This data set includes votes for each of the U.S. House of Representatives Congressmen on the 16 key votes identified by the CQA. The CQA lists nine different types of votes: voted for, paired for, and announced for (these three simplified to yea), voted against, paired against, and announced against (these three simplified to nay), voted present, voted present to avoid conflict of interest, and did not vote or otherwise make a position known (these three simplified to an unknown disposition).
data(Votes)A data frame with 435 observations on the following 17 variables.
handicapped-infantsa factor with levels n and y
water-project-cost-sharinga factor with levels n and y
adoption-of-the-budget-resolutiona factor with levels n and y
physician-fee-freezea factor with levels n and y
el-salvador-aida factor with levels n and y
religious-groups-in-schoolsa factor with levels n and y
anti-satellite-test-bana factor with levels n and y
aid-to-nicaraguan-contrasa factor with levels n and y
mx-missilea factor with levels n and y
immigrationa factor with levels n and y
synfuels-corporation-cutbacka factor with levels n and y
education-spendinga factor with levels n and y
superfund-right-to-suea factor with levels n and y
crimea factor with levels n and y
duty-free-exportsa factor with levels n and y
export-administration-act-south-africaa factor with levels n and y
Classa factor with levels democrat and republican
The records are drawn from:
Congressional Quarterly Almanac, 98th Congress, 2nd session 1984, Volume XL: Congressional Quarterly Inc. Washington, D.C., 1985.
It is important to recognize that NA in this database does
not mean that the value of the attribute is unknown. It
means simply, that the value is not "yea" or "nay" (see above).
The current version of the UC Irvine Machine Learning Repository Congressional Voting Records data set is available from tools:::Rd_expr_doi("10.24432/C5C01P").
Blake, C.L. & Merz, C.J. (1998). UCI Repository of Machine Learning Databases. Irvine, CA: University of California, Department of Information and Computer Science. Formerly available from http://www.ics.uci.edu/~mlearn/MLRepository.html.
data(Votes)
summary(Votes)
## maybe str(Votes) ; plot(Votes) ...
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