Netflix reported $11.51B in Sales Revenues for its fiscal quarter ending in September of 2025. Data for Netflix | NFLX - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last December in 2025.

By 2026, around ** million Europeans are forecast to have a Netflix subscription. In 2020 this figure stood at just below ** million Netflix subscribers in Europe. As of the first quarter of 2021, Netflix had almost *** million paying subscribers worldwide. History of Netflix Netflix was founded in the United States in 1997, offering media through online streams or through a DVD-by-mail service. Now, the service is available across more than *** countries globally and boasts revenues of almost ** billion U.S. dollars. As of the first quarter of 2020, its leading markets included the U.S., Brazil, and the UK, although it is popular across many European countries. Video-on-Demand Despite some European countries having access to as many as around *** legal options for Video-on-Demand services, in terms of use there are two clear front runners. As of 2020, Netflix held a market share of almost ** percent of the Subscription Video-on-Demand services in the EU, while Amazon came second with about a third of the market.

In the second quarter of 2024, Netflix generated total revenue of over **** billion U.S. dollars, up from about *** billion dollars in the corresponding quarter of 2024. The company's annual revenue in 2024 amounted to around ** billion U.S. dollars, continuing the impressive year-on-year growth Netflix has enjoyed over the last decade. Netflix’s global position Netflix’s revenue has been heavily impacted by its ever-growing global subscriber base. The leading Netflix market is Europe, the Middle East, and Africa, surpassing the U.S. and Canada in terms of subscriber count. Netflix has also significantly increased its licensed and produced content assets since 2016. Despite concerns among investors that the company’s content spend was negatively affecting cash flow, Netflix’s plans to amortize its content assets long-term along with generating revenue from other sources such as licensing and merchandise should ensure the company’s future profitability. Netflix’s original content Netflix is also fortunate in that many of its original shows have been a hit with consumers across the globe. Shows such as “Orange is the New Black,” “Black Mirror,” and “House of Cards” won the hearts of subscribers long ago, but newer content such as English-language shows “Bridgerton,” “Wednesday,” and “Stranger Things,” as well as local TV shows such as “Squid Game,” have also been favorably reviewed and proved popular among users.

Netflix stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

This dataset offers a comprehensive historical record of Netflix’s stock price movements, capturing the company’s financial journey from its early days to its position as a global streaming giant.

From its IPO in May 2002, Netflix (Ticker: NFLX) has transformed from a DVD rental service to a powerhouse in on-demand digital content. With its disruptive innovation, strategic shifts, and global expansion, Netflix has seen dramatic shifts in stock prices, reflecting not just market trends but also cultural impact. This dataset provides a window into that evolution.

What’s Included?

Each row in this dataset represents daily trading activity on the stock market and includes the following columns:

• Date – The trading day (from 2002 onward)
• Open – Stock price when the market opened
• High – Highest trading price of the day
• Low – Lowest trading price of the day
• Close – Final price at market close
• Adj Close – Closing price adjusted for splits and dividends
• Volume – Number of shares traded that day

The data is structured in CSV format and is clean, easy to use, and ready for immediate analysis.

Why Use This Dataset?

Whether you're learning data science, building a financial model, or exploring machine learning in the real world, this dataset is a goldmine of insights. Netflix's market history includes:

• Periods of explosive growth during digital transformation
• Volatility during market crashes and global events (e.g., 2008, COVID-19)
• Strategic pivots such as the shift to original content
• Market reactions to earnings, acquisitions, and subscriber milestones

This makes the dataset ideal for:

• Time-series forecasting (ARIMA, Prophet, LSTM)
• Technical and trend analysis (moving averages, RSI, Bollinger Bands)
• Predictive modeling with machine learning
• Investment simulation projects
• Stock market visualization and storytelling
• Financial dashboards (Tableau, Power BI, Streamlit, etc.)

Who Can Use It?

