Data Trends for Investment Professionals

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The Cost of Free Data: Why Use Premium Stock Prices?

Quandl has always prided itself on making financial and economic data accessible to all investors. This is why a number of our datasets are free resources, like the Federal Reserve Economic Data (FRED) and US Energy Information Administration Data (EIA). While we’re happy to support these products for the foreseeable future, we nonetheless advocate for the use of premium sources for professional investors. Understandably, one of the most common questions we get is "Why should users pay for premium stock price data, when stock quotes are available for free from many different sources?" Free sources may be appropriate for casual...

One Doc to Rule Them All: Quandl Launches API Documents 2.0

An API is only as good as its documentation. Everyone knows that. But not everyone knows how much work goes into making (and then keeping) documentation good. From the dev and marketing teams to the data scientists and UX specialists (not to mention the insightful user feedback we’ve been receiving since day one), we need all hands on deck to build, deliver and maintain good docs. As some of our users have pointed out, our API documentation has needed a revamp for some time now. Because of Quandl’s constantly growing functionality and tools, we kept adding to our docs piecemeal...

Bring Your Own Tool: the Latest Trend in Data Analysis

The role of the data analyst is changing. The best analysts know that different tasks require different tools. The End of Bundling Once upon a time, data purchases came bundled with data consumption software. You couldn't just buy a dataset; you had to install a proprietary data downloader. You couldn’t just view the data on your computer; you needed a custom visualizer, or even a full-fledged data terminal. And you couldn't do whatever you wanted with the data; you were forced to work within the applications provided to you by the vendor. Today, this seems absurd. In 2016, analysts don't...

Expanding Quandl’s European Futures Data

Futures data has always been an area of focus for Quandl. Our newest databases expand our coverage significantly. Futures Data on Quandl When we launched Quandl three years and 20 million datasets ago, futures coverage was a major strength. We had excellent data for North American futures markets, especially the CME and CBOT. Over the years, we added several more North American exchanges: ICE, Minneapolis, Montreal and CBOE. We also added supporting data from the CFTC. Then we expanded into international markets: futures data from Singapore, Shanghai, Tokyo, Osaka, Mumbai, Dubai and other exchanges. When we launched our data marketplace...

API for Stock Data

Quandl offers a simple API for stock market data. The API delivers end-of-day prices, harmonized fundamentals, financial ratios, indexes, options and volatility, earnings estimates, analyst ratings, investor sentiment and more. Example Calls AAPL stock price: Free: https://www.quandl.com/api/v3/datasets/WIKI/AAPL.csv?api_key=YOURAPIKEY Premium: https://www.quandl.com/api/v3/datasets/EOD/AAPL.csv?api_key=YOURAPIKEY AAPL revenue: Free: https://www.quandl.com/api/v3/datasets/SEC/AAPL_SALESREVENUENET_Q.csv?api_key=YOURAPIKEY Premium: https://www.quandl.com/api/v3/datasets/SF1/AAPL_REVENUE_MRQ.csv?api_key=YOURAPIKEY Sign up for a free API key To find the data you need, use the guide below or use our data browser. Use our quick start guide to learn our API syntax, or go to our documentation portal for a full reference. If you prefer, you can get data via our libraries for Python, R,...

Getting Started with the Quandl API

Every single dataset on Quandl is available via our API. The API is simple, consistent and completely free to use. Here's a quick and easy guide to get you started. This is not meant to be a formal reference for the Quandl API; merely a quick-start guide. To read the complete and definitive documentation, please click here. To start using the Quandl API: Sign up for a free API key Synopsis Here is an API call for FB stock data in CSV format: https://www.quandl.com/api/v3/datasets/WIKI/FB/data.csv Here is the same call, with some additional parameters appended: https://www.quandl.com/api/v3/datasets/WIKI/FB/data.csv?column_index=4&exclude_column_names=true&rows=3&start_date=2012-11-01&end_date=2013-11-30&order=asc&collapse=quarterly&transform=rdiff The second call gets FB stock...

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