Enums

class pystlouisfed.enums.AggregationMethod(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

A key that indicates the aggregation method used for frequency aggregation.

average = 'avg'

Average (same as pystlouisfed.enums.AggregationMethod.avg)

avg = 'avg'

Average (same as pystlouisfed.enums.AggregationMethod.average)

end_of_period = 'eop'

End of Period (same as pystlouisfed.enums.AggregationMethod.eop)

eop = 'eop'

End of Period (same as pystlouisfed.enums.AggregationMethod.end_of_period)

sum = 'sum'

Sum

class pystlouisfed.enums.FilterValue(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

The value of the filter_variable attribute to filter results by.

all = 'all'

All results.

macro = 'macro'

Limits results to macroeconomic data series. In general, these are series for entire countries that are not subregions of the United States.

regional = 'regional'

Limits results to series for parts of the US; namely, series for US states, counties, and Metropolitan Statistical Areas (MSA).

class pystlouisfed.enums.FilterVariable(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

The attribute to filter results by.

frequency = 'frequency'

Filter by frequency

seasonal_adjustment = 'seasonal_adjustment'

Filter by seasonal adjustment

units = 'units'

Filter by units

class pystlouisfed.enums.Frequency(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

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, and the lowest frequency data is annual. There are 3 aggregation methods available - See AggregationMethod.

anual = 'a'

Annual

biweekly = 'bw'

Biweekly

biweekly_ending_monday = 'bwem'

Biweekly Ending Monday (same as pystlouisfed.enums.Frequency.bwem)

biweekly_ending_wednesday = 'bwew'

Biweekly Ending Wednesday (same as pystlouisfed.enums.Frequency.bwew)

bwem = 'bwem'

Biweekly Ending Monday (same as pystlouisfed.enums.Frequency.biweekly_ending_monday)

bwew = 'bwew'

Biweekly Ending Wednesday (same as pystlouisfed.enums.Frequency.biweekly_ending_wednesday)

daily = 'd'

Daily

monthly = 'm'

Monthly

querterly = 'q'

Quarterly

semiannual = 'sa'

Semiannual

weekly = 'w'

Weekly

weekly_ending_friday = 'wef'

Weekly Ending Friday (same as pystlouisfed.enums.Frequency.wef)

weekly_ending_monday = 'wem'

Weekly Ending Monday (same as pystlouisfed.enums.Frequency.wem)

weekly_ending_saturday = 'wesa'

Weekly Ending Saturday (same as pystlouisfed.enums.Frequency.wesa)

weekly_ending_sunday = 'wesu'

Weekly Ending Sunday (same as pystlouisfed.enums.Frequency.wesu)

weekly_ending_thursday = 'weth'

Weekly Ending Thursday (same as pystlouisfed.enums.Frequency.weth)

weekly_ending_tuesday = 'wetu'

Weekly Ending Tuesday (same as pystlouisfed.enums.Frequency.wetu)

weekly_ending_wednesday = 'wew'

Weekly Ending Wednesday (same as pystlouisfed.enums.Frequency.wew)

wef = 'wef'

Weekly Ending Friday (same as pystlouisfed.enums.Frequency.weekly_ending_friday)

wem = 'wem'

Weekly Ending Monday (same as pystlouisfed.enums.Frequency.weekly_ending_monday)

wesa = 'wesa'

Weekly Ending Saturday (same as pystlouisfed.enums.Frequency.weekly_ending_saturday)

wesu = 'wesu'

Weekly Ending Sunday (same as pystlouisfed.enums.Frequency.weekly_ending_sunday)

weth = 'weth'

Weekly Ending Thursday (same as pystlouisfed.enums.Frequency.weekly_ending_thursday)

wetu = 'wetu'

Weekly Ending Tuesday (same as pystlouisfed.enums.Frequency.weekly_ending_tuesday)

wew = 'wew'

Weekly Ending Wednesday (same as pystlouisfed.enums.Frequency.weekly_ending_wednesday)

class pystlouisfed.enums.OrderBy(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Order results by values of the specified attribute.

created = 'created'

Order by created

frequency = 'frequency'

Order by frequency

group_id = 'group_id'

Order by group id

group_popularity = 'group_popularity'

Order by group popularity

last_updated = 'last_updated'

Order by last updated

name = 'name'

Order by name

observation_end = 'observation_end'

Order by observation end

observation_start = 'observation_start'

Order by observation start

popularity = 'popularity'

Order by popularity

press_release = 'press_release'

Order by press release

realtime_end = 'realtime_end'

Order by realtime end

realtime_start = 'realtime_start'

Order by realtime start

release_date = 'release_date'

Order by release date

release_id = 'release_id'

Order by release id

release_name = 'release_name'

Order by release name

search_rank = 'search_rank'

Order by search rank

seasonal_adjustment = 'seasonal_adjustment'

Order by seasonal adjustment

series_count = 'series_count'

Order by series count

series_id = 'series_id'

Order by series id

source_id = 'source_id'

Order by source id

title = 'title'

Order by title

units = 'units'

Order by units

class pystlouisfed.enums.OutputType(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Output type.

