Tag: Presidential Results by CD

NY-20: Traditionally Red District Turned Blue in 2008

SSP’s Presidential Results by CD project continues to chip away at the outstanding districts left up on our big board, and I’m pleased to announce that today, thanks to the tireless efforts of SSP hero jeffmd and the lawyerly phone charm of DavidNYC, we now have complete data for New York’s newly-open 20th District.

Check it out:

Votes cast: 330,992

Obama: 167,827 (50.7%)

McCain: 157,879 (47.7%)

A traditionally GOP district, Bush carried the 20th by a 54-46 margin in 2004, and also smacked Al Gore by a 51-44 spread four years earlier.

That’s one more district that we can take down from our big board, but we still have plenty more to go. If you enjoy the work that this project has produced, please consider lending a hand by calling county offices to inquire about obtaining precinct data. We can do this thing, but we need more people to participate in lightening the load. More details are available here.

Crowdsourcing Pres-by-CD: 100 Counties for the Last 100 Districts

Thanks to the heroic efforts of this community, we were able to post a third wave of presidential results by Congressional district yesterday. And as you can see from our perma-post, we now have numbers for an impressive 332 districts. That leaves us with just over 100 districts to go, and as you’d expect, these are some of the thorniest.

The real problem is access to data. Most of the more recently-posted numbers have been drawn from precinct-level data. This sort of information is usually only available at the county level, rather than from Secretaries of State. Many counties make this data easily accessible on the web (some in more usable forms than others), but some don’t offer it online at all – and those are the counties we need to tackle. Some offer it, but charge for it. And some don’t even appear to have websites.

The bottom line is that there are about 100 counties whose precinct-level data we need in order to finish this project – and we’re only gonna solve this problem by throwing as much manpower (or dare I say, people power?) at it as possible. To that end, we’ve created another crowdsourcing spreadsheet for folks to start tackling this.

The first order of business is finding out contact information for the county Boards of Election. Many won’t have email addresses, and even for those that do, emails may go unanswered. So that means we’re going to have to start making phone calls. I can’t stress this enough: Please be super-polite when making these calls. These are hardworking folks who ensure our elections are run properly and probably don’t do this for much money.

Anyhow, if you do call up a county BoE and request the data, please put the date of your request & your name (username is fine) in column E. This will help us avoid inundating the BoEs with multiple requests. Some might be able to email you the data, in which case you can just directly upload it. (For spreadsheets, please upload them to Google Docs. For PDFs, please use Scribd – PDFs on Google Docs can’t be shared. Spreadsheets which exceed Google’s 1MB limit can also be uploaded to Scribd.) When you do, please put the URL in the right-most column.

Some counties might insist on mailing you a disk. It’s even possible that some will only want to send you a hard copy. If this turns out to be the case and you don’t have access to a scanner, please make a note on the spreadsheet so that someone else who does have a scanner can make the request instead.

Finally, some (maybe a lot) of these counties will try to charge us for the data. I think that’s a load of bollocks, seeing as the information has already been gathered (and paid for with tax dollars) – obviously the cost of distributing it is zero. But this is something we just have to live with. Anyhow, if you do encounter a county which charges a fee, PLEASE DO NOT ORDER THE DATA AND PAY FOR IT YOURSELF. I’d hate for us to make duplicate orders and wind up wasting money. Please just make a note of the cost in column F and we’ll revisit this soon in a co-ordinated fashion.

A complete list of counties we need (plus a few cities and towns) is below the fold, and of course in our crowdsourcing spreadsheet. Oh, and please share your tips/experiences in comments. Let’s get to work!










































































































































































































































































































































