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Daily Treasury Rates Downloader

Project description

Daily Treasury Rates Downloader

A simple command line tool for downloading or updating daily US interest rates (Par Yield Curve Rates) from the US Department of the Treasury.

Installation

To install run:

> pip install dailytreasuryrates

Usage

To create or update the file rates.csv with the latest treasury rates, run the following command:

> dailytreasuryrates rates.csv

This will look for the rates.csv file in the current folder and append any new data that is available for download on the US treasury site. You can also specify a fully qualitied path like C:\dataset\myrates.csv if you want to maintain the rates files at a different location.

A common usage for the rates-file it to load it into Python with Pandas for processing:

import pandas as pd

df = pd.read_csv('rates.csv', parse_dates=["Date"]).set_index("Date")

Output format details

The output file is a csv file.

Date,1 Mo,2 Mo,3 Mo,4 Mo,6 Mo,1 Yr,2 Yr,3 Yr,5 Yr,7 Yr,10 Yr,20 Yr,30 Yr
1990-01-02,,,7.83,,7.89,7.81,7.87,7.9,7.87,7.98,7.94,,8.0
1990-01-03,,,7.89,,7.94,7.85,7.94,7.96,7.92,8.04,7.99,,8.04
...
2023-03-06,4.75,4.79,4.93,5.02,5.22,5.05,4.89,4.61,4.27,4.16,3.98,4.14,3.92
2023-03-07,4.8,4.88,5.04,5.12,5.32,5.22,5.0,4.66,4.31,4.17,3.97,4.11,3.88
  • The first columns contains the date in yyyy-mm-dd format.
  • Dates are sorted in ascending order.
  • The first date is Jan 2nd 1990.
  • The number of tenors has grown over time. E.g. in 1990 there was no 1 Month and 2 Month tennor, but now there is. These missing values for older dates have empty string in the csv file, as can be seen in the snipped above.

Download details

Data gets downloaded from the U.S. DEPARTMENT OF THE TREASURY : Daily Treasury Par Yield Curve Rates

https://home.treasury.gov/resource-center/data-chart-center/interest-rates/TextView?type=daily_treasury_yield_curve

Project details


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dailytreasuryrates-0.1.7.tar.gz (136.5 kB view hashes)

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Built Distribution

dailytreasuryrates-0.1.7-py3-none-any.whl (137.9 kB view hashes)

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