Download FRED data using the Python fredapi

The Federal Reserve Economic Data archive is a great place to find financial data. You can visit the FRED web site to search for a data series or use the Python fredapi to download data programmatically. Below is an example of the fredapi functionality and usage.

import pandas as pd
from fredapi import Fred
import datetime as dt
# set up Fred key else queries do not work
fred = Fred(api_key='yourkeygoeshere')

# Search for the ticker by description
ticker_description = 'Civilian Unemployment Rate'
ticker_info = fred.search(ticker_description)

if ticker_info is None:
    print("Did not find ticker by searching the text '{0}'. Pleave revise your search.".format(ticker_description))
else:
    ticker_id = ticker_info['id'].values[0]
    ticker_start = ticker_info['observation_start'].values[0]
    ticker_end = ticker_info['observation_end'].values[0]
    print("Ticker id = {0}, start_date = {1}, end_date = {2}".format(ticker_id, ticker_start, ticker_end))
    try:
        # query the ticker information from FRED using start and end dates
        s = fred.get_series(ticker_id, observation_start=ticker_start, observation_end=ticker_end)
        print(s.tail())
        # Save daily close file since inception
        s.to_csv("output/"+ticker_id+".csv")
        # Save quarterly file. Use 'QS' frequency for beginning of month data
        pd.Series(s, pd.date_range('2013-01-05', dt.datetime.now(), freq='QS')).to_csv("output/"+ticker_id+"_quarterly.csv")
    except: 
        print("Problem downloading '{0}' series".format(ticker_id))

Ticker id = UNRATE, start_date = 1948-01-01T00:00:00.000000000Z, end_date = 2017-10-31T17:00:00.000000000-0700
2017-07-01    4.3
2017-08-01    4.4
2017-09-01    4.2
2017-10-01    4.1
2017-11-01    4.1
dtype: float64

import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

s.plot(figsize=(10,5), grid=True, title='{0}% ({1})'.format(ticker_description, ticker_id))

<matplotlib.axes._subplots.AxesSubplot at 0x1092dfe48>