State County/City State County/City State County/City
Alabama Clarke Massachusetts Fall River town Oklahoma Canadian
Coosa Hanson town Creek
Jefferson Michigan Wayne Oklahoma
Morgan Missouri St. Louis City Rogers
Pickens Cass Oregon Josephine
St. Clair Polk Pennsylvania Butler
Tuscaloosa St. Charles Clearfield
California Fresno Taney Cumberland
Madera New Jersey Burlington Lycoming
San Joaquin Camden Mifflin
Santa Clara Essex Montgomery
Ventura Gloucester Perry
Colorado Adams Mercer Venango
Arapahoe Middlesex Warren
Otero Monmouth Texas Archer
Park Ocean Burleson
Weld Passaic Cameron
Florida Alachua Sussex Cass
Illinois Adams Union Cooke
Christian New York Broome Limestone
DeKalb Erie Nolan
Edwards Fulton Robertson
Fayette Monroe San Patricio
Gallatin Nassau Sutton
Greene New York City Trinity
Henry Oneida Utah Juab
Jersey Ontario Salt Lake
Lawrence Orleans
Livingston Otsego
Madison Rensselaer
Pike Suffolk
Saline Tioga
Shelby Ohio Ashland
Wabash Belmont
Woodford Mahoning
Indiana Allen Medina
Dearborn Portage
Elkhart Scioto
Fountain Trumbull
Shelby Wyandot

Crowdsourcing Pres-by-CD: Third Wave of Results

The elves were busy while I was taking Christmas off, and now that I’ve picked the crowdsourcing project back up, we’ve made another big jump, taking us to the point of having presidential election results for 3/4s of all congressional districts.

Results from the first wave are here, and results from the second wave are here. If you want to see all results in one place, they’re permalinked here. Also, please check out our master database; although we’ve made a lot of headway, there’s still plenty to do if you have access to precinct-level data (however, the remaining states are the ones that tend to be most coy about releasing precinct-level data, so those remaining districts may never see daylight until Polidata somehow solves those enigmas).

