For those who are interested: Very nice examples of (static) statistical graphics on election results can be found here: https://www.nytimes.com/interactive/2020/11/09/us/arizona-election-battleground-state-counties.html?action=click&module=Spotlight&pgtype=Homepage
Takes multidisciplinary teams and lots of hard work to produce, I would guess. Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Nov 9, 2020 at 4:46 PM Abby Spurdle <spurdl...@gmail.com> wrote: > RESENT > INITIAL EMAIL, TOO BIG > ATTACHMENTS REPLACED WITH LINKS > > I created a dataset, linked. > Had to manually copy and paste from the NY Times website. > > > head (data, 3) > STATE EQCOUNTY RMARGIN_2016 RMARGIN_2020 NVOTERS_2020 > SUB_STATEVAL_2016 > 1 Alabama Mobile 13.3 12 181783 > 0 > 2 Alabama Dallas -37.5 -38 17861 > 0 > 3 Alabama Tuscaloosa 19.3 15 89760 > 0 > > > tail (data, 3) > STATE EQCOUNTY RMARGIN_2016 RMARGIN_2020 NVOTERS_2020 > SUB_STATEVAL_2016 > 4248 Wyoming Uinta 58.5 63 9400 > 0 > 4249 Wyoming Sublette 63.0 62 4970 > 0 > 4250 Wyoming Johnson 64.3 61 4914 > 0 > > > head (data [data [,1] == "Alaska",], 3) > STATE EQCOUNTY RMARGIN_2016 RMARGIN_2020 NVOTERS_2020 SUB_STATEVAL_2016 > 68 Alaska ED 40 14.7 -24.0 82 1 > 69 Alaska ED 37 14.7 -1.7 173 1 > 70 Alaska ED 38 14.7 -0.4 249 1 > > EQCounty, is the County or Equivalent. > Several states, D.C., Alaska, Connecticut, Maine, Massachusetts, Rhode > Island and Vermont are different. > RMargin(s) are the republican percentages minus the democrate > percentages, as 2 or 3 digit numbers between 0 and 100. > The last column is 0s or 1s, with 1s for Alaska, Connecticut, Maine, > Massachusetts, Rhode Island and Vermont, where I didn't have the 2016 > margins, so the 2016 margins have been replaced with state-levels > values. > > Then I scaled the margins, based on the number of voters. > i.e. > wx2016 <- 1000 * x2016 * nv / max.nv > (Where x2016 is equal to RMARGIN_2020, and nv is equal to NVOTERS_2020). > > There may be a much better way. > > And came up the following plots (linked) and output (follows): > > ---INPUT--- > PATH = "<PATH TO FILE>" > data = read.csv (PATH, header=TRUE) > > #raw data > x2016 <- as.numeric (data$RMARGIN_2016) > x2020 <- as.numeric (data$RMARGIN_2020) > nv <- as.numeric (data$NVOTERS_2020) > subs <- as.logical (data$SUB_STATEVAL) > > #computed data > max.nv <- max (nv) > wx2016 <- 1000 * x2016 * nv / max.nv > wx2020 <- 1000 * x2020 * nv / max.nv > diffs <- wx2020 - wx2016 > > OFFSET <- 500 > p0 <- par (mfrow = c (2, 2) ) > > #plot 1 > plot (wx2016, wx2020, > main="All Votes\n(By County, or Equivalent)", > xlab="Scaled Republican Margin, 2016", ylab="Scaled Republican Margin, > 2020") > abline (h=0, v=0, lty=2) > > #plot 2 > OFFSET <- 200 > plot (wx2016, wx2020, > xlim = c (-OFFSET, OFFSET), ylim = c (-OFFSET, OFFSET), > main="All Votes\n(Zoomed In)", > xlab="Scaled Republican Margin, 2016", ylab="Scaled Republican Margin, > 2020") > abline (h=0, v=0, lty=2) > > OFFSET <- 1000 > > #plot 3 > J1 <- order (diffs, decreasing=TRUE)[1:400] > plot (wx2016 [J1], wx2020 [J1], > xlim = c (-OFFSET, OFFSET), ylim = c (-OFFSET, OFFSET), > main="400 Biggest Shifts Towards Republican", > xlab="Scaled Republican Margin, 2016", ylab="Scaled Republican Margin, > 2020") > abline (h=0, v=0, lty=2) > abline (a=0, b=1, lty=2) > > #plot 4 > J2 <- order (diffs)[1:400] > plot (wx2016 [J2], wx2020 [J2], > xlim = c (-OFFSET, OFFSET), ylim = c (-OFFSET, OFFSET), > main="400 Biggest Shifts Towards Democrat", > xlab="Scaled Republican Margin, 2016", ylab="Scaled Republican Margin, > 2020") > abline (h=0, v=0, lty=2) > abline (a=0, b=1, lty=2) > > par (p0) > > #most democrat > I = order (wx2020)[1:30] > cbind (data [I,], scaled.dem.vote = -1 * wx2020 [I]) > > #biggest move toward democrat > head (cbind (data [J2,], diffs = diffs [J2]), 30) > > ---OUTPUT--- > #most democrat > > cbind (data [I,], scaled.dem.vote = -1 * wx2020 [I]) > STATE EQCOUNTY RMARGIN_2016 RMARGIN_2020 > NVOTERS_2020 SUB_STATEVAL_2016 scaled.dem.vote > 229 California Los Angeles -49.3 -44 > 3674850 0 44000.000 > 769 Illinois Cook -53.1 -47 > 1897721 0 24271.164 > 4073 Washington King -48.8 -53 > 1188152 0 17135.953 > 3092 Pennsylvania Philadelphia -67.0 -63 > 701647 0 12028.725 > 215 California Alameda -63.5 -64 > 625710 0 10897.163 > 227 California Santa Clara -52.1 -49 > 726186 0 9682.875 > 238 California San Diego -19.7 -23 > 1546144 0 9676.942 > 2683 New York Brooklyn -62.0 -49 > 693937 0 9252.871 > 2162 Minnesota Hennepin -34.9 -43 > 753716 0 8819.350 > 2074 Michigan Wayne -37.1 -37 > 863382 0 8692.908 > 2673 New York Manhattan -76.9 -70 > 446861 0 8511.986 > 221 California San Francisco -75.2 -73 > 413642 0 8216.898 > 3495 Texas Dallas -26.1 -32 > 920772 0 8017.934 > 1741 Maryland Prince George's -79.7 -80 > 365857 0 7964.559 > 510 Florida Broward -34.9 -30 > 959418 0 7832.303 > 3057 Oregon Multnomah -56.3 -61 > 458395 0 7609.044 > 3563 Texas Travis -38.6 -45 > 605034 0 7408.882 > 565 Georgia DeKalb -62.9 -67 > 369341 0 6733.839 > 3942 Virginia Fairfax -35.8 -42 > 578931 0 6616.624 > 492 D.C. D.C. -86.4 -87 > 279152 0 6608.766 > 562 Georgia Fulton -40.9 -46 > 522050 0 6534.770 > 230 California Contra Costa -43.0 -48 > 498340 0 6509.196 > 2674 New York Queens -53.6 -39 > 597928 0 6345.617 > 257 Colorado Denver -54.8 -64 > 350606 0 6106.041 > 2677 New York Bronx -79.1 -66 > 329638 0 5920.271 > 3530 Texas Harris -12.3 -13 > 1633671 0 5779.208 > 1718 Maryland Montgomery -55.4 -57 > 369405 0 5729.781 > 2888 Ohio Cuyahoga -35.2 -34 > 605268 0 5599.987 > 2745 North Carolina Mecklenburg -29.4 -35 > 565980 0 5390.506 > 2894 Ohio Franklin -25.8 -31 > 606022 0 5112.231 > > #biggest move toward democrat > > head (cbind (data [J2,], diffs = diffs [J2]), 30) > STATE EQCOUNTY RMARGIN_2016 RMARGIN_2020 > NVOTERS_2020 SUB_STATEVAL_2016 diffs > 1751 Massachusetts Boston -26.8 -67.00 > 273133 1 -2987.8625 > 113 Arizona Maricopa 2.8 -2.00 > 2046295 0 -2672.8209 > 3531 Texas Tarrant 8.6 -0.16 > 830104 0 -1978.7776 > 2162 Minnesota Hennepin -34.9 -43.00 > 753716 0 -1661.3194 > 3564 Texas Collin 16.7 5.00 > 486917 0 -1550.2480 > 3495 Texas Dallas -26.1 -32.00 > 920772 0 -1478.3065 > 238 California San Diego -19.7 -23.00 > 1546144 0 -1388.4309 > 563 Georgia Gwinnett -5.8 -18.00 > 413166 0 -1371.6547 > 3565 Texas Denton 20.0 8.00 > 416610 0 -1360.4147 > 4073 Washington King -48.8 -53.00 > 1188152 0 -1357.9434 > 564 Georgia Cobb -2.2 -14.00 > 393340 0 -1263.0208 > 2075 Michigan Oakland -8.1 -14.00 > 778418 0 -1249.7561 > 291 Colorado Jefferson -6.9 -19.00 > 376430 0 -1239.4528 > 292 Colorado El Paso 22.3 11.00 > 375058 0 -1153.2866 > 2321 Missouri St. Louis County -16.2 -24.00 > 528107 0 -1120.9259 > 3563 Texas Travis -38.6 -45.00 > 605034 0 -1053.7077 > 277 Colorado Arapahoe -14.1 -25.00 > 346740 0 -1028.4681 > 2744 North Carolina Wake -20.2 -26.00 > 624049 0 -984.9339 > 3942 Virginia Fairfax -35.8 -42.00 > 578931 0 -976.7398 > 1116 Kansas Johnson 2.6 -8.00 > 338343 0 -975.9407 > 3562 Texas Bexar -13.4 -18.00 > 757667 0 -948.4110 > 2077 Michigan Kent 3.1 -6.00 > 359915 0 -891.2545 > 257 Colorado Denver -54.8 -64.00 > 350606 0 -877.7434 > 110 Arizona Pima -13.6 -20.00 > 501058 0 -872.6264 > 2625 New Jersey Monmouth 9.3 -1.60 > 292654 0 -868.0432 > 2745 North Carolina Mecklenburg -29.4 -35.00 > 565980 0 -862.4809 > 3567 Texas Williamson 9.7 -1.30 > 287696 0 -861.1660 > 2894 Ohio Franklin -25.8 -31.00 > 606022 0 -857.5355 > 203 California Riverside -5.4 -11.00 > 558759 0 -851.4770 > 3966 Virginia Virginia Beach 3.5 -8.00 > 253477 0 -793.2257 > > DISCLAIMER: > I can not guarantee the accuracy of this data, or any conclusions. > > NOTE: > Reiterating, several states used state-level values for 2016. > (So, the Boston value above, may be off). > > Monospaced fonts are required for reading the contents of this email. > > LINKS: > > https://sites.google.com/site/spurdlea/temp_election > > https://sites.google.com/site/spurdlea/exts/election_data.txt > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
