This project involves the analysis of Netflix data using Python and various data science libraries such as pandas, numpy, and Plotly. The primary goals were to clean and preprocess the raw data, perform insightful analyses, and create meaningful visualizations to uncover patterns and trends in the dataset.
The raw Netflix dataset was loaded into a Jupyter Notebook using pandas. Data cleaning tasks included handling missing values, removing duplicates, and ensuring data consistency.
Exploratory Data Analysis (EDA) was conducted to gain a deeper understanding of the dataset. Key statistical metrics and summary statistics were calculated to identify central tendencies and outliers.
Utilizing the Plotly library, interactive visualizations were created to illustrate trends and patterns in the data. Graphs and charts were generated to present insights related to genres, release dates, and viewer ratings.
Interpretations and conclusions were drawn based on the analyses and visualizations. Findings provided valuable insights into user preferences, popular genres, and temporal patterns.
- Python
- Jupyter Notebook
- Pandas
- NumPy
- Plotly