District Obama # McCain # Other # 2008 % 2004 % 2000 %
CA-01 199,835 96,530 8,264 65.6/31.7 60/38 52/39
CA-02 125,291 161,636 7,041 42.6/55.0 37/62 33/61
CA-03 165,617 164,025 6,440 49.3/48.8 41/58 41/55
CA-04 167,604 206,385 8,368 43.8/54.0 37/61 36/59
CA-05 165,776 67,625 4,709 69.6/28.4 61/38 60/35
CA-06 253,087 73,345 6,802 76.0/22.0 70/28 62/30
CA-07 179,037 66,272 5,450 71.4/26.4 67/32 66/31
CA-08 266,210 38,665 7,519 85.2/12.4 85/14 77/15
CA-09 260,662 29,186 5,919 88.1/9.9 86/13 79/13
CA-10 204,138 104,624 6,972 64.7/33.1 59/40 55/41
CA-12 214,850 69,029 5,213 74.3/23.9 72/27 67/29
CA-13 175,838 56,299 4,270 74.4/23.8 71/28 67/30
CA-17 171,180 61,163 4,932 72.1/25.8 66/33 60/33
CA-22 110,910 172,792 5,879 38.3/59.7 31/68 33/64
CA-25 134,222 131,201 6,010 49.5/48.3 40/59 42/56
CA-26 149,249 137,329 5,885 51.0/47.0 44/55 44/53
CA-27 157,100 75,286 5,219 66.1/31.7 59/39 60/36
CA-28 147,958 42,815 3,492 76.2/22.0 71/28 73/24
CA-29 159,947 71,860 4,840 67.6/30.4 61/37 58/38
CA-30 242,022 95,869 5,710 70.4/27.9 66/33 68/28
CA-31 113,941 25,441 3,280 79.9/18.3 77/22 77/19
CA-32 119,726 52,356 3,557 68.2/29.8 62/37 67/31
CA-33 205,470 27,672 3,539 86.8/11.7 83/16 83/14
CA-34 106,695 33,056 3,023 74.7/23.2 69/30 72/26
CA-35 165,761 27,789 2,923 84.4/14.1 79/20 82/17
CA-36 176,924 92,105 5,754 64.4/33.5 59/40 57/39
CA-37 157,219 36,940 3,388 79.6/18.7 74/25 76/22
CA-38 130,092 48,599 3,846 71.3/26.6 65/34 70/28
CA-39 128,579 63,680 4,117 65.5/32.4 59/40 62/36
CA-40 114,025 125,066 5,456 46.6/51.1 39/60 41/56
CA-41 119,255 147,982 5,890 43.7/54.2 37/62 41/56
CA-42 128,474 152,256 5,529 44.9/53.2 37/62 39/59
CA-43 112,020 49,594 3,216 68.0/30.1 58/41 64/34
CA-44 133,535 131,003 5,169 49.5/48.6 40/59 44/53
CA-45 142,305 129,664 4,251 51.5/46.9 43/56 47/51
CA-46 145,393 150,937 6,921 47.9/49.8 42/57 42/55
CA-47 77,144 48,461 2,672 60.1/37.8 49/50 56/42
CA-48 163,063 160,584 7,091 49.3/48.6 40/58 40/58
CA-49 117,283 137,739 4,805 45.1/53.0 36/63 39/59
CA-50 172,962 158,845 5,616 51.3/47.1 44/55 43/54
CA-51 135,960 76,438 3,021 63.1/35.5 53/46 57/41
CA-52 135,848 161,332 4,827 45.0/53.4 38/61 40/57
CA-53 177,863 77,930 5,101 68.2/29.9 61/38 58/38
GA-01 96,818 167,122 2,149 36.4/62.8 34/66 38/62
GA-02 130,109 111,559 1,322 53.6/45.9 50/50 52/48
GA-03 129,895 235,263 3,178 35.3/63.9 29/70 32/68
GA-04 208,874 54,868 1,974 78.6/20.7 71/28 70/30
GA-05 249,927 63,053 2,734 79.1/20.0 74/26 73/27
GA-06 133,716 227,701 4,301 36.6/62.3 29/70 32/68
GA-07 140,009 212,721 3,710 39.3/59.7 30/70 31/69
GA-08 123,877 162,376 1,978 43.0/56.3 39/61 42/58
GA-09 70,366 225,929 3,611 23.5/75.3 23/77 29/71
GA-10 113,915 183,441 2,773 38.0/61.1 35/65 37/63
GA-11 103,112 204,275 3,987 33.1/65.6 29/71 35/66
GA-12 143,624 120,150 1,733 54.1/45.3 49/50 52/48
GA-13 200,567 80,327 2,180 70.9/28.4 60/40 57/43
IN-01 184,871 111,895 2,582 61.8/37.4 55/44 56/42
IN-04 141,946 184,389 3,509 43.0/55.9 30/69 32/66
IN-05 143,447 210,103 3,172 40.2/58.9 28/71 30/69
IN-07 191,381 76,530 2,056 70.9/28.4 58/42 56/43
IN-09 149,587 151,543 3,783 49.1/49.7 40/59 42/56
KS-01 79,638 184,501 4,813 29.6/68.6 26/72 29/67
KS-02 133,759 170,279 6,003 43.1/54.9 39/59 41/54
KS-03 186,196 177,019 5,148 50.6/48.1 44/55 42/53