This dataset is designed for:

• Aspiring data scientists practicing EDA and modeling
• Financial analysts and traders exploring trends
• AI researchers working on time-series models
• Students building ML projects
• Developers creating stock visualization tools
• Kaggle competitors seeking real-world datasets

Data Source & Credits

The dataset is derived from publicly available historical stock price data, such as Yahoo Finance, and has been cleaned and organized for educational and research purposes. It is continuously maintained to ensure accuracy.

Start Exploring

Netflix’s rise is more than just a business story — it’s a data-driven journey. With this dataset, you can analyze the company’s stock behavior, train models to predict future trends, or simply visualize how tech reshapes the market.

Netflix reported $458.27B in Market Capitalization this December of 2025, considering the latest stock price and the number of outstanding shares.Data for Netflix | NFLX - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Welcome to the Netflix Stock Prices and Performance Data dataset! This dataset is your go-to resource for analyzing the financial performance of Netflix, Inc. over time. Whether you’re a seasoned data scientist, a finance enthusiast, or a beginner looking to practice your time series analysis skills, this dataset provides all the key metrics you need.

Date: The trading day (YYYY-MM-DD format) Open: Opening price of the stock on that day High: Highest price reached during the trading day Low: Lowest price reached during the trading day Close: Closing price of the stock on that day Volume: Number of shares traded Potential Uses:

Trend Analysis: Examine how Netflix’s stock price has evolved over time and identify significant trends or events that impacted its performance.

Technical Analysis: Apply various technical indicators to forecast future stock movements.

Investment Strategy Development: Create and backtest trading strategies based on historical data.

Correlation Studies: Compare Netflix’s stock performance with other stocks or indices to uncover correlations.

Market Sentiment Analysis: Integrate with news or social media sentiment data to see how external factors influence stock prices.

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.

Netflix reported $6.16B in Cost of Sales for its fiscal quarter ending in September of 2025. Data for Netflix | NFLX - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Netflix reported $5.35B in Gross Profit on Sales for its fiscal quarter ending in September of 2025. Data for Netflix | NFLX - Gross Profit On Sales including historical, tables and charts were last updated by Trading Economics this last December in 2025.

This dataset offers an in-depth analysis of Netflix's stock performance over the last decade, incorporating numerous technical indicators to examine its price fluctuations. It includes the recording date and several vital statistics: the opening, highest, lowest, and closing prices for each trading day, along with the trading volume. It also contains momentum indicators like the 7-day and 14-day Relative Strength Index (RSI) to determine if the stock is overbought or oversold. The Commodity Channel Index (CCI) for 7 and 14 days is also included, helping identify short- and medium-term market trends by comparing the current price to the historical average. The dataset integrates the 50-day and 100-day Simple Moving Average (SMA) and Exponential Moving Average (EMA), which shed light on the stock's trend direction. Additional important indicators are the Moving Average Convergence Divergence (MACD), Bollinger Bands for assessing price volatility, the True Range, and the 7-day and 14-day Average True Range (ATR), which provide a gauge of market volatility. This dataset is designed to forecast the closing price for the following day, making it a crucial tool for predicting future movements of Netflix's stock.

Please find descriptions for the columns.

• Open: The price at which a stock first trades upon the opening of an exchange on a trading day.

• High: The highest price at which a stock traded during the trading day.

• Low: The lowest price at which a stock traded during the trading day.

• Close: The final price at which a stock trades during a trading day.

• Volume: The total number of shares of a stock traded during a trading day.

• RSI_7 / RSI_14: The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. RSI_7 and RSI_14 indicate the RSI calculated over 7 days and 14 days, respectively. https://www.investopedia.com/terms/r/rsi.asp

• CCI_7 / CCI_14: The Commodity Channel Index (CCI) is a versatile indicator that can be used to identify a new trend or warn of extreme conditions. CCI_7 and CCI_14 are calculated over 7 days and 14 days, respectively. https://www.investopedia.com/terms/c/commoditychannelindex.asp

• SMA_50 / SMA_100: The Simple Moving Average (SMA) is calculated by averaging the price of a stock over a specific number of days. SMA_50 and SMA_100 are the averages over 50 days and 100 days, respectively. https://www.investopedia.com/terms/s/sma.asp

