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

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.

Original Data Source: Dataset: NetFlix Shows

Netflix Prize consists of about 100,000,000 ratings for 17,770 movies given by 480,189 users. Each rating in the training dataset consists of four entries: user, movie, date of grade, grade. Users and movies are represented with integer IDs, while ratings range from 1 to 5.

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

This dataset provides a comprehensive collection of all titles (Movies and TV Series) available on Netflix. In addition to basic information, it includes IMDb-specific data like IMDb ID, Average Rating, and Number of Votes.

A dataset is updated daily at 10:00 AM CET. If you find this dataset helpful, feel free to give it an upvote! 😊

You can find all our APIs, maintained and developed by us, at the following link: octopusteam.dev. These APIs provide access to various features and data, ensuring high-quality and reliable integration options for your needs.

All Datasets:

• Full Netflix Dataset
• Full Apple TV+ Dataset
• Full Amazon Prime Dataset
• Full Hulu Dataset
• Full HBO Max Dataset

Context

Netflix, Inc. is an American media company engaged in paid streaming and the production of films and series.

Market cap

Market capitalization of Netflix (NFLX)

Market cap: $517.08 Billion USD

As of June 2025 Netflix has a market cap of $517.08 Billion USD. This makes Netflix the world's 19th most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Revenue

Revenue for Netflix (NFLX)

Revenue in 2025: $40.17 Billion USD

According to Netflix's latest financial reports the company's current revenue (TTM ) is $40.17 Billion USD. In 2024 the company made a revenue of $39.00 Billion USD an increase over the revenue in the year 2023 that were of $33.72 Billion USD. The revenue is the total amount of income that a company generates by the sale of goods or services. Unlike with the earnings no expenses are subtracted.

Earnings

Earnings for Netflix (NFLX)

Earnings in 2025 (TTM): $11.31 Billion USD

According to Netflix's latest financial reports the company's current earnings are $40.17 Billion USD. In 2024 the company made an earning of $10.70 Billion USD, an increase over its 2023 earnings that were of $7.02 Billion USD. The earnings displayed on this page is the company's Pretax Income.

End of Day market cap according to different sources

On Jun 12th, 2025 the market cap of Netflix was reported to be:

$517.08 Billion USD by Yahoo Finance

$517.08 Billion USD by CompaniesMarketCap

$517.21 Billion USD by Nasdaq

Content

Geography: USA

Time period: May 2002- June 2025

Unit of analysis: Netflix Stock Data 2025

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

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

Data on the share of Netflix viewing in the United States showed that 37 percent of content viewing n the platform was of of original shows. This marks a dramatic increase from January 2017 when the figure was just 14 percent. Netflix originals have proved to be hugely popular and often draw in large audiences. More than 18 million viewers across the globe watched the entire third season of 'Stranger Things' within four days of its release in 2019, and 40.7 million watched at least part of Season 3 in that time. However, the majority of Netflix viewing is still of licensed content, which could cause Netflix issues in months and years to come as its competitors reclaim their content and use it on their own streaming services. It has already been noted that Netflix will eventually lose the rights to show American sitcom 'Friends', for example - one of the most watched shows on the platform.

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.

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.

About this Dataset

This dataset shows the number of paid subscribers to the Netflix streaming service at the end of each quarter going back to 3/31/2016. The data is also broken down by geographical region.

Category

Business Information & Financials

Keywords

Netflix,streaming,subscriber data

Row Count

30

Price

$99.00

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.

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.

Traffic analytics, rankings, and competitive metrics for netflix.com as of May 2025

This dataset addresses the common issue of finding quality content amidst a vast catalogue, specifically on Netflix. It aims to help users discover underrated content and hidden gems. The dataset aggregates information from multiple sources, including Netflix itself, Rotten Tomatoes, and IMDb, combining various attributes to provide deeper insights into content quality and characteristics. A unique "Hidden Gem Score" is included, calculated based on low review counts and high user ratings, making it easier to identify valuable content that might otherwise be overlooked. This dataset powers the FlixGem.com platform, a related project designed for interactive exploration.

Columns

The dataset includes several key columns to facilitate detailed analysis of Netflix content: * Title: The name of the movie or series. * Genre: Hundreds of genre classifications for the content. * Tags: Thousands of detailed tags describing the content. * Languages: Languages available for the content, including English and many others. * Series or Movie: Indicates whether the content is a TV series or a movie. * Hidden Gem Score: A calculated metric based on low review counts and high ratings to identify hidden gems. * Country Availability: Information on Netflix country availability for the content. * Runtime: The duration of the series or movie. * Director: The director of the content. * Writer: The writer of the content.

Distribution

The data files are typically in CSV format. This dataset is regularly updated, with monthly revisions to ensure freshness. It was last updated in early April 2021. The dataset is version 1.0. While specific total row or record counts are not provided, some columns feature a considerable number of unique values, such as over 15,000 unique genres and over 13,000 unique languages.

Usage

This dataset is ideal for various analytical and exploratory applications, including: * Finding correlations between ratings, actors, directors, and box office performance. * Identifying patterns related to content quality based on characteristics like language and genre. * Discovering hidden gems across different regions. * Interactive browsing and knowledge discovery through platforms like FlixGem.com, which is powered by this very dataset. * Developing machine learning models for content recommendation or classification.

Coverage

The dataset offers global regional coverage, with a specific column indicating Netflix country availability for content. It focuses on recent Netflix data, with monthly updates provided. The last update was in early April 2021. The content spans a wide range of genres and includes various languages, with English being a significant portion. Runtime varies, with a large percentage of content being 1-2 hours long, followed by content under 30 minutes.

License

CCO

Who Can Use It

This dataset is designed for anyone interested in delving deeply into Netflix content, including: * Data analysts looking to unearth trends and insights. * Researchers studying media consumption patterns or content quality. * Developers creating recommendation engines or content discovery tools. * Machine learning practitioners building models for classification or prediction. * Content strategists seeking to understand what makes content resonate. * Individuals simply curious about finding their next favourite show or movie.

Dataset Name Suggestions

• Netflix Hidden Gems Dataset
• Netflix Content Quality & Discovery Data
• Global Netflix Catalogue Insights
• Curated Netflix Content Attributes
• Netflix Underrated Content Analysis

Attributes

Original Data Source: Latest Netflix data with 26+ joined attributes

The Measurable AI Netflix Email Receipt Dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Japan) - EMEA (Spain, United Arab Emirates)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from the Careem Now food delivery app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

Dataset

This dataset was created by Abhishek Ranjan

Contents

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 ---

Netflix reported $1.45B in Trade Debtors for its fiscal quarter ending in March of 2025. Data for Netflix | NFLX - Trade Debtors including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Netflix reported $10.54B in Sales Revenues for its fiscal quarter ending in March of 2025. Data for Netflix | NFLX - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last July in 2025.