KS-04 113,418 166,705 5,440 39.7/58.4 34/64 37/59
NY-18 184,182 112,214 2,294 61.7/37.6 58/42 58/39
NY-19 160,645 153,424 3,100 50.7/48.4 45/54 47/49
OH-01 164,824 133,576 3,147 54.7/44.3 49/51 46/51
OH-02 126,796 190,109 4,297 39.5/59.2 36/64 34/63
OH-03 155,610 167,897 4,830 47.4/51.1 46/54 45/52
OH-04 112,543 176,973 5,882 38.1/59.9 34/65 35/62
OH-05 136,666 159,433 5,981 45.2/52.8 39/61 37/59
OH-07 142,154 171,568 5,194 44.6/53.8 43/57 42/56
OH-08 118,915 189,578 5,499 37.9/60.4 35/64 36/61
OH-09 194,682 113,095 4,925 62.3/36.2 58/42 55/41
OH-10 174,575 115,005 5,489 59.2/39.0 58/41 53/42
OH-11 245,149 41,606 2,463 84.8/14.4 81/18 79/18
OH-12 213,177 183,233 5,172 53.1/45.6 49/51 46/52
OH-15 167,441 139,425 5,486 53.6/44.6 50/50 44/52
OH-18 112,545 128,735 6,122 45.5/52.0 43/57 41/55
OR-02 155,301 192,627 10,632 43.3/53.7 38/61 35/60
OR-04 200,841 161,645 11,572 53.7/43.2 49/49 44/49
PA-01 246,006 32,174 1,310 88.0/11.5 84/15 84/15
PA-02 270,695 26,521 1,264 90.7/8.9 87/12 87/12
PA-08 186,372 157,544 3,814 53.6/45.3 51/48 51/46
PA-11 164,451 121,559 3,229 56.9/42.0 53/47 54/43
PA-12 131,544 132,497 3,892 49.1/49.5 51/49 55/44
PA-14 209,771 86,927 2,886 70.0/29.0 69/30 70/28
PA-15 162,471 122,163 3,804 56.3/42.4 50/50 49/48
PA-16 150,341 161,844 2,719 47.7/51.4 38/61 36/62
PA-17 144,897 152,406 3,737 48.1/50.6 42/58 41/56
PA-18 149,824 186,297 3,215 44.2/54.9 46/54 47/52
TN-01 75,052 181,912 3,829 28.8/69.8 31/68 38/61
TN-02 104,287 195,540 4,600 34.3/64.2 35/64 39/59
TN-03 103,817 174,248 3,600 36.9/61.9 38/61 41/57
TN-04 92,924 173,841 4,917 34.2/64.0 41/58 49/50
TN-05 166,293 128,615 3,636 55.7/43.1 52/48 57/42
TN-06 112,064 189,729 4,721 36.6/61.9 40/60 49/49
TN-07 123,063 230,779 3,397 34.4/64.6 33/66 40/59
TN-08 110,390 144,957 3,255 42.7/56.1 47/53 51/48
TN-09 196,824 56,130 1,432 77.4/22.1 70/30 63/36
TX-02 105,736 159,141 1,805 39.7/59.7 37/63 37/63
TX-03 124,027 171,119 3,283 41.6/57.3 33/67 30/70
TX-04 90,191 206,621 2,992 30.1/68.9 30/70 34/66
TX-05 90,135 158,356 2,128 36.0/63.2 33/67 34/66
TX-06 112,025 167,778 2,243 39.7/59.5 34/66 34/66
TX-07 121,472 173,162 2,673 40.9/58.2 36/64 31/69
TX-08 73,428 213,450 2,464 25.4/73.8 28/72 31/69
TX-09 137,619 40,240 850 77.0/22.5 70/30 69/31
TX-10 149,112 183,908 3,987 44.3/54.6 38/62 34/67
TX-11 56,939 182,074 2,332 23.6/75.4 22/78 25/75
TX-12 99,083 171,408 2,539 36.3/62.8 33/67 36/64
TX-13 52,691 175,174 2,087 22.9/76.2 22/78 25/75
TX-14 88,532 177,370 2,230 33.0/66.2 33/67 36/64
TX-16 118,178 60,279 1,773 65.6/33.5 57/44 59/41
TX-17 78,756 166,649 2,351 31.8/67.3 30/70 32/68
TX-18 150,973 43,292 1,104 77.3/22.2 72/28 72/28
TX-19 64,541 168,789 1,912 27.4/71.8 23/77 25/75
TX-20 115,470 64,724 2,163 63.3/35.5 55/45 58/42
TX-21 149,261 214,569 4,299 40.6/58.3 34/66 31/69
TX-22 129,414 183,172 2,454 41.1/58.1 36/64 33/67
TX-23 124,568 117,704 2,348 50.9/48.1 43/57 47/54
TX-24 124,128 153,758 2,688 44.2/54.8 35/65 32/68
TX-25 176,016 118,183 4,805 58.9/39.5 54/46 47/53
TX-26 135,285 185,468 2,746 41.8/57.3 35/65 38/62
TX-28 103,037 80,192 1,251 55.9/43.5 46/54 50/50
TX-29 66,808 40,884 815 61.6/37.7 56/44 57/43
TX-30 170,826 37,465 1,306 81.5/17.9 75/25 74/26
TX-32 96,203 110,397 2,509 46.0/52.8 40/60 36/64

