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This is an Exploratory Data Analysis (EDA) in 12 Steps with an easy going dataset for beginners. The goal is to understand the correlation between variables step by step. For advance practionners you can use the profiling package in Python

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tezam84/EDA_Happiness_report_2019

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😃 EDA_Happiness_report_2019

This is an Exploratory Data Analysis (EDA) of numerical and categorical observations on more than 100 countries in 2019.

The goal is to understand the correlation between a country labelled "Happy" and the factors linked to it.

Here's are some factors: GPD per capita, social support, generosity, rank...

This project is created with the following Python packages: Numpy, Pandas, Matplolib, Seaborn.

I have used a heatmap to have a clear visualization and the corr() method.

Photo by LIDYA NADA on Unsplash

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This is an Exploratory Data Analysis (EDA) in 12 Steps with an easy going dataset for beginners. The goal is to understand the correlation between variables step by step. For advance practionners you can use the profiling package in Python

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