Dataset Card for Dataset: NetFlix Shows

  Dataset Summary

The raw data is Web Scrapped through Selenium. It contains Unlabelled text data of around 9000 Netflix Shows and Movies along with Full details like Cast, Release Year, Rating, Description, etc.

  Supported Tasks and Leaderboards

[More Information Needed]

  Languages

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  Dataset Structure





  Data Instances

[More Information Needed]

  Data Fields… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/netflix-shows.

This is the official data set used in the Netflix Prize competition. The data consists of about 100 million movie ratings, and the goal is to predict missing entries in the movie-user rating matrix. |Attribute| Value| |——|—-| | Data Set Characteristics: | Multivariate, Time-Series | | Attribute Characteristics: | Integer | | Associated Tasks: | Clustering, Recommender-Systems | | Number of Instances: | 100480507 | | Number of Attributes: | 17770 | | Missing Values? | Yes | | Area: | N/A | #Data Set Information: This dataset was constructed to support participants in the Netflix Prize. There are over 480,000 customers in the dataset, each identified by a unique integer id. The title and release year for each movie is also provided. There are over 17,000 movies in the dataset, each identified by

Netflix is a streaming service and production company. Crawl feeds team extracted more than 100 records from netflix for quality analysis purposes. Get in touch with crawl feeds team for complete dataset. Last extracted on 5 mar 2022

1) Data Introduction • The Netflix Movies and TV Shows Dataset contains various metadata on movies and TV shows available on Netflix. • Key features include the title, director, cast, country, date added, release year, rating, genre, and total duration (in minutes or number of seasons) of the content.

2) Data Utilization (1) Characteristics of the Netflix Movies and TV Shows Dataset • This dataset helps in understanding content trends and markets, as well as analyzing global preferences and changing consumer tastes. • It is useful for analyzing the characteristics of content available in different countries, including genre, cast, director, and more.

(2) Applications of the Netflix Movies and TV Shows Dataset • Content Analysis: Analyze how Netflix's content is distributed, and understand preferences based on genre or country. • Recommendation System Development: Develop algorithms that recommend similar content based on user viewing patterns. • Market Analysis: Identify which content is popular in different countries and analyze if Netflix focuses more on specific countries or genres.

Dive into the Netflix Movies and TV Shows Dataset, a detailed collection of web-scraped data featuring popular streaming titles. Discover trending movies, binge-worthy TV series, genres, ratings, release years, and audience preferences. Gain insights into Netflix originals, global streaming trends, and viewer favorites to inform market analysis and entertainment research.

Perfect for exploring content diversity, production trends, and streaming platform dynamics.

This dataset, titled "Netflix Stock Data and Key Affiliated Companies", provides comprehensive insights into the stock performance of Netflix (NFLX) alongside several key companies that have played a significant role in Netflix's growth and operational success. These companies include major technology and media giants such as Amazon (AMZN), Intel (INTC), Warner Bros. Discovery (WBD), Sony (SONY), and others.

Dataset Overview:

The dataset includes daily stock data for Netflix and a selection of companies that contribute to its content distribution, technological infrastructure, cloud services, and content licensing. The selection of affiliated companies highlights the broad ecosystem of services and technologies that power Netflix's streaming service and its original content production.

Key Companies Included:

1. Netflix (NFLX) – The leading global streaming platform that revolutionized the way we consume media.
2. Amazon (AMZN) – Provides critical cloud infrastructure via Amazon Web Services (AWS), enabling Netflix to scale globally.
3. Intel (INTC) – Supplies advanced processors and server technologies that help Netflix handle massive data loads.
4. Akamai Technologies (AKAM) – A key content delivery network (CDN) provider that ensures fast and reliable streaming.
5. Warner Bros. Discovery (WBD), Paramount Global (PARA), and Sony (SONY) – These media companies have been essential content partners for licensing and streaming rights, fueling Netflix’s growth before and during its original content development.

Features:

• Daily stock prices for Netflix and its key partners over time.
• Open, High, Low, Close, Volume and other financial metrics for each company.
• The dataset allows users to analyze correlations between Netflix and companies that provide essential services like cloud infrastructure, content delivery, and licensed content.

Use Cases:

• Financial Analysis: Evaluate stock trends, price movements, and performance relationships among Netflix and its affiliated companies.
• Business Strategy: Understand how various partnerships and technological dependencies have influenced Netflix’s rapid growth.
• Machine Learning: Use the data for stock prediction models, time-series analysis, or risk assessments by understanding the historical volatility of these companies.

