



## 2. Problem Statement



What countries or regions rank the highest in overall happiness and each of the six factors

contributing to happiness? What trends can we observe and outliers are present? And

majorly, can we model the happiness based on the other factors?



It's an open-ended realm and you can explore the data as much as you want. We would

want to see some good analysis of the same and you have open hands for the same



## 3. Getting Started



1. Install the package:



Clone the github repository [https://github.com/saiteja-talluri/Data-Analytics-Assignement.git](https://github.com/saiteja-talluri/Data-Analytics-Assignement.git)

using

```

git clone https://github.com/saiteja-talluri/Data-Analytics-Assignement.git

```

2. Install dependencies: You need to have jupyter or ipython installed on your system.



3. Now go to iPython SCript folder and use this command to start using the notebook

```

jupyter notebook dav_script.ipynb

```

## 4. Note

   As I have written the code in jupyter notebook and the report in the repository is generated by the notebook. 

   For a better view watch it in the notebook view only :)