This dataset provides comprehensive real-time data from Amazon's global marketplaces. It includes detailed product information, reviews, seller profiles, best sellers, deals, influencers, and more across all Amazon domains worldwide. The data covers product attributes like pricing, availability, specifications, reviews and ratings, as well as seller information including profiles, contact details, and performance metrics. Users can leverage this dataset for price monitoring, competitive analysis, market research, and building e-commerce applications. The API enables real-time access to Amazon's vast product catalog and marketplace data, helping businesses make data-driven decisions about pricing, inventory, and market positioning. Whether you're conducting market analysis, tracking competitors, or building e-commerce tools, this dataset provides current and reliable Amazon marketplace data. The dataset is delivered in a JSON format via REST API.

This dataset provides real-time Amazon product information collected using a fast and reliable API. It includes a wide range of structured data such as product titles, prices, ratings, reviews, availability, seller details, and top deals or best sellers. The dataset is ideal for anyone working on e-commerce analytics, product comparison tools, sentiment analysis, or market research.

Whether you're a developer building a price tracker, a data scientist analyzing customer reviews, or a researcher studying online shopping trends, this dataset offers rich and fresh data directly from Amazon’s marketplace. It supports use cases like tracking pricing fluctuations, analyzing customer sentiment using NLP, monitoring seller performance, and identifying high-performing products in real time.

Each entry is cleaned and organized for easy analysis, saving you the time and effort of raw data preprocessing. This dataset can be used in academic projects, business intelligence dashboards, or machine learning pipelines that rely on updated product and consumer data.

The data was collected using an API that supports real-time product search, review extraction, and seller insights, making it highly valuable for building scalable, data-driven applications in the e-commerce domain.

Merchant API will provide you with all essential data and metrics for conducting comprehensive competitor analysis, price monitoring, and market niche research.

With Google Shopping API you can get:

• Google Shopping Products listed for the specified keyword. The results include product title, description in Google Shopping SERP, product rank, price, reviews, and rating as well as the related domain. • Full detailed Google Shopping Product Specification. You will receive all product attributes and their content from the product specification page. • A list of Google Shopping Sellers of the specified product. The provided data for each seller includes related product base and total price, shipment and purchase details, and special offers. • Google Shopping Sellers Ad URL with all additional parameters set by the seller.

With Amazon API you can get:

• Results from Amazon product listings according to the specified keyword (product name), location, and language parameters. • A list of ASINs (unique product identifiers assigned by Amazon) of all modifications listed for the specified product and information about the product prices based on ASIN • Amazon Choice products

We offer well-rounded API documentation, GUI for API usage control, comprehensive client libraries for different programming languages, free sandbox API testing, ad hoc integration, and deployment support.

We have a pay-as-you-go pricing model. You simply add funds to your account and use them to get data. The account balance doesn't expire.

This dataset provides comprehensive real-time information on 340 phone products from Amazon, collected using the "Real-Time Amazon Data" API. The data covers various attributes such as product titles, prices, ratings, availability, and sales volume, offering a valuable resource for e-commerce analysis, machine learning projects, and consumer behavior studies focused on mobile phones.

Key features of this dataset include:

• Phone pricing trends: Including original and discounted prices.
• Customer reviews and ratings: Star ratings and the number of reviews for each phone.
• Sales insights: Sales volume and product demand.
• Amazon-specific flags: Information on whether a phone is marked as Best Seller, Amazon Choice, or Prime eligible.
• Product availability: Delivery options and availability status.

This dataset is ideal for:

• Analyzing price fluctuations in the phone market.
• Studying the impact of customer reviews on phone sales.
• Predicting phone sales volume based on price, reviews, and product attributes.
• Creating machine learning models for price optimization or recommendation systems.
• E-commerce insights to develop marketing strategies for phone sales.

Whether you're a data scientist, business analyst, or mobile phone enthusiast, this dataset offers a detailed snapshot of the mobile phone market on Amazon.

Get the needed Amazon product review data right from the data extractor! Collect Amazon review information from 19 Amazon countries from the following domains: - amazon.com - amazon.com.au - amazon.com.br - amazon.ca - amazon.cn - amazon.fr - amazon.de - amazon.in - amazon.it - amazon.com.mx - amazon.nl - amazon.sg - amazon.es - amazon.com.tr

Request Ecommerce Product Review dataset by: - keyword - category - seller - product ID (ASIN)

Amazon E-commerce Reviews Data datasets gathered by keyword, seller, category, or ASIN contain: - Product ID (can be extended to the full product information) - Review content and rating - Review metadata

Amazon extraction results can be delivered by schedule or API request, so the data can be extracted in real-time.

