The objective of this project is to perform exploratory data analysis on a given dataset to uncover meaningful insights and patterns. Through various statistical and visual techniques, we aim to understand the structure and characteristics of the data, identify any outliers or missing values, explore relationships between variables, and derive actionable insights.
The dataset used for this project is Disney Plus from kaggle. If necessary, perform any preprocessing steps such as data cleaning, transformation, or feature engineering to prepare the dataset for analysis.
The following tools and libraries were used for this project:
- Python programming language
- Jupyter Notebook
The following Python libraries were used:
- Pandas: for data manipulation and analysis.
- NumPy: for numerical computations and array operations.
- Matplotlib: for data visualization and creating plots.
- Seaborn: for advanced statistical visualizations.
Make sure that the required libraries are installed in your Python environment before running the code.
This EDA preformed project aims to explore a given dataset and derive meaningful insights through data analysis and visualization. By following the instructions in this README file and running the code in the Jupyter Notebook, you will be able to reproduce the analysis and gain a deeper understanding of the dataset. Feel free to modify the code or visualizations to suit your specific needs and requirements.