API reference · FRED

fred/series-observations

Integrate this model through SandBase's unified API, with production-ready schemas and examples.

APISynchronousOpen model

Production endpoint

Send your first request

OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/api/fred/series-observations

Model IDfred/series-observations

Input Schema

14 parameters · 1 required · 13 optional

Parameter	Type	Required	Description
`series_id`	string	Required	The id for a series. string, required
`limit`	integer	Optional	The maximum number of results to return. integer between 1 and 100000, optional, default: 100000 · Min: 1 · Max: 100000 · Default: 100000
`units`	string	Optional	A key that indicates a data value transformation. string, optional, default: lin (No transformation) One of the following values: 'lin', 'chg', 'ch1', 'pch', 'pc1', 'pca', 'cch', 'cca', 'log' lin = Levels (No transformation) chg = Change ch1 = Change from Year Ago pch = Percent Change pc1 = Percent · Options: lin, chg, ch1, pch, pc1, pca, cch, cca, log · Default: "lin" linchgch1pchpc1pcacchccalog
`offset`	integer	Optional	non-negative integer, optional, default: 0 · Min: 0 · Default: 0
`file_type`	string	Optional	Response format. Only json is supported. · Options: json · Default: "json" json
`frequency`	string	Optional	An optional parameter that indicates a lower frequency to aggregate values to. The FRED frequency aggregation feature converts higher frequency data series into lower frequency data series (e.g. converts a monthly data series into an annual data series). In FRED, the highest frequency data is daily, · Options: d, w, bw, m, q, sa, a, wef, weth, wew, wetu, wem, wesu, wesa, bwew, bwem dwbwmqsaawefwethwewwetuwemwesuwesabwewbwem
`sort_order`	string	Optional	Sort results is ascending or descending observation_date order. One of the following strings: 'asc', 'desc'. optional, default: asc · Options: asc, desc · Default: "asc" ascdesc
`output_type`	integer	Optional	An integer that indicates an output type. integer, optional, default: 1 One of the following values: '1', '2', '3', '4' 1 = Observations by Real-Time Period 2 = Observations by Vintage Date, All Observations 3 = Observations by Vintage Date, New and Revised Observations Only 4 = Observations, Initia · Options: 1, 2, 3, 4 · Default: 1 1234
`realtime_end`	string	Optional	The end of the real-time period. For more information, see Real-Time Periods , vintage_dates . YYYY-MM-DD formatted string, optional, default: today's date
`vintage_dates`	string	Optional	A comma separated string of YYYY-MM-DD formatted dates in history (e.g. 2000-01-01,2005-02-24). Vintage dates are used to download data as it existed on these specified dates in history. Vintage dates can be specified instead of a real-time period using realtime_start and realtime_end. Sometimes it
`realtime_start`	string	Optional	The start of the real-time period. For more information, see Real-Time Periods , vintage_dates . YYYY-MM-DD formatted string, optional, default: today's date
`observation_end`	string	Optional	The end of the observation period. YYYY-MM-DD formatted string, optional, default: 9999-12-31 (latest available) · Default: "9999-12-31"
`observation_start`	string	Optional	The start of the observation period. YYYY-MM-DD formatted string, optional, default: 1776-07-04 (earliest available) · Default: "1776-07-04"
`aggregation_method`	string	Optional	A key that indicates the aggregation method used for frequency aggregation. This parameter has no affect if the frequency parameter is not set. string, optional, default: avg One of the following values: 'avg', 'sum', 'eop' avg = Average sum = Sum eop = End of Period avg = Average sum = Sum eop = En · Options: avg, sum, eop · Default: "avg" avgsumeop

Output Schema

Field	Type	Description
`id`	string	Unique identifier for the generation task
`status`	string	Task status: pending, running, completed, failed, timeout
`model`	string	Model used for the generation
`outputs`	array	Array of output items
`outputs[].url`	string	URL of the generated artifact
`outputs[].content_type`	string	MIME type (e.g. image/png, video/mp4)
`error`	object \| null	Error details if failed, null on success
`error.type`	string	Machine-readable error type code
`error.message`	string	Human-readable error description

Code Examples

Ready-to-run snippets

const apiKey = process.env.SANDBASE_API_KEY;
const response = await fetch("https://api.sandbase.ai/v1/api/fred/series-observations", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "limit": 100000,
    "units": "lin",
    "offset": 0,
    "file_type": "json",
    "sort_order": "asc",
    "output_type": 1,
    "observation_end": "9999-12-31",
    "observation_start": "1776-07-04",
    "aggregation_method": "avg"
  }),
});

if (!response.ok) throw new Error(await response.text());
console.log(await response.json());

← Back to FRED Get Series Observations