• EMA_50 / EMA_100: The Exponential Moving Average (EMA) gives more weight to more recent prices and thus reacts more quickly to price changes than the SMA. EMA_50 and EMA_100 are calculated over 50 days and 100 days, respectively. https://www.investopedia.com/terms/e/ema.asp

• MACD: The Moving Average Convergence Divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a stock’s price. https://www.investopedia.com/terms/m/macd.asp

• Bollinger Bands (Bollinger): A set of lines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a stock's price. https://www.investopedia.com/terms/b/bollingerbands.asp

• True Range: The greatest of the following: current high minus the current low, the absolute value of the current high minus the previous close, or the absolute value of the current low minus the previous close.

• ATR_7 / ATR_14: The Average True Range (ATR) is a measure of volatility that shows how much a stock moves, on average, over a given period. ATR_7 and ATR_14 are calculated over 7 days and 14 days, respectively. https://www.investopedia.com/terms/a/atr.asp

• Next Day Close: Future price. Closing price of a stock for the following trading day. Can be used as target variable for regression predictions.

In 2024, the total revenue of the video streaming platform Netflix amounted to approximately ** billion U.S. dollars, having grown from *** billion U.S. dollars a decade ago. The American media company's net income in 2023 stood at *** billion U.S. dollars, with a total of ****** employees working at the company worldwide. The fiscal year end of the company is December 31. Netflix annual revenue – additional information Netflix has been very successful in the last few years. The company not only leads the subscription streaming market in the U.S., but is effectively expanding its service outside North America. Along with gaining numerous subscribers worldwide, Netflix has managed to produce and distribute high-profile original shows, such as "House of Cards" and "Orange is the New Black," challenging traditional TV networks like HBO and CBS. In 2023, Netflix’s original programs received 103 Emmy Awards nominations, around double the number of nominations received 7 years previously. These are just a few indicators of Netflix’s success, which can be measured in a number of ways. Firstly, as seen in the statistic, Netflix’s annual revenue has consistently increased over the years, reaching the highest figure to date in 2023 – **** billion U.S. dollars. This figure is around ** times higher than Netflix’s annual revenue a decade ago. Netflix's originals The time that consumers dedicate to watching Netflix content is another way of indicating success. One of Netflix’s strategies has been to release TV series in bulk, so consumers are able to binge watch their favorite shows. Indeed, Netflix accounts for the highest share of most in-demand originals among global video streaming services. As a result, Netflix's streaming content obligations have increased from *** billion U.S. dollars in 2010 to over ** billion U.S. dollars in 2023.

About this Dataset

This dataset offers a comprehensive, up-to-date look at the historical stock performance of Netflix Inc. (NFLX), the world's leading streaming entertainment service.

About the Company

Netflix, Inc. is an American entertainment company founded in 1997. It began as a DVD-by-mail service before revolutionizing the industry with its streaming platform in 2007. Headquartered in Los Gatos, California, Netflix is a major player in content creation, production, and distribution, with a massive library of films, television series, and documentaries. As a key technology and media company, Netflix's stock performance is a significant indicator of trends in the entertainment industry and digital consumer behavior.

Key Features

Daily OHLCV Data: The dataset contains essential Open, High, Low, Close, and Volume metrics for each trading day.

Comprehensive History: Includes data from Netflix's early trading history to the present, offering a long-term perspective.

Regular Updates: The dataset is designed for regular, automated updates to ensure data freshness for time-sensitive projects.

Data Dictionary

Date: The date of the trading session in YYYY-MM-DD format.

ticker: The standard ticker symbol for Netflix Inc. on the NASDAQ exchange: 'NFLX'.

name: The full name of the company: 'Netflix Inc.'.

Open: The stock price in USD at the start of the trading session.

High: The highest price reached during the trading day in USD.

Low: The lowest price recorded during the trading day in USD.

Close: The final stock price at market close in USD.

Volume: The total number of shares traded on that day.

Data Collection

The data for this dataset is collected using the yfinance Python library, which pulls information directly from the Yahoo Finance API.

Potential Use Cases

Financial Analysis: Analyze historical price trends, volatility, and trading volume of Netflix stock.

