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Get Economic Data Using the FRED API
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Dec 11, 2024
Learn how to use the Python FRED API to get economic data from the Federal Reserve. š Subscribe for more: https://bit.ly/3lLybeP š Follow along: https://analyzingalpha.com/fred-api-python/ 00:00 Intro 01:30 Install FRED API 01:58 Get Imports 03:11 Get FRED API Key 03:25 Connect to FRED 04:11 Use get_series method 15:05 Create Get Bars Method 20:24 Get Economic Data #fredapi #economics #algotrading #python Videos are intended strictly for information, education, and entertainment purposes. Do not base any investment decisions based upon these materials. Please read the disclaimer: https://analyzingalpha.com/disclaimer
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0:00
hello world today we're going to talk to
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fred
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actually i don't mean that fred and i
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might be dating myself we're going to
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talk to the federal reserve more
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specifically we're going to make api
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calls to the federal reserve economic
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database short for fred now this is
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probably could have been a youtube short
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it's going to be a short video but i'm
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going to use some of this data because
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there's tons of great data from the
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federal reserve and it's high quality in
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some of our economic analysis in the
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next video
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where we try to figure out what moves
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the market so i hope you're excited
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let's create some code
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let's check out the fred website
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you can get to it by going to
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fred.stlouisfed.org
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and simply you can just search for
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really any data set that you want um and
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see if it's there
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look it says
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816 000 u.s and international time
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series datas from 107 107 sources so
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obviously there's tons of data so we'll
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check out yeah the 10-year treasury
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right so we'll do 10-year
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you can see 10-year treasury minus
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2-year treasury
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market yield et cetera there's just all
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sorts of stuff i'm obviously not going
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to go through that
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gdp
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let's see um
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m3
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look at different monetary
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data sets so
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so there's all sorts of cool stuff
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so with that being said let's go ahead
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and access that data so the first thing
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we'll do
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is we'll put a heading here install
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red api so if you don't have it
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installed already make sure you've got
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your virtual environment activated and
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then simply type bang tip install red
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api i'm not going to hit enter here
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because i already have it installed and
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i don't want to you know muddy up the
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screen too much and make it as clear as
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possible but if you don't have it
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installed that's all you need to do
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the next thing we'll do is we'll import
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the various modules and packages we need
2:01
to import
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packages and modules
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and the difference between modules and
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packages modules just really one file
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packages is a set of files
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now
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we can import what we need we'll do
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import
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spread api as fa
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import pandas as pd
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okay so now
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you've got that now the next thing that
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you'll need to do is you know connect to
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fred now in order to do that you need
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your own api key in fact i'm going to go
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back here and grab my api key so from
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local settings import read as settings
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now
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basically all you need is a api key if
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you're not familiar with what i'm doing
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here i just have a dictionary file
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that has you know that it's
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a python file that is i'll give an
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example of it but
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it's simply fred equals and then api key
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is the value and then coming the key and
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then the value is the api key
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again like i said once i upload this to
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github i'll provide an example too
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all right so assuming you already have
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your fred api key which all you need to
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do is sign up with an account with that
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at that previous website super easy to
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do
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fred equals fa because we're referencing
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now the the module here and then fred
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settings
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api key where you would just put in your
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direct api key or you could have another
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file
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whichever you'd like to do
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enter
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now we've got
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an object
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that connects to the thread right
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we get a fret object all right now what
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do we want to query let's check out um
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i'm going to check out the gdp
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we can go back over here
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search for gdp
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first domestic product and you can see
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here
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here's the table name right so we can
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see the gdp is going up over time which
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makes sense
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like you've got a covet dip there
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everything was shut down but in order to
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get this time series it's super easy to
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do so we'll do gdp equals
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and we'll just print the gdp out to
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screen
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do tail that might be easier so you can
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see i was at 1946
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so it goes back a ways and it looks like
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that is
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quarterly so you could probably find um
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other data sets that are more frequent
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but just understand here's the frequency
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but that's your quarterly data set let's
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try another one
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we'll try uh currency in circulation in
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fact we'll do the weekly
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currency it's
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oops
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wrong here let's try it again
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okay so there might be an issue with
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fred at the moment let's see if we can
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get it from the api good thing is i
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already know um
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the database name i was just going to
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show you just remember basically after
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the
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name of every
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you know data set it shows you the
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um essentially the database name for for
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lookup purposes so i'll do weekly
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currency and circle circulation
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do fred dot get series
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w c u r c i r
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and see if that worked
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perfect it looks like it did we've got
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it all the way back to 1984.
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okay so if you want to merge this data
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set which i'll do now
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you can do df equals pd.merge we'll just
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say pdp
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and weekly currency and circulation will
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emerge on the index
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true
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right index
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through
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and then print that out
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do what i do here
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oh that's right i have to name them
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name equals
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and we'll also do
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ddp.name equals gdp
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now we can merge them
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and you can see now that's merged and
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you'll notice
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uh you know the weekly is now
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quarterly because we did we performed an
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inner merge
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see i told you that was going to be a
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quick one that might be my shortest
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video today regardless now you know how
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to query the federal reserve api to get
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all sorts of awesome economic data and
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we as you know we're going to use that
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economic data to potentially figure out
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what moves the market in the next video
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which is right here so if you like this
6:48
video i'd really appreciate if you hit
6:50
the thumbs up or even subscribe let's
6:52
the google algorithm know that this is a
6:54
video we're sharing with the wider
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audience so
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hope you like the video and i hope to
6:58
see you in the next one bye
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