A complete exploratory data analysis project on the Netflix Movies and TV Shows dataset. This project involves data cleaning, handling null values and duplicates, detecting and removing outliers, and visualizing categorical and numerical variables.
Key Highlights: -Cleaned and preprocessed the dataset (null values, duplicates, outliers). -Converted relevant columns to numerical form for analysis. -Explored key insights through boxplots, bar charts, histograms, and heatmaps. -Analyzed trends in content duration, release years, and added dates. -Visualized categorical distributions like genres, countries, and content ratings. -Summarized correlations among numeric variables.
Tools & Libraries: -Python (Pandas, NumPy). -Visualization: Matplotlib, Seaborn.
Objective: -To practice and demonstrate data cleaning, EDA, and visualization skills by uncovering trends and patterns in Netflix content data.