A few words about some of the states. Many of you have already seen the California numbers, which californianintexas published in her excellent diary; for those of you who haven’t, here they are on the front page again. There are unfortunately some California districts missing; a number of large counties (Santa Clara, San Joaquin, Ventura, and Fresno especially) haven’t provided precinct-by-precinct data, so districts incorporating parts of those counties can’t be completed.

The missing precinct-level data problem explains missing districts in certain other states, too. (In some cases, there was missing data for smaller counties, but I made a judgment call that the counties in question were small enough that they wouldn’t affect the overall percentage much, so they’re included.) In Indiana, we’re still missing data for Allen and Elkhart Counties, so that rules out IN-02, IN-03, and IN-06. (I already did the 8th in the first wave.) The partial totals for the left-out districts are still available in the Indiana database (the same is true for OH, PA, and TX as well), if you click the link. They may well be very close to the actual percentages, but there’s just no way of knowing.

In Ohio, large counties we’re missing include Mahoning, Trumbull, and Medina, so we’re short OH-06, OH-13, OH-14, OH-16, and OH-17.  Pennsylvania is missing Montgomery, Butler, and Cumberland Counties among others, so there we’re also missing the PA-03, PA-04, PA-05, PA-06, PA-07, PA-09, PA-10, PA-13, and PA-19. (MontCo also occupies a tiny bit of PA-02, PA-08, and PA-15, but it’s such a small percentage of those districts I decided to let it slide.)

In Texas, Cameron County is missing, so that leaves out TX-15 and TX-27. (I also did the 1st and 31st in the first wave.) Finally, there’s the matter of New York, where only a few counties bother to report by precinct. Luckily, two of them are Westchester and Rockland, so at least we can do NY-18 and NY-19 there.

There was also one missing county in Oregon, which kept me from including OR-02 and OR-04 in the first wave. I found enough information about Josephine County to decide how to allocate its votes (66.8% of the county’s voters voted for a candidate in the OR-02 congressional race, while 33.1% voted in OR-04, so I just applied those percentages to the presidential race).

In Georgia, as with many of the other southern states, early votes aren’t broken down, so what jeffmd did, as before, was to use both ‘hard’ and ‘soft’ totals, where soft totals included early votes allocated proportionately. I’m including the soft totals (otherwise, we wouldn’t have even won GA-02 and GA-12, where victory clearly depended heavily on black turnout).

So what are some of the highlights in this data set? Check out some of the traditionally Republican districts in California (where in many, not coincidentally, we came very close to surprising long-term incumbents) like CA-03, CA-26, CA-44, and even GOP strongholds like CA-25 and CA-48: all won by Obama.

Some of the biggest gains were in Indiana, especially in the Indianapolis area, where both the city itself (IN-07) and its right-wing suburbs (IN-05) zoomed to the left. Amazing what you can accomplish when you actually try to contest a formerly uncontested state.

One area where the GOP might take heart is western Pennsylvania, where there’s apparently the one district in the nation that flipped from going for Kerry to going narrowly for McCain: John Murtha’s PA-12. Also, the Philly burbs didn’t move as much as one might expect (the needle barely budged in PA-08 in Bucks County); where the biggest progress occurred in Pennsylvania was out in places like Lancaster and Harrisburg (see PA-16 and PA-17).

Texas is a very complicated tapestry: in many rural parts of the state, there was no real improvement from 2004, despite the loss of the favorite son effect. For example, expect TX-13 to replace UT-03 as the district with the worst PVI once they recalculate. And look at TX-08, where both growing right-wing exurbs and declining Dem fortunes in the Beaumont area were a double-whammy. Contrast that, though, with not just hugely improved percentages in the minority districts, but also a lot of progress in the suburban districts that we’ve discussed a lot recently where the minority growth is accelerating: TX-10, TX-22 (where the growth wasn’t enough to save Nick Lampson, sadly), TX-32, and especially TX-24 in the area around DFW airport.

And, as always, if more results trickle into the master database, I’ll be sure and post them to the front page. So keep on number-crunching!

Crowdsourcing Pres-by-CD: Second Wave of Results

Last week we released our first wave of results, for over 100 congressional districts. Today, as promised, here’s our second wave, with the results for another 95 districts.

Despite the huge avalanche of data, we’re still only halfway done. Please take a look at our master database to see what states remain. Even if you don’t have time to tabulate data yourself but if you’ve sniffed out some precinct-level data sources anywhere, please let us know in the database! We need you, to put the “crowd” in “crowdsourcing.” (A permalink to all our results so far is available here.)

