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.
