Análisis y visualización de datos con R de historial de actividad en Netflix de una cuenta personal. Visualización de maratones de series más vistas y frecuencia de actividad por días, meses y años
-
Updated
Mar 13, 2021 - R
Análisis y visualización de datos con R de historial de actividad en Netflix de una cuenta personal. Visualización de maratones de series más vistas y frecuencia de actividad por días, meses y años
Production-style Netflix data lakehouse platform built on AWS, implementing a Medallion (Bronze–Silver–Gold) architecture to transform raw data into analytics-ready datasets. The pipeline leverages AWS Glue for scalable ETL processing, S3 as a data lake storage layer, Athena for serverless SQL analytics & Automated Glue workflows for Orchestration.
A notebook for movie and TV show recommendations using Boolean and TF-IDF methods. Get personalized suggestions based on text descriptions and choose the method that suits your preferences.
This is the Netflix Analysis till 2021 mid, done using Python. Read the "readme" file for a quick overview of the conslusions.
A comprehensive exploration of Netflix movies & TV shows and mobile datasets, featuring univariate, bivariate, and multivariate analyses. Visualizations and insights showcase trends, correlations, and patterns in the data.
Netflix Data Analysis based on Age Based Ratings and Top Genres of 2021 of Movies - TV Shows along side Data Visualization
Data warehousing project from identifying business opportunities, researching for data, designing, data modeling, performing data Extraction, Transformation, Loading using Python, building analytics in Tableau and made recommendations to optimize business strategies. Netflix is not only a successful Service But it is completely a Data-Driven
Stock Price Prediction
Analyzing Netflix content trends using Python for data cleaning and Flourish Studio for interactive storytelling.
End-to-end Netflix catalog analysis using Python, Pandas, and Power BI. Includes data cleaning, visualization, and business insights generation.
A tutorial-style repository to master network analysis in Python using real-world Netflix collaboration data. Learn to construct, analyze, and visualize evolving networks with networkx, track temporal trends, and detect communities — perfect for aspiring data scientists and SNA enthusiasts.
An Exploratory Data Analysis (EDA) of Netflix's 2021 content catalog using the Kaggle dataset. This project covers data cleaning, content categorization, and temporal and geographic insights. The analysis explores trends in Netflix's movies and TV shows, including ratings, genres, release patterns, and geographic production distribution.
Performed Analysis and Visualization on the NETFLIX TV SHOWS AND MOVIES Dataset. Data taken from Kaggle ( https://www.kaggle.com/datasets/shivamb/netflix-shows). @RaofaizanAPSACS
My first project
📊 Netflix Data Analysis and Visualization using Python (pandas, matplotlib, seaborn)
An end-to-end Exploratory Data Analysis (EDA) of Netflix's global content library using Python. This project focuses on identifying trends in content ratings, release years, and production countries to provide strategic insights into streaming trends.
Data exploration and preprocessing on Netflix Dataset
This repository features in-depth analyses and insightful observations obtained from a Netflix dataset. It provides a comprehensive overview of user preferences, content trends, and more. The analysis used dynamic charts, graphs, and dashboards to uncover patterns, correlations, and key metrics in streaming entertainment.
Add a description, image, and links to the netflix-dataset topic page so that developers can more easily learn about it.
To associate your repository with the netflix-dataset topic, visit your repo's landing page and select "manage topics."