Potential Analysis:

• Stock Price Correlation: Investigate the correlation between Netflix’s stock and its key partners, such as Amazon and Intel.
• Impact of Technological Partners: Assess the importance of key tech partnerships in supporting Netflix’s streaming infrastructure and business operations.
• Influence of Media Partnerships: Examine how the stock performance of media companies like Warner Bros., Sony, and Paramount align with Netflix’s success.

Conclusion:

By analyzing the historical stock data of Netflix alongside these affiliated companies, users can gain deeper insights into how a diverse set of industries—including technology, media, and cloud infrastructure—come together to create the backbone of Netflix’s success. This dataset serves as a valuable resource for financial analysts, machine learning enthusiasts, and business strategists interested in the interconnections between these influential companies.

How to Use:

• Download the dataset, and explore the stock data for the companies mentioned.
• Perform exploratory data analysis (EDA), build models to predict stock prices, or conduct business analysis to uncover the relationships that drive Netflix’s market success.

This dataset provides a solid foundation for understanding the financial landscape surrounding Netflix and its key partners.

Industry data revealed that Slovakia had the most extensive Netflix media library worldwide as of July 2024, with over 8,500 titles available on the platform. Interestingly, the top 10 ranking was spearheaded by European countries. Where do you get the most bang for your Netflix buck? In February 2024, Liechtenstein and Switzerland were the countries with the most expensive Netflix subscription rates. Viewers had to pay around 21.19 U.S. dollars per month for a standard subscription. Subscribers in these countries could choose from between around 6,500 and 6,900 titles. On the other end of the spectrum, Pakistan, Egypt, and Nigeria are some of the countries with the cheapest Netflix subscription costs at around 2.90 to 4.65 U.S. dollars per month. Popular content on Netflix While viewing preferences can differ across countries and regions, some titles have proven particularly popular with international audiences. As of mid-2024, "Red Notice" and "Don't Look Up" were the most popular English-language movies on Netflix, with over 230 million views in its first 91 days available on the platform. Meanwhile, "Troll" ranks first among the top non-English language Netflix movies of all time. The monster film has amassed 103 million views on Netflix, making it the most successful Norwegian-language film on the platform to date.

YouTube flows

Netflix held the Netflix Prize open competition for the best algorithm to predict user ratings for films. The grand prize was $1,000,000 and was won by BellKor's Pragmatic Chaos team. This is the dataset that was used in that competition.

full data https://www.kaggle.com/datasets/netflix-inc/netflix-prize-data

I extracted this data to find the unpopular movies on Netflix. The dataset I used here comes directly from Netflix movies data, which consists of 4 text data files, each file contains over 20M rows, over 4K movies, and 400K, customers. Altogether over are 17K movies and 500K+ customers!

I made some modifications and I extracted the e df_avgRating_with_usersCount.csv from the original data after applying some mathematical operations to get the average ratings and the count of users who made the ratings for each movie in movie_id below. Feel free to browse and use the data within your notebooks.

Here you could find my previous notebook on Kaggle to extract the dataset

Netflix's global subscriber base has reached an impressive milestone, surpassing *** million paid subscribers worldwide in the fourth quarter of 2024. This marks a significant increase of nearly ** million subscribers compared to the previous quarter, solidifying Netflix's position as a dominant force in the streaming industry. Adapting to customer losses Netflix's growth has not always been consistent. During the first half of 2022, the streaming giant lost over *** million customers. In response to these losses, Netflix introduced an ad-supported tier in November of that same year. This strategic move has paid off, with the lower-cost plan attracting ** million monthly active users globally by November 2024, demonstrating Netflix's ability to adapt to changing market conditions and consumer preferences. Global expansion Netflix continues to focus on international markets, with a forecast suggesting that the Asia Pacific region is expected to see the most substantial growth in the upcoming years, potentially reaching around **** million subscribers by 2029. To correspond to the needs of the non-American target group, the company has heavily invested in international content in recent years, with Korean, Spanish, and Japanese being the most watched non-English content languages on the platform.

In 2024, Netflix had licensed content assets valued at ***** billion U.S. dollars, down from ***** billion in the previous year. In contrast to previous trends, the company's produced content assets slightly increased from **** billion in the previous year to ** billion dollars in 2024.

