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 [Intro]
 
 This repository is organized as follows:
-* [EDA](./EDA): Exploring data, handling missing values, analyzing variable distribution, filtering data, feature selection, encoding variables, and performing correlation analysis.
+* [EDA](./EDA): 
+    * [output](./EDA/output): Plots about feature distributions, correlations and importance.
+    * [EDA.ipynb](./EDA/EDA.ipynb): Notebook used for exploring and filtering data, handling missing values, encoding variables, building the final pre- and post- pandemic datasets, and generating plots for feature distributions, correlations and importance.
 * [gen_train_data](./gen_train_data): Generating training and testing datasets [wait for final approach TBC].
 * [model_selection](./model_selection): Tuning models, generating metrics from cross-validation and testing, and selecting final models.
     * [hyperparam_tuning.py](./model_selection/hyperparam_tuning.py): Tunes models through a random search of hyperparameters.