Machine Learning: Develop and test models for stock price prediction and time series forecasting.

Educational Projects: A perfect real-world dataset for students and data enthusiasts to practice data cleaning, visualization, and modeling.

Kaggle Dataset Description

Netflix (NFLX) Stock Price Data (2002-2025)Overview:

This dataset provides historical stock price data for Netflix Inc. (NASDAQ: NFLX) from May 23, 2002, to January 31, 2025. The data has been sourced from Yahoo Finance and includes essential financial metrics, making it valuable for financial analysis, stock price prediction, and time-series forecasting.

Dataset Features:

Date: The trading date (YYYY-MM-DD format).

Open: Opening price of Netflix stock on that trading day.

High: Highest price recorded during the trading session.

Low: Lowest price recorded during the trading session.

Close: Closing price of the stock at the end of the trading session.

Adj Close: Adjusted closing price, accounting for corporate actions such as stock splits and dividends.

Volume: The total number of Netflix shares traded on the respective day.

Usage & Applications:

Stock Price Analysis – Evaluate historical trends and identify key patterns.

Time-Series Forecasting – Train predictive models for stock market behavior.

Volatility & Risk Assessment – Analyze price fluctuations over time.

Trading Strategy Development – Backtest investment strategies.

Data Source: Extracted using Yahoo Finance API.

License & Citation:

This dataset is publicly available and should be credited to Yahoo Finance API and Muhammad Atif Latif when used in research or projects.

More Stocks Datasets

If you want to check out my more stocks related Datasets then CLICK HERE

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.

Context

The art of forecasting stock prices has been a difficult task for many of the researchers and analysts. In fact, investors are highly interested in the research area of stock price prediction. For a good and successful investment, many investors are keen on knowing the future situation of the stock market. Good and effective prediction systems for the stock market help traders, investors, and analyst by providing supportive information like the future direction of the stock market. In this work, we present a recurrent neural network (RNN) and Long Short-Term Memory (LSTM) approach to predict stock market indices.

Content

Data from yahoo.com/finance Netflix historical price 12/16/2015 ~ 12/16/2019 daily price and volume. There are 7 columns; Date, open, high, low, close, volume, adj close (2001, 7) each of stock

Acknowledgements

I want to find relationship between volume and price.

Inspiration

Here is couple of things one could try out with this data:

One day ahead prediction: Rolling Linear Regression, ARIMA, Neural Networks, LSTM
Momentum/Mean-Reversion Strategies
Security clustering, portfolio construction/hedging

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Disney+ has experienced remarkable growth since its launch in November 2019, reaching around 127.8 million global subscribers in the third quarter of 2025. The streaming service's rapid ascent is particularly noteworthy given that it took Netflix, the current market leader, about a decade to achieve similar customer numbers in a less competitive landscape. Disney's biggest streaming competitor Despite its impressive subscriber base, Disney+ faces stiff competition in the streaming market, particularly among younger viewers. As of October 2023, Netflix remained the most-watched subscription video-on-demand service among U.S. children, capturing 34 percent of the audience, with Disney+ following at 31 percent. To address profitability challenges and retain customers, Disney has implemented strategies such as introducing extra member pricing in various countries, with costs ranging from 3.58 U.S. dollars in Hong Kong to 6.67 U.S. dollars in Italy. Market adaptation In response to the evolving streaming landscape, Disney has adjusted its pricing strategy. In late 2024, the company once again increased its monthly subscription prices for Disney+, Hulu, and ESPN+ in the United States. This move followed significant improvements in the provider's direct-to-consumer streaming segment, with operating losses decreasing substantially between 2022 and 2024. Disney's DTC entertainment business, for example, reported an income of about 143 million U.S. dollars in 2024 after years of making losses, demonstrating that Disney's efforts to achieve profitability seemed to have paid off.

Dataset Description: Netflix vs. Disney Price and Split

This dataset provides a comprehensive analysis of the stock performance of two leading entertainment companies: Netflix (NFLX) and Disney (DIS). It includes historical data on stock prices, stock splits, and relevant metrics to facilitate a detailed comparison between the two streaming giants.

