treasurycurves 1.0.4

query and analyze US Treasury yield data

Access and chart US Treasury Curve data

Full documentation can be found at treasury-curves.readthedocs.io

Selecting and plotting data

Using the Developer API found at treasury.gov, one can find yield curves dating back to the 90's.

Access data for a particular date using curves("2022-08-08"). curves will find the nearest valid date (weekday) and returns a pandas dataframes of all curves available on that date or nearest to it. calling curves() will use the current date. Optionally specify curves(allow_missing=True) to keep years with missing data.

Alternatively, you can retrieve all data by calling download().

Once you have the data, it is possible to plot out the yield curves with plot(curves_data, start="2022-01-01", end="2022-05-03", num_years=1). Specify the number of years, or pick a start and end date to sample from, as the chart would otherwise become inundated with yield curve data.

Save your data in a spreadsheet using export(curves_data, file_extension="csv") and specify "csv" or "xlsx" to determine the file type.

Using treasurycurves from the Command Line

Install through pip:

pip install treasury-curves

Once installing, you can run the entrypoint:

treasury --help

Use the module directly:

import treasury

Working inside the repository

python treasury.py --help

usage: treasury.py [-h] [-a] [-s START] [-e END] [-d DATE] [-y YEARS] [-p] [-o OUTPUT]

treasurycurves - query and analyze US Treasury yield data

optional arguments:
  -h, --help            show this help message and exit
  -a, --allowna         Allow NaN values
  -s START, --start START
                        Year to start analysis
  -e END, --end END     Year to end analysis. If equal to start, analyze curves for the year
  -d DATE, --date DATE  Date in YYYY-MM-DD to analyze
  -y YEARS, --years YEARS
                        Num years before end to analyze
  -p, --plot            Plot yield curves
  -o OUTPUT, --output OUTPUT
                        File extension to save data (csv or xlsx), leave empty to avoid saving file