Graph and download economic data for Market Yield on U.S. Treasury Securities at 3-Year Constant Maturity, Quoted on an Investment Basis (DGS3) from 1962-01-02 to 2025-07-10 about 3-year, maturity, Treasury, interest rate, interest, rate, and USA.

The yield on US 3 Year Note Bond Yield rose to 3.87% on July 11, 2025, marking a 0.02 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.01 points and is 0.36 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. United States 3 Year Note Yield - values, historical data, forecasts and news - updated on July of 2025.

In December 2024, the yield on a 10-year U.S. Treasury note was **** percent, forecasted to decrease to reach **** percent by August 2025. Treasury securities are debt instruments used by the government to finance the national debt. Who owns treasury notes? Because the U.S. treasury notes are generally assumed to be a risk-free investment, they are often used by large financial institutions as collateral. Because of this, billions of dollars in treasury securities are traded daily. Other countries also hold U.S. treasury securities, as do U.S. households. Investors and institutions accept the relatively low interest rate because the U.S. Treasury guarantees the investment. Looking into the future Because these notes are so commonly traded, their interest rate also serves as a signal about the market’s expectations of future growth. When markets expect the economy to grow, forecasts for treasury notes will reflect that in a higher interest rate. In fact, one harbinger of recession is an inverted yield curve, when the return on 3-month treasury bills is higher than the ten-year rate. While this does not always lead to a recession, it certainly signals pessimism from financial markets.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 5-Year Constant Maturity, Quoted on an Investment Basis (DGS5) from 1962-01-02 to 2025-06-18 about maturity, Treasury, interest rate, interest, 5-year, rate, and USA.

Interactive chart showing the daily 5 year treasury yield back to 1962. The values shown are daily data published by the Federal Reserve Board based on the average yield of a range of Treasury securities, all adjusted to the equivalent of a five-year maturity.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 20-Year Constant Maturity, Quoted on an Investment Basis, Inflation-Indexed (DFII20) from 2004-07-27 to 2025-07-10 about 20-year, TIPS, maturity, securities, Treasury, interest rate, interest, real, rate, and USA.

The yield on US 2 Year Note Bond Yield rose to 3.91% on July 11, 2025, marking a 0.03 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.01 points and is 0.55 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. US 2 Year Treasury Bond Note Yield - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 2-Year Constant Maturity, Quoted on an Investment Basis (DGS2) from 1976-06-01 to 2025-07-10 about 2-year, maturity, Treasury, interest rate, interest, rate, and USA.

Graph and download economic data for Market Yield on U.S. Treasury Securities at 7-Year Constant Maturity, Quoted on an Investment Basis (DGS7) from 1969-07-01 to 2025-07-10 about 7-year, maturity, Treasury, interest rate, interest, rate, and USA.

Graph and download economic data for 5-Year Treasury Constant Maturity Minus Federal Funds Rate (T5YFF) from 1962-01-02 to 2025-07-10 about yield curve, spread, maturity, Treasury, federal, interest rate, interest, 5-year, rate, and USA.

Graph and download economic data for 1-Year Treasury Constant Maturity Minus Federal Funds Rate (T1YFF) from 1962-01-02 to 2025-07-10 about yield curve, 1-year, spread, maturity, Treasury, federal, interest rate, interest, rate, and USA.

This dataset contains the percentage of students achieving goal in reading and mathematics on the 3rd grade Connecticut Mastery Test (CMT) for the years 2007-2013. Data are disaggregated by various subgroups including race/ethnicity, special education, free and reduced price lunch eligibility, and English language learner (ELL) status.

Context

Treasury rates

Content

https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yieldAll

import requests from bs4 import BeautifulSoup import datetime import pandas as pd import numpy as np

def risk_free(): url = r'https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yieldAll' data = requests.get(url).text soup = BeautifulSoup(data,"html.parser") time = np.array([1/12,0.25,0.5,1,2,3,5,7,10,20,30]) cols = ['m1','m3','m6','y001','y002','y003','y005','y007','y010','y020','y030'] rates_zero = np.zeros(len(time)) data = {} rw = 0 for tbl_rw in soup.find('table',{'class':'t-chart'}).find_all('tr'): rates = {} i = 0 if rw == 0: rw+=1 continue

  for td in tbl_rw.contents:
    if i > 0:
      r = td.contents[0]
      if r.find(r'N/A') > 0:
        rates[cols[i-1]] = None
      else:
        rates[cols[i-1]] = float(r)/100
    else:
      date = datetime.datetime.strptime(td.contents[0], '%m/%d/%y') 
    i+= 1

  data[date] = rates

data = pd.DataFrame.from_dict(data,orient='index')
data.index.name = 'Date'
return (data,time)

data,time = risk_free() data.to_csv('treasury_cmt.csv')

Acknowledgements

Treasury.gov, everyone who has contributed to the packages I used to download the data

Graph and download economic data for Market Yield on U.S. Treasury Securities at 1-Month Constant Maturity, Quoted on an Investment Basis (DGS1MO) from 2001-07-31 to 2025-07-10 about 1-month, bills, maturity, Treasury, interest rate, interest, rate, and USA.

