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.



For your convenience, Quandl has optimized our datasets for one of two different formats: 1) Time-series and 2) Tables.



To find out whether a dataset supports time-series or tables, simply go to the Data section of its documentation and look under API.

For example, the FRED dataset shows an API type of Time-series, whereas the Mergent Global Fundamentals dataset shows an API type of Tables.

As a data platform, we take great pains to consider the best shape to format our different datasets. Currently, most of our datasets are accessible in either time-series format or table format. A few of our datasets, however, are accessible in both time-series and table format. Consequently, it is important to understand the differences and overlaps between the two data formats.

The Time-series API

A time-series is a collection of observations or measurements taken over a period of time, generally in equal intervals. Time-series are commonly displayed using line graphs, where the X-axis represents dates and the Y-axis represents other numeric observations.

It is important to note that time-series only contain numeric data types and are indexed by one date field. In other words, time-series data are always sorted by date. Through our API calls, users can retrieve the entire time-series as well as a slice of it.

Most of Quandl's datasets are stored as time-series because financial data generally consists of two types: dates and observations, which perfectly fit the time-series format.

The Tables API

While time-series only contain sorted numeric values, tables can include various unsorted data types (strings, numbers, dates, etc.) and can be filtered by different fields.

Updated 2 years ago


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