Fedtools 0.0.1

An open source library for the extraction of Federal Reserve Data.

FedTools

An open source Python library for the scraping of Federal Reserve data.

By default, all modules within FedTools use 10 threads to increase scraping speed. By default, the Output is a Pandas DataFrame, indexed by release date of the materials. Additional serialised storage methods are optional.

Installation

From Command Line:

$ python FedMinutes.py

Saves a Pickled Pandas DataFrame 'dataset.pkl', which contains all Meeting Minutes within search range, indexed by Date.

From Python:

pip install FedTools
from FedTools import MonetaryPolicyCommittee

Usage

From Command Line:

$ python FedMinutes.py

Saves a Pickled Pandas DataFrame 'dataset.pkl', which contains all Meeting Minutes within search range, indexed by Date.

From Python:

pip install FedTools
from FedTools import MonetaryPolicyCommittee
dataset = MonetaryPolicyCommittee().find_statements()

MonetaryPolicyCommittee().pickle_data("DIRECTORY")

Returns a Pandas DataFrame 'dataset', which contains all Meeting Minutes, indexed by Date and a '.pkl' file saved within "DIRECTORY".

To edit input default arguments:

monetary_policy = MonetaryPolicyCommittee(
            main_url = 'https://www.federalreserve.gov', 
            calendar_url = 'https://www.federalreserve.gov/monetarypolicy/fomccalendars.htm',
            historical_split = 2014,
            verbose = True,
            max_threads = 10)

dataset = monetary_policy.find_statements()

# serialise, save to "DIRECTORY":
monetary_policy.pickle_data("DIRECTORY")

All parameters above are optional, with a short explanation of each parameter outlined below:

Argument	Description
main_url	Federal Reserve Open Monetary Policy (FOMC) website URL. (str)
calendar_url	URL containing a list of FOMC Meeting dates. (str)
historical_split	year(s) considered as historical (check here). (int)
verbose	boolean determining printing during scraping. (bool)
thread_num	the number of threads to use for web scraping. (int)