Analysis of ‘Statewide CMT 3rd Grade Reading And Math: 2007-2013’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c616f29d-a84a-4182-9c68-a05f6861e8ea on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains the percentage of students achieving goal in reading and mathematics on the 3rd grade Connecticut Mastery Test (CMT) for the years 2007-2013. Data are disaggregated by various subgroups including race/ethnicity, special education, free and reduced price lunch eligibility, and English language learner (ELL) status.

--- Original source retains full ownership of the source dataset ---

Graph and download economic data for 10-Year Treasury Constant Maturity Minus Federal Funds Rate (T10YFF) from 1962-01-02 to 2025-07-10 about yield curve, spread, 10-year, maturity, Treasury, federal, interest rate, interest, rate, and USA.

Supplementary Material 1: Table S1. CMT-U27_protein ID and quantification.

The CMT solutions are obtained in “Impact of offshore seismograph network and 3-D seismic velocity structure model on centroid moment tensor analysis for offshore earthquake: Application to the Japan Trench subduction zone” by Lina Yamaya, Hisahiko Kubo, Katsuhiko Shiomi, and Shunsuke Takemura.

• Earthquakes at the Japan Trench subduction zone
• April 1, 2017 to March 31, 2024
• Mw of 5.2–7.0

Data format: Date (“YYMMDDHHMM”, JST [UTC+9]), longitude, latitude, depth, Mrr, Mtt, Mff, Mrt, Mrf, Mtf (Nm), time shift, variance reduction, Mw

"SFCMT.zip" and "FCMT.zip" files include SF-CMT and F-CMT solutions for the earthquakes and station lists.

This dataset is for a submitted manuscript.

The manuscript can be downloaded at https://essopenarchive.org/doi/full/10.22541/essoar.172192808.86300687.

For more information, please contact the creator.

The increasing scale and diversity of seismic data, and the growing role of big data in seismology, has raised interest in methods to make data exploration more accessible. This paper presents the use of knowledge graphs (KGs) for representing seismic data and metadata to improve data exploration and analysis, focusing on usability, flexibility, and extensibility. Using constraints derived from domain knowledge in seismology, we define semantic models of seismic station and event information used to construct the KGs. Our approach utilizes the capability of KGs to integrate data across many sources and diverse schema formats. We use schema-diverse, real-world seismic data to construct KGs with millions of nodes, and illustrate potential applications with three big-data examples. Our findings demonstrate the potential of KGs to enhance the efficiency and efficacy of seismological workflows in research and beyond, indicating a promising interdisciplinary future for this technology. Methods The data here consists of, and was collected from:

Station metadata, in StationXML format, acquired from IRIS DMC using the fdsnws-station webservice (https://service.iris.edu/fdsnws/station/1/). Earthquake event data, in NDK format, acquired from the Global Centroid-Moment Tensor (GCMT) catalog webservice (https://www.globalcmt.org) [1,2]. Earthquake event data, in CSV format, acquired from the USGS earthquake catalog webservice (https://doi.org/10.5066/F7MS3QZH) [3].

The format of the data is described in the README. In addition, a complete description of the StationXML, NDK, and USGS file formats can be found at https://www.fdsn.org/xml/station/, https://www.ldeo.columbia.edu/~gcmt/projects/CMT/catalog/allorder.ndk_explained, and https://earthquake.usgs.gov/data/comcat/#event-terms, respectively. Also provided are conversions from NDK and StationXML file formats into JSON format. References: [1] Dziewonski, A. M., Chou, T. A., & Woodhouse, J. H. (1981). Determination of earthquake source parameters from waveform data for studies of global and regional seismicity. Journal of Geophysical Research: Solid Earth, 86(B4), 2825-2852. [2] Ekström, G., Nettles, M., & Dziewoński, A. M. (2012). The global CMT project 2004–2010: Centroid-moment tensors for 13,017 earthquakes. Physics of the Earth and Planetary Interiors, 200, 1-9. [3] U.S. Geological Survey, Earthquake Hazards Program, 2017, Advanced National Seismic System (ANSS) Comprehensive Catalog of Earthquake Events and Products: Various, https://doi.org/10.5066/F7MS3QZH.

View a 10-year yield estimated from the average yields of a variety of Treasury securities with different maturities derived from the Treasury yield curve.