all = 2

Observations by Vintage Date - All Observations

initial_release_only = 4

Observations - Initial Release Only

new_and_revised = 3

Observations by Vintage Date - New and Revised Observations Only

realtime_period = 1

Observations by Real-Time Period

class pystlouisfed.enums.RegionType(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

The region you want want to pull data for.

bea = 'bea'

Bureau of Economic Anaylis Region

censusdivision = 'censusdivision'

US Census Divisons

censusregion = 'censusregion'

US Census Regions

country = 'country'

Country

county = 'county'

USA Counties

frb = 'frb'

Federal Reserve Bank Districts

msa = 'msa'

Metropolitan Statistical Area

necta = 'necta'

New England City and Town Area

state = 'state'

State

class pystlouisfed.enums.SearchType(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Determines the type of search to perform.

full_text = 'full_text'

“full_text” searches series attributes title, units, frequency, and tags by parsing words into stems. This makes it possible for searches like “Industry” to match series containing related words such as “Industries”. Of course, you can search for multiple words like “money” and “stock”.

series_id = 'series_id'

“series_id” performs a substring search on series IDs. Searching for “ex” will find series containing “ex” anywhere in a series ID. “*” can be used to anchor searches and match 0 or more of any character. Searching for “ex*” will find series containing “ex” at the beginning of a series ID. Searching for “ex” will find series containing “ex” at the end of a series ID. It”s also possible to put an “” in the middle of a string. “m*sl” finds any series starting with “m” and ending with “sl”.

class pystlouisfed.enums.Seasonality(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

The seasonality of the series group.

not_seasonally_adjusted = 'NSA'

Not Seasonally Adjusted (same as pystlouisfed.enums.Seasonality.nsa)

nsa = 'NSA'

Not Seasonally Adjusted (same as pystlouisfed.enums.Seasonality.not_seasonally_adjusted)

sa = 'SA'

Seasonally Adjusted (same as pystlouisfed.enums.Seasonality.seasonally_adjusted)

seasonally_adjusted = 'SA'

Seasonally Adjusted (same as pystlouisfed.enums.Seasonality.sa)

smoothed_seasonally_adjusted = 'SSA'

Smoothed Seasonally Adjusted (same as pystlouisfed.enums.Seasonality.ssa)

ssa = 'SSA'

Smoothed Seasonally Adjusted (same as pystlouisfed.enums.Seasonality.smoothed_seasonally_adjusted)

class pystlouisfed.enums.ShapeType(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

The type of shape you want to pull Well-known text (WKT) data for.

bea = 'bea'

Bureau of Economic Anaylis Region

censusdivision = 'censusdivision'

US Census Divisons

censusregion = 'censusregion'

US Census Regions

country = 'country'

Country

county = 'county'

USA Counties

frb = 'frb'

Federal Reserve Bank Districts

msa = 'msa'

Metropolitan Statistical Area

necta = 'necta'

New England City and Town Area

state = 'state'

State

class pystlouisfed.enums.SortOrder(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

asc = 'asc'

Ascending

desc = 'desc'

Descending

class pystlouisfed.enums.TagGroupID(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

A tag group id to filter tags by type.

cc = 'cc'

Citation & Copyright (same as pystlouisfed.enums.TagGroupID.citation_and_copyright)

citation_and_copyright = 'cc'

Citation & Copyright (same as pystlouisfed.enums.TagGroupID.cc)

freq = 'freq'

Frequency (same as pystlouisfed.enums.TagGroupID.frequency)

frequency = 'freq'

Frequency (same as pystlouisfed.enums.TagGroupID.freq)

gen = 'gen'

General or Concept (same as pystlouisfed.enums.TagGroupID.general_or_concept)

general_or_concept = 'gen'

General or Concept (same as pystlouisfed.enums.TagGroupID.gen)

geo = 'geo'

Geography (same as pystlouisfed.enums.TagGroupID.geography)

geography = 'geo'

Geography (same as pystlouisfed.enums.TagGroupID.geo)

geography_type = 'geot'

Geography Type (same as pystlouisfed.enums.TagGroupID.geot)

geot = 'geot'

Geography Type (same as pystlouisfed.enums.TagGroupID.geography_type)

release = 'rls'

Release (same as pystlouisfed.enums.TagGroupID.rls)

rls = 'rls'

Release (same as pystlouisfed.enums.TagGroupID.release)

seas = 'seas'

Seasonal Adjustment (same as pystlouisfed.enums.TagGroupID.seasonal_adjustment)

seasonal_adjustment = 'seas'

Seasonal Adjustment (same as pystlouisfed.enums.TagGroupID.seas)

source = 'src'

Source (same as pystlouisfed.enums.TagGroupID.src)

src = 'src'

Source (same as pystlouisfed.enums.TagGroupID.source)

class pystlouisfed.enums.Unit(value, names=None, *values, module=None, qualname=None, type=None, start=1, boundary=None)

A key that indicates a data value transformation.

cca = 'cca'

Continuously Compounded Annual Rate of Change

cch = 'cch'

Continuously Compounded Rate of Change

ch1 = 'ch1'

Change from Year Ago

chg = 'chg'

Change

lin = 'lin'

Levels (No transformation)

log = 'log'

Natural Log

pc1 = 'pc1'

Percent Change from Year Ago

pca = 'pca'

Compounded Annual Rate of Change

pch = 'pch'

Percent Change