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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

Home Page: https://github.com/tezam84

Jupyter Notebook 96.38% Python 3.62%
eda exploratory-data-analysis happiness-report notebook-jupyter python boxplot correlation duplicate-checker missing-values numpy

eda_happiness_report_2019's Introduction

Hi, I am Aurélie Mazet

🕵️‍♀️ Data enthusiast drove by how data can tackle human challenges, through technology and innovative solutions. Improving my skills every day in Data exploration & visualization through Machine Learning thanks to Jupyter notebook and Visual Studio Code

🎓 Graduated with a Master of Science in Artificial Intelligence for Business Transformation (AIBT) from SKEMA, a top leading business school in Paris(2022)

❗ Miscellaneous: I used to have my company in the wine industry & created wine tasting videos on Youtube

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