Key Components:

Daily Stock Prices: This section includes the daily open, high, low, close prices, and trading volume for both Netflix and Disney. It allows for the examination of market trends and price movements over time.

Stock Splits: The dataset details any stock splits that have occurred for both companies, including the date of the split and the split ratio. Understanding stock splits is crucial for assessing changes in stock value and investor sentiment.

Comparison Metrics: The dataset enables analysts and investors to compare critical financial indicators, providing insights into each company's growth strategies and market positioning.

Purpose:

This dataset is designed for financial analysts, investors, and researchers interested in the streaming industry and its leading players. By examining the historical stock prices and split data, users can gain insights into the financial health and market dynamics of Netflix and Disney, aiding in informed investment decisions and strategic analysis.

Data Sources:

Alpha Vantage: Used for fetching daily stock price and dividend data. Yahoo Finance (yfinance): Utilized for obtaining stock splits information

FAANG

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• FAANG is an acronym referring to the stocks of the five most popular and best-performing American technology companies: Meta (formerly known as Facebook), Amazon, Apple, Netflix, and Alphabet (formerly known as Google).

• In addition to being widely known among consumers, the five FAANG stocks are among the largest companies in the world, with a combined market capitalization of nearly $7.1 trillion as of Aug. 19, 2021.

• Some have raised concerns that the FAANG stocks may be in the midst of a bubble, whereas others argue that their growth is justified by the stellar financial and operational performance they have shown in recent years.

Each of the FAANG stocks trades on the Nasdaq exchange and is included in the S&P 500 Index. Since the S&P 500 is a broad representation of the market, the movement of the market mirrors the index's movement. As of August 2021, the FAANGs make up about 19% of the S&P 500—a staggering figure considering the S&P 500 is generally viewed as a proxy for the United States economy as a whole.

This large influence over the index means that volatility in the stock price of the FAANG stocks can have a substantial effect on the performance of the S&P 500 in general. In August 2018, for example, FAANG stocks were responsible for nearly 40% of the index’s gain from the lows reached in February 2018.

What Makes FAANG Stocks So Popular?

• The five stocks that make up the “FAANG” acronym - Meta (FB), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOG) are all well-known brands among consumers. But they are also famous for their remarkable growth in recent years, with market capitalizations ranging from $240 billion (in the case of Netflix)3 to $2.4 trillion (in the case of Apple), as of August 2021.

• From an investment perspective, these five stocks are generally praised for their stellar historical track records and clear leadership positions within their industries.

Datset Information

The dataset consists of the historical stock prices of the FAANG companies. The dataset has been cleaned and uploaded for easy use and analysis.

• Google Class A(GOOGL) consists of 4340 data records of stock prices starting from 20/08/2004 to date(11/11/2021)
• Google Class C(GOOG) consists of 1924 records of GOOG stocks starting from 28/03/2004 to date.
• Apple (AAPL) consists of 10319 records starting from 12/12/1980 to date
• Amazon(AMZN) consists of 6167 records starting from 15/5/1997 to date
• Meta(FB) consists of 2389 records from 18/05/2012 records to date
• Netflix(NFLX) consists of 4904 records from 24/05/2002 to date

Note:

You might find two different types of google stocks GOOGL and GOOG in the dataset.

• GOOGL

  • GOOGL shares are categorized as Class A shares. Class A shares are known as common shares. They give investors an ownership stake and, typically, voting rights. They are the most common type of shares.

• GOOG

  • GOOG shares are the company's Class C shares. Class C shares give stockholders an ownership stake in the company, just like Class A shares, but unlike common shares, they do not confer voting rights to shareholders.

Class A: Held by a regular investor with regular voting rights (GOOGL) Class B: Held by the founders with 10 times the voting power compared to Class A Class C: No voting rights, normally held by employees and some Class A stockholders (GOOG)

Inspiration

• Annual growth rate of FAANG companies
• Forecast the growth rate of FAANG companies in the next ten years
• Exploratory data analysis