District Obama # McCain # Other # 2008 % 2004 % 2000 %
AZ-01 127,790 157,160 3,848 44.3/54.4 46/54 46/51
AZ-02 138,275 220,667 4,279 38.1/60.8 38/61 41/57
AZ-03 121,996 162,724 3,422 42.3/56.5 41/58 43/55
AZ-04 86,815 43,610 1,651 65.7/33.0 62/38 63/35
AZ-05 140,287 153,736 3,362 47.2/51.7 45./54 43/54
AZ-06 135,178 220,718 4,068 37.6/61.3 35/64 37/61
AZ-07 123,202 89,725 2,491 57.2/41.7 57/43 58/38
AZ-08 161,164 181,771 4,141 46.4/52.4 46/53 46/50
FL-01 112,291 232,449 3,638 32.2/66.7 28/72 31/69
FL-02 161,822 196,555 3,715 44.7/54.3 46/54 47/53
FL-03 144,167 52,056 1,213 73.0/26.4 65/35 65/35
FL-04 141,930 231,915 3,541 37.6/61.5 31/69 34/66
FL-05 191,959 249,328 5,029 43.0/55.9 41/58 46/54
FL-06 117,280 184,864 3,089 38.4/60.6 39/61 42/58
FL-07 116,797 158,437 2,868 42.0/57.0 43/57 46/54
FL-08 187,295 167,127 2,714 52.4/46.8 45/55 46/54
FL-09 169,897 190,344 4,596 46.6/52.2 43/57 46/54
FL-10 164,148 150,962 4,895 51.3/47.1 49/51 51/49
FL-11 174,314 88,357 2,642 65.7/33.3 58/41 61/39
FL-12 115,180 123,958 2,424 47.7/51.3 42/58 45/55
FL-13 175,991 196,908 3,732 46.7/52.3 44/56 46/55
FL-14 167,015 224,405 3,084 42.3/56.9 38/62 39/61
FL-15 137,627 152,415 3,352 46.9/52.0 43/57 46/54
FL-16 174,255 191,423 3,821 47.2/51.8 46/54 47/53
FL-17 209,839 29,758 899 87.3/12.4 83/17 85/15
FL-18 128,124 122,428 1,774 50.8/48.5 46/54 43/57
FL-19 223,009 115,655 2,249 65.4/33.9 66/34 73/27
FL-20 186,912 106,344 2,240 63.3/36.0 64/36 69/31
FL-21 122,024 127,402 1,232 48.7/50.8 43/57 42/58
FL-22 175,731 162,012 2,638 51.6/47.6 52/48 52/48
FL-23 194,022 39,159 1,141 82.8/16.7 76/24 80/20
FL-24 116,527 127,386 2,562 47.3/51.7 45/55 47/53
FL-25 126,010 128,349 1,359 49.3/50.2 44/56 45/55
HI-01 152,320 60,979 4,129 70.1/28.1 53/47 55/39
HI-02 172,881 59,450 5,278 72.8/25.0 56/44 56/36
IL-01 248,990 37,176 1,587 86.5/12.9 83/17 84/16
IL-02 260,869 28,676 1,347 89.7/9.9 84/16 83/17
IL-03 154,999 85,502 3,203 63.6/35.1 59/41 58/40
IL-04 119,227 18,453 1,866 85.4/13.2 79/21 79/20
IL-05 178,170 62,906 3,383 72.9/25.7 67/33 66/34
IL-06 156,903 119,998 3,737 55.9/42.8 47/53 44/53
IL-07 255,470 33,662 1,935 87.8/11.6 83/17 83/16
IL-08 140,593 104,544 3,161 56.6/42.1 44/56 42/56
IL-09 188,822 68,989 3,202 72.3/26.4 68/32 67/31
IL-10 178,561 111,755 2,801 60.9/38.1 53/47 51/47
IL-11 163,664 137,334 4,640 53.6/44.9 46/53 48/50
IL-12 140,346 114,112 4,086 54.3/44.1 52/48 54/43
IL-13 188,155 154,788 4,148 54.2/44.6 45/55 42/55
