Quandl API Documentation

Welcome to Quandl. You'll find comprehensive guides and documentation to help you start working with Quandl as quickly as possible, as well as support if you get stuck. Let's get started.

Guides    

TIME-SERIES

Make a time-series call

This call gets the WTI Crude Oil Price, which has a Quandl Code of EIA/PET_RWTC_D from the US Department of Energy dataset: data = quandl.get("EIA/PET_RWTC_D")

Change formats

You can get the same data in a NumPy array: data = quandl.get("EIA/PET_RWTC_D", returns="numpy")

Make a filtered time-series call

To set start and end dates: data = quandl.get("FRED/GDP", start_date="2001-12-31", end_date="2005-12-31")

To request specific columns: data = quandl.get(["NSE/OIL.1", "WIKI/AAPL.4"])

To request the last 5 rows: data = quandl.get("WIKI/AAPL", rows=5)

Preprocess the data

To change the sampling frequency: data = quandl.get("EIA/PET_RWTC_D", collapse="monthly")

To perform elementary calculations on the data: data = quandl.get("FRED/GDP", transformation="rdiff")

Download an entire time-series dataset

An entire time-series dataset's data can be downloaded.

For example, to download the dataset ZEA: quandl.bulkdownload("ZEA")

This call will download an entire time-series dataset as a ZIP file.

NOTE:

For a full list of optional query parameters for downloading a time-series dataset, click here.

TIME-SERIES