DATAANT uses the in-house web scraping service with no concurrency limitations, so unlimited data extractions can be performed simultaneously.

Output can and attributes can be customized to fit your particular needs.

OpenWeb Ninja's Product Data API provides Product Data, Product Reviews Data, Product Offers, sourced in real-time from Google Shopping - the largest product listings aggregate on the web, listing products from all publicly available e-commerce sites (Amazon, eBay, Walmart + many others).

The API covers more than 35 billion Product Data Listings, including Product Reviews and Product Offers across the web. The API provides over 40 product data points including prices, rating and reviews insights, product details and specs, typical price ranges, and more.

OpenWeb Ninja's Product Data common use cases: - Price Optimization & Price Comparison - Market Research & Competitive Analysis - Product Research & Trend Analysis - Customer Reviews Analysis

OpenWeb Ninja's Product Data Stats & Capabilities: - 35B+ Product Listings - 40+ data points per job listing - Global aggregate - Search by keyword or GTIN/EAN

The Mobile Backend as a Service (mBaaS) market is booming, projected to reach $45 billion by 2033 with an 18% CAGR. Learn about key drivers, trends, and top companies shaping this dynamic industry, including Amazon, Google, and Salesforce. Explore market segmentation and regional analysis for a comprehensive overview.

The Mobile Backend as a Service (MBaaS) market is booming, projected to reach $32.12 billion by 2033. Discover key trends, drivers, and top players shaping this dynamic industry, including cloud-based solutions, enterprise adoption, and regional growth insights.

Discover the booming High-Performance Message Infrastructure (HPMI) market. This in-depth analysis reveals key trends, drivers, and challenges shaping this dynamic sector, featuring leading players like AWS, Salesforce, and Red Hat. Explore market size projections, CAGR, and regional breakdowns to gain valuable insights for investment and strategic planning.

I have created this dataset to showcase the use of predictive modeling using the stock market as a case study. This dataset is designed to help and predict tomorrow's Amazon stock price. If you want to get the most updated dataset you will need to pull them in real time. I have shared my code to pull data using Yahoo Finance API and preprocess it in Data Analytics for Fun Github Repository

The uploaded dataset is for Jan 11, 2021.

What are the columns?

yes_changeP: Yesterday Amazon's stock price change lastweek_changeP: Last week Amazon's stock price change dow_yes_changeP: Yesterday Dow Jones change dow_lastweek_changeP: Last Week Dow Jones change nasdaq_yes_changeP: Yesterday NASDAQ 100 change nasdaq_lastweek_changeP: Last Week NASDAQ 100 change today_changeP: Today Amazon's stock price change

To learn more about the dataset and see a very simple prediction model applied to the dataset you may watch this YouTube Video where I have explained the dataset and also prediction: A Taste for Prediction: Predict Tomorrow's Amazon Stock Price

The intelligent voice transcription platform market is booming, projected to reach $1466.8 million in 2025, driven by AI advancements and cloud adoption. Explore market trends, key players (like Amazon Transcribe & Google Speech-to-Text), and regional growth forecasts in this comprehensive analysis.

The Notification Infrastructure Software market is booming, projected to reach [estimated value] by 2033. Learn about key drivers, trends, restraints, leading companies (SuprSend, MoEngage, Amazon, etc.), and regional market analysis in this comprehensive market report. Discover how businesses are leveraging push notifications, email, and SMS to boost engagement and personalize customer experiences.

We benchmarked the best web scraper API services using 12,500 requests across various domains. This web crawling services comparison goes beyond marketing claims to reveal real-time performance in e-commerce (Amazon, Target), search engines (SERP), and social media.

About this Dataset

This dataset offers a comprehensive, up-to-date look at the historical stock performance of Amazon.com Inc. (AMZN), one of the world's most influential technology and e-commerce companies.

About the Company

Amazon.com Inc. is an American multinational technology company founded in 1994 by Jeff Bezos. It is best known for its e-commerce, cloud computing (Amazon Web Services), digital streaming, and artificial intelligence ventures. Headquartered in Seattle, Washington, Amazon has grown to be a global leader in online retail and is a key component of the S&P 500, making its stock performance a significant indicator of consumer spending and technology sector trends.

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 Amazon's early trading history to the present, offering a long-term perspective.

High-Quality Data: The data is clean and sourced from a reliable financial API, ideal for direct use in analysis and modeling.

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 Amazon.com Inc. on the NASDAQ exchange: 'AMZN'.

name: The full name of the company: 'Amazon.com 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 Amazon 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.