IL-14 145,613 118,327 3,559 54.4/44.2 44/55 43/54
IL-15 123,074 124,717 4,472 48.8/49.4 41/59 43/54
IL-16 114,337 96,108 3,622 53.4/44.9 44/55 43/54
IL-17 113,913 79,311 2,918 58.1/40.4 51/48 54/44
IL-18 139,085 136,394 4,690 49.6/48.7 42/58 44/54
IL-19 69,939 93,635 2,941 42.0/56.2 39/61 41/56
MD-01 142,667 208,743 6,839 39.8/58.3 36/62 40/57
MD-02 164,089 106,088 5,263 59.6/38.5 54/45 57/41
MD-03 176,572 118,975 5,997 58.6/39.5 54/45 55/41
MD-04 240,715 40,002 2,200 85.1/14.1 78/21 77/21
MD-05 219,437 114,607 4,287 64.9/33.9 57/42 57/41
MD-06 138,091 198,238 7,426 40.2/57.7 34/65 36/61
MD-07 214,542 54,354 3,578 78.7/20.0 73/26 73/25
MD-08 201,510 69,062 3,922 73.4/25.2 69/30 66/31
NE-01 121,411 148,179 4,303 44.3/54.1 36/63 36/59
NE-02 138,809 135,439 3,561 50.0/48.8 38/60 39/57
NE-03 73,099 169,361 4,282 29.6/68.6 24/75 25/71
NV-01 158,418 85,226 5,139 63.7/34.3 57/42 56/41
NV-02 167,812 167,900 8,417 48.8/48.8 41/57 37/57
NV-03 207,418 159,574 7,716 55.4/42.6 49/50 49/48
NC-01 177,941 105,738 1,288 62.4/37.1 57/42 57/42
NC-02 155,681 141,840 2,397 51.9/47.3 46/54 46/53
NC-03 117,178 190,093 2,456 37.8/61.4 32/68 35/64
NC-04 275,205 159,427 4,305 62.7/36.3 55/44 53/46
NC-05 126,556 203,076 4,208 37.9/60.8 33/66 33/66
NC-06 122,291 212,011 3,525 36.2/62.8 30/69 32/67
NC-07 150,071 167,888 2,747 46.8/52.4 44/56 48/52
NC-08 152,261 135,234 2,222 52.6/46.7 45/54 46/54
NC-09 174,410 212,250 3,043 44.8/54.5 36/63 36/63
NC-10 108,496 191,580 3,501 35.7/63.1 33/67 34/65
NC-11 159,772 179,061 4,746 46.5/52.1 43/57 40/58
NC-12 218,599 89,790 2,033 70.4/28.9 63/37 57/42
NC-13 204,190 140,486 3,193 58.7/40.4 52/47 49/50
SC-01 118,356 174,458 3,810 39.9/58.8 39/61 38/59
SC-02 135,452 175,052 3,284 43.2/55.8 39/60 39/58
SC-03 95,124 178,089 3,644 34.4/64.3 34/66 35/63
SC-04 118,453 188,854 5,229 37.9/60.4 34/65 33/64
SC-05 135,564 160,944 3,497 45.2/53.7 42/57 43/55
SC-06 139,438 83,696 2,278 61.9/37.1 61/39 58/40
WA-01 226,526 130,343 5,911 62.4/35.9 56/42 53/42
WA-02 202,480 151,992 7,415 56.0/42.0 51/47 48/46
WA-03 183,306 159,803 6,898 52.4/45.7 48/50 46/48
WA-04 111,423 159,904 5,127 40.3/57.8 35/63 34/62
WA-05 152,921 171,426 8,283 46.0/51.5 41/57 40/56
WA-06 182,446 128,681 6,545 57.4/40.5 53/45 52/43
WA-07 308,226 55,200 5,536 83.5/15.0 79/19 72/21
WA-08 210,998 155,900 5,779 56.6/41.8 51/48 49/47
WA-09 172,318 115,837 5,298 58.7/39.5 53/46 53/43

