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fred_get_series

Retrieve any FRED time series data by ID with support for data transformations, frequency changes, and custom date ranges.

Overview

The fred_get_series tool is your primary interface for accessing actual economic data. It supports:
  • Retrieving observations for any of the 800,000+ series
  • Applying mathematical transformations (growth rates, percent changes)
  • Converting between frequencies (daily to monthly, monthly to quarterly)
  • Custom date ranges and vintage data
  • Multiple aggregation methods

Parameters

series_id
string
required
The FRED series ID to retrieve data for.Popular IDs:
  • GDP: Gross Domestic Product
  • UNRATE: Unemployment Rate
  • CPIAUCSL: Consumer Price Index
  • DFF: Federal Funds Rate
  • SP500: S&P 500 Index
Finding IDs: Use fred_search or fred_browse to discover series IDs
observation_start
string
Start date for observations in YYYY-MM-DD format.Examples:
  • 2024-01-01: Start of 2024
  • 2020-03-01: Beginning of pandemic period
  • 2008-09-01: Start of financial crisis
Default: Series start date
observation_end
string
End date for observations in YYYY-MM-DD format.Examples:
  • 2024-12-31: End of 2024
  • 2023-12-31: Full year 2023
Default: Most recent available data
limit
number
default:"100000"
Maximum number of observations to return (1-100000).Usage:
  • Small limits for recent data: 12 for last year of monthly data
  • Large limits for historical analysis
offset
number
default:"0"
Number of observations to skip from the beginning.
sort_order
string
default:"asc"
Sort order of observations by date.Options:
  • asc: Chronological order (oldest first)
  • desc: Reverse chronological (newest first)
units
string
default:"lin"
Data transformation to apply.Options:
  • lin: Levels (no transformation) - raw values
  • chg: Change from previous period
  • ch1: Change from year ago
  • pch: Percent change from previous period
  • pc1: Percent change from year ago
  • pca: Compounded annual rate of change
  • cch: Continuously compounded rate of change
  • cca: Continuously compounded annual rate
  • log: Natural logarithm
Common uses:
  • pc1 for year-over-year inflation
  • pch for month-over-month growth
  • log for regression analysis
frequency
string
Frequency aggregation/conversion.Main options:
  • d: Daily
  • w: Weekly
  • bw: Biweekly
  • m: Monthly
  • q: Quarterly
  • sa: Semiannual
  • a: Annual
Weekly variants:
  • wef: Week Ending Friday
  • weth: Week Ending Thursday
  • wew: Week Ending Wednesday
  • wetu: Week Ending Tuesday
  • wem: Week Ending Monday
  • wesu: Week Ending Sunday
  • wesa: Week Ending Saturday
Default: Native series frequency
aggregation_method
string
default:"avg"
Method for aggregating to lower frequencies.Options:
  • avg: Average over period
  • sum: Sum of values in period
  • eop: End of period value
Usage examples:
  • avg for interest rates, prices
  • sum for flows like GDP, sales
  • eop for stock prices, levels
output_type
number
default:"1"
Output format type.Options:
  • 1: Time series observations
  • 2: Observations by vintage date
  • 3: Observations by release date
  • 4: Initial release only
Note: Types 2-4 for vintage analysis
vintage_dates
string
Specific vintage date(s) in YYYY-MM-DD format.Usage:
  • Single date: 2024-01-01
  • Date range: 2024-01-01:2024-12-31
Purpose: Retrieve data as it existed on specific dates

Examples

Basic Series Retrieval

{
  "tool": "fred_get_series",
  "params": {
    "series_id": "UNRATE",
    "limit": 12
  }
}

Year-over-Year Inflation

{
  "tool": "fred_get_series",
  "params": {
    "series_id": "CPIAUCSL",
    "units": "pc1",
    "observation_start": "2024-01-01",
    "limit": 12
  }
}

Quarterly GDP Growth

{
  "tool": "fred_get_series",
  "params": {
    "series_id": "GDPC1",
    "units": "pca",
    "observation_start": "2023-01-01",
    "observation_end": "2024-12-31"
  }
}

