This repository contains exploratory data analysis (EDA) on multiple datasets including Flight Price Data, Black Friday Sales Data etc. The purpose of this project is to analyze the data and gain insights that can be used to inform future decisions.
The datasets used in this project are obtained from Kaggle.
The EDA is performed using Python and the following libraries: pandas, matplotlib, seaborn, and numpy. The EDA covers the following aspects of the data: Data cleaning and preprocessing
- Univariate analysis of each variable
- Bivariate analysis of each variable with respect to the target variable
- Correlation analysis between variables
- The findings of the EDA are presented in the notebook along with visualizations that help to communicate the insights gained from the analysis.
The EDA provides a foundation for future analyses and modeling. The insights gained from the EDA can be used to guide feature engineering, model selection, and hyperparameter tuning.