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Data Trends for Investment Professionals

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FEATURED POST

The Data Factory

This is an introduction to a series of blog posts exploring the data factory, the premier approach to data management.  The data explosion From the evolving landscape of data privacy regulation to record-breaking acquisitions in data production, distribution and analytics, the world has its eye on data.  Even in the finance industry, data is...

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API USAGE GUIDES Jan 22 2014

API for Housing Data

Using the Quandl API for Housing Data This document is a comprehensive guide to using the Quandl API to access our free house price data. If you haven't already done so, we recommend reading Quandl's general API documentation; the functionality will be a lot clearer if you do so. Free Unlimited API for Housing Data Quandl offers 30+ real estate market indicators for over 35,000 geographical areas across the United States. Quandl's easy to use API gives access to housing prices and housing market data. With numerous software packages, including R and Python, Quandl is the easiest way to find...

INDUSTRY TRENDS Jan 16 2014

Data: The Big Picture

These are the slides from a 2-hour talk I gave at IRMAC Canada in January 2014. I cover a lot of ground: The problem of finding information on the internet The evolution of search, from manual to automated to vertical Building a data search engine Transitioning to a data platform The criticality of user-driven content in the data world The role played by open data The age of data ubiquity Network effects for data The emerging data layer Data as a Service An explosion of context What it all means for you   [pdf-embedder url="https://blog.quandl.com/wp-content/uploads/2015/09/Quandl-at-Irmac.pdf"]   You can download the entire...

DATA ANALYSIS TIPS Dec 16 2013

Cheat Sheet for Data Analysis in Python

This is a quick reference for data gathering and analysis using the NumPy, SciPy, Pandas and Quandl packages for Python:   [pdf-embedder url="https://blog.quandl.com/wp-content/uploads/2013/12/Quandl-NumPy-SciPy-Pandas-Cheat-Sheet.pdf"]   You can download this document here.

DATA ANALYSIS TIPS Dec 15 2013

Cheat Sheet for Data Analysis in R

This is a quick reference for data acquisition and analysis using R and Quandl.   [pdf-embedder url="https://blog.quandl.com/wp-content/uploads/2013/12/Quandl-R-Cheat-Sheet.pdf"]   You can download a PDF of this file here.

API USAGE GUIDES Nov 13 2013

API for Interest Rate Data

API for Interest Rate Data Quandl provides a single easy-to-use API for current and historical interest rate data. Coverage includes short-term money market rates, long-term bond yields, commercial paper interest rates, corporate bond rates, forward rate curves, time deposit interest rates, lending interest rates, and more. Example Calls Interest rate on US government 3-month treasury bills: Free: https://www.quandl.com/api/v3/datasets/FRED/DTB3.csv?api_key=YOURAPIKEY Premium: https://www.quandl.com/api/v3/datasets/YC/USA3M.csv?api_key=YOURAPIKEY US government yield curve: Free: https://www.quandl.com/api/v3/datasets/USTREASURY/YIELD.csv?api_key=YOURAPIKEY Premium: https://www.quandl.com/api/v3/datasets/YC/USA.csv?api_key=YOURAPIKEY Japanese government 10-Year bond yields: Free: Not Available Premium: https://www.quandl.com/api/v3/datasets/YC/JPN10Y.csv?api_key=YOURAPIKEY Note: Premium databases are more reliable, accurate, comprehensive and timely than open databases. You can preview all premium databases for free; all...

API USAGE GUIDES Nov 07 2013

API for Economic Data

Using the Quandl API for Economic Data This document is a comprehensive guide to using the Quandl API to access our economic data.The mechanism for accessing economic data via the Quandl API is no diferent from the mechanism for accessing all data on Quandl. The purpose of this help page is mainly to explain the specific publishers and nomenclature for economic data. For further information on the Quandl data API, read our general API reference. You can also access Quandl data directly from within the analysis tool of your choice - Stata, SAS, R, Python, Matlab, Maple, EViews and more...

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