Convert Daily to Monthly

{
  "tool": "fred_get_series",
  "params": {
    "series_id": "DFF",
    "frequency": "m",
    "aggregation_method": "avg",
    "observation_start": "2024-01-01",
    "limit": 12
  }
}

Common Use Cases

Economic Dashboard

// GDP Growth (Quarterly)
{
  "series_id": "GDPC1",
  "units": "pca",
  "limit": 8
}

// Unemployment Rate (Monthly)
{
  "series_id": "UNRATE",
  "limit": 24
}

// Inflation Rate (Monthly YoY)
{
  "series_id": "CPIAUCSL",
  "units": "pc1",
  "limit": 24
}

// Federal Funds Rate (Daily)
{
  "series_id": "DFF",
  "limit": 30
}

Historical Analysis

// Long-term GDP growth
{
  "series_id": "GDPC1",
  "units": "pc1",
  "observation_start": "1950-01-01",
  "frequency": "a"
}

// Unemployment during recessions
{
  "series_id": "UNRATE",
  "observation_start": "2007-01-01",
  "observation_end": "2010-12-31"
}

// Inflation in the 1970s
{
  "series_id": "CPIAUCSL",
  "units": "pc1",
  "observation_start": "1970-01-01",
  "observation_end": "1979-12-31"
}

Financial Market Indicators

// 10-Year Treasury Yield
{
  "series_id": "DGS10",
  "limit": 252  // ~1 year of trading days
}

// Yield Curve (10Y-2Y Spread)
// Requires two calls and calculation
{
  "series_id": "T10Y2Y",
  "limit": 252
}

// S&P 500 Monthly Returns
{
  "series_id": "SP500",
  "units": "pch",
  "frequency": "m",
  "aggregation_method": "eop"
}

Transformation Examples

Growth Rate Calculations

{
  "series_id": "PAYEMS",
  "units": "chg",
  "limit": 12
}
Returns absolute change from previous month

Frequency Conversions

{
  "series_id": "DFF",
  "frequency": "m",
  "aggregation_method": "avg"
}
Average daily values into monthly

Key Economic Indicators

Series IDDescriptionFrequencyCommon Transform
GDPNominal GDPQuarterlyunits: "pch"
GDPC1Real GDPQuarterlyunits: "pca"
UNRATEUnemployment RateMonthlyNone (already %)
PAYEMSNonfarm PayrollsMonthlyunits: "chg"
CPIAUCSLCPI All UrbanMonthlyunits: "pc1"
CPILFESLCore CPIMonthlyunits: "pc1"
PCEPIPCE Price IndexMonthlyunits: "pc1"

Interest Rates

Series IDDescriptionFrequencyNotes
DFFFed Funds EffectiveDailyCurrent policy rate
DGS1010-Year TreasuryDailyLong-term rate
DGS22-Year TreasuryDailyShort-term rate
TB3MS3-Month T-BillMonthlyRisk-free rate
MORTGAGE30US30-Year MortgageWeeklyConsumer rate

Market Indicators

Series IDDescriptionFrequencyTransform for Returns
SP500S&P 500 IndexDailyunits: "pch"
DJIADow JonesDailyunits: "pch"
NASDAQCOMNASDAQ CompositeDailyunits: "pch"
VIXCLSVIX VolatilityDailyNone
DEXUSEUEUR/USD ExchangeDailyunits: "pch"

Error Handling

Common Errors

ErrorCauseSolution
Invalid series IDSeries doesn’t existUse fred_search to find correct ID
No data in rangeDate range has no dataCheck series start/end dates
Invalid transformationTransform not applicableSome transforms need positive values
Frequency conversion errorCan’t convert to requested frequencyCheck if conversion makes sense

Validation Rules

Important constraints:
  • Dates must be in YYYY-MM-DD format
  • observation_start must be ≤ observation_end
  • Some transformations require positive values
  • Not all frequency conversions are valid

Best Practices

1

Know Your Data

Check series metadata (frequency, units, seasonal adjustment) before retrieval
2

Use Appropriate Transforms

Match transformation to analysis needs (growth rates for trends, logs for regression)
3

Consider Frequency

Align data frequencies when comparing multiple series
4

Handle Missing Data

Some series have gaps; check for null values in observations
5

Plan Queries Carefully

Think through data needs to minimize redundant requests