An exploratory data analysis(EDA) on education inequality of differenet countries Most of the project focuses on data cleaning Especially handling missing values For this project, There were more than 50% missing values In order to handle them: I determined the proportion of missing values first based on rows and then columns Countries with more than 30% of missing values were dropped This caused a significant loss of data But as in real-life project, That is what happens usually
Data Source : UNESCO