Context

This is a Data set for Stock Price of Netflix . This Data set start from 2002 to 2022 . It was collected from Yahoo Finance.

Source

Yahoo Finance

1) Data Introduction • The Netflix Users Dataset World Wide is a user-analyzed dataset that summarizes various attributes such as subscription types, countries, subscription dates, viewing patterns, and device information of Netflix users around the world.

2) Data Utilization (1) Netflix Users Dataset World Wide has characteristics that: • Each row contains a variety of user and behavior data, including User ID, Subscription Type (Basic/Standard/Premium), Country, Subscription Date, Latest Payment Date, Account Status (Active/Disactive), Key View Devices, Monthly View Time, Preferred Genre, Average Session Length, and Monthly Subscription Sales. • Data is designed to enable various analyses such as regional trends, usage behaviors, churn rates, and viewing preferences. (2) Netflix Users Dataset World Wide can be used to: • User Segmentation and Marketing Strategy: Data such as subscription type, country, viewing pattern, etc. can be used to define customer groups and to establish customized marketing and recommendation strategies. • Service improvement and departure prediction: Based on behavioral data such as device, viewing time, and account status, it can be applied to service improvement, departure risk prediction, and development of new features.

Introduction

Netflix Statistics: In 2024, Netflix consolidated its status as a streaming leader among competitors worldwide with enormous milestones in new subscriptions, revenue, and content extension.

This article takes a more in-depth look at Netflix statistics, including major numbers, achievements in finance, demographic distributions of subscribers, investments in content, and other strategies that enabled Netflix to continue enjoying success.

https://www.kaggle.com/datasets/shivamb/netflix-shows

Netflix reported **** million paid streaming subscribers across the United States and Canada in the fourth quarter of 2024. This marked a growth of over **** million compared with the same quarter of the previous year. Why is Netflix losing subscribers? The EMEA (Europe, the Middle East, and Africa) region is Netflix's top-performing market in terms of subscribers, surpassing North America in the third quarter of 2022 for the first time. The company reported losing an estimated *** million users worldwide in the second quarter of 2022, with the number of Netflix users standing at approximately *** million that quarter. But why have audiences canceled their subscriptions? One reason for the unprecedented drop in account holders is Netflix's monthly fee, which has been increasing rapidly over the past few years. On top of that, viewers have also voiced criticism over Netflix's cancellation of popular shows and its lack of big movie franchises. What are audiences watching? Netflix's vast content library offers anything from reality TV to Hollywood blockbusters, with shows and movies delivered in many languages. As of mid-2024, European countries such as Slovakia, Bulgaria, and Slovenia boasted the largest content catalogs on Netflix. In the U.S., where audiences could choose from approximately ***** titles, “NCIS” and “Suits” ranked among the most popular streaming series on Netflix in 2023. As of that year, fan favorites “Stranger Things” and “3 Body Problem” were the most expensive Netflix original series, with production costs of ** and ** million U.S. dollars per episode, respectively.

Netflix 员工 总数 - 当前值，历史数据，预测，统计，图表和经济日历 - Aug 2025.Data for Netflix | 员工 | 总数 including historical, tables and charts were last updated by Trading Economics this last August in 2025.

The action comedy film “Red Notice” was the most popular English-language Netflix movie of all time as of January 2025, based on the number of views in its first 91 days on Netflix. The film counted nearly 231 million views. The second most popular movie, “Don't Look Up,” reached about 60 million fewer views than “Red Notice.” “The Adam Project,” starring Ryan Reynolds, ranked third in popularity with roughly 158 million views.

Analysis of ‘Netflix Top 10 Weekly Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mikitkanakia/netflix-top-10-weekly-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

OTT platforms are growing in the last few years. Netflix is one of the top OTT platforms with maximum subsriber and viewership. Netflix has released Top 10 Movies and TV across weeks where we can analyze the viewership and movie content.

Content

The data is present in the excel sheets and it was directly downloaded from the website and will be updated on weekly basis.

We have two files in the dataset.

1) All Weeks Global Global Top 10 viewership counts across the weeks.

2) All Weeks Countries Per Countrywise Top 10 List of Movies and TV

Acknowledgements

Last week Netflix has started publishing its data to the public domain. The data is available on https://top10.netflix.com/

Inspiration

What are the viewership distribution across top 10 movies and TV and change on the weekly basis? We can find which countries have similar viewership?

--- Original source retains full ownership of the source dataset ---