This round was even more fun than the previous batch, because it involves a number of states where the turnaround was huge (either because of the favorite son effect, as in Illinois, or because the Obama campaign actually decided to compete there for once, like Nevada and North Carolina). Want to see some truly staggering progress? Check out IL-08, once the core of Chicago’s deep red suburbs (and home to Rep. Phil Crane), and even the site of a 56-44 edge for Bush in 2004. This year? Obama won 57-42.

As we get into the more complicated states here (the last wave picked all the lowest hanging fruit), there are some caveats to be mindful of, which may affect the data reliability a small amount. In Florida, for instance, we’re missing precinct-level data for one county, which affects two districts (the 3rd and 6th); unfortunately, it’s a pretty big county (Alachua, home of Gainesville and Univ. of Florida). In Illinois, all districts are affected by the curse of split precincts, which don’t seem to make much of a big difference, while some of the downstate districts are affected by some missing precinct-level data from some smaller counties; because of their small size, it doesn’t seem to affect the district’s overall percentages much, though.

In North Carolina, our spreadsheet whiz there broke the totals down into ‘hard’ and ‘soft’ totals, with ‘hard’ reflecting only known numbers and ‘soft’ allocating early votes and absentees proportionately (which apparently just sit in an indistinguished lump in NC). I chose to proceed using the ‘soft’ totals, which are much larger, but a stickler might choose to focus on ‘hard’ totals instead. South Carolina also has a high number of ‘indivisibles’ in its spreadsheet, which appear to be a lot of split precincts. The high number of indivisibles appears to exert some pressure on some of the percentages in South Carolina, perhaps in SC-01, where there appears to be little leftward movement since 2004.

So, take the numbers with a grain of salt, and certainly don’t expect these numbers to be a 100% match for Polidata’s numbers, forthcoming this spring. And of course, please contribute to this project however you see fit!

2008 Presidential Results by Congressional District Permalink

We’re pleased to announce that we’ve created a perma-post for the 2008 presidential results by congressional district. (We’ve included the 2004 and 2000 results as well.) You can use this link, and you’ll also find a permalink in the “Resources” box on the right-hand sidebar of the site.

As our crowdsourcing project continues, we’ll keep adding new numbers. In fact, you should expect another round of numbers this week.

Some other site news stuff: Thank you to everyone who has taken the Blogads reader survey so far! We’ve gathered about 75 responses so far, which is terrific. We’d love to hit at least 100. This may not be a scientific study, but nonetheless, everyone on this site knows the value of a big N! So please take the survey today. Once it’s complete, I promise that we’ll share some of the results.

Presidential Results by Congressional District, 2000-2008

Click Column Headers to Sort

(all numbers use 2006 district lines)

State CD Member Party Obama McCain Kerry Bush ’04 Gore Bush ’00
AK AL Young, Don (R) 38 59 36 61 28 59
AL 1 Bonner (R) 39 61 35 64 38 60
AL 2 Roby (R) 36 63 33 67 38 61
AL 3 Rogers, Mike D. (R) 43 56 41 58 47 52
AL 4 Aderholt (R) 23 76 28 71 37 61
AL 5 Brooks (R) 38 61 39 60 44 54
AL 6 Bachus (R) 23 76 22 78 25 74
AL 7 Sewell (D) 72 27 64 35 66 33
AR 1 Crawford (R) 38 59 47 52 50 48
AR 2 Griffin (R) 44 54 48 51 48 49
AR 3 Womack (R) 34 64 36 62 37 60
AR 4 Ross, Mike (D) 39 58 48 51 49 48
AZ 1 Gosar (R) 44 54 46 54 46 51
AZ 2 Franks (R) 38 61 38 61 41 57
AZ 3 Quayle (R) 42 57 41 58 43 55
AZ 4 Pastor (D) 66 33 62 38 63 35
AZ 5 Schweikert (R) 47 52 45 54 43 54
AZ 6 Flake (R) 38 61 35 64 37 61
AZ 7 Grijalva (D) 57 42 57 43 58 38
AZ 8 Giffords (D) 46 52 46 53 46 50
CA 1 Thompson, Mike (D) 66 32 60 38 52 39
CA 2 Herger (R) 43 55 37 62 33 61
CA 3 Lungren (R) 49 49 41 58 41 55
CA 4 McClintock (R) 44 54 37 61 36 59
CA 5 Matsui (D) 70 28 61 38 60 35
CA 6 Woolsey (D) 76 22 70 28 62 30
CA 7 Miller, George (D) 72 27 67 32 66 31
CA 8 Pelosi (D) 85 12 85 14 77 15
CA 9 Lee (D) 88 10 86 13 79 13
CA 10 Garamendi (D) 65 33 59 40 55 41
CA 11 McNerney (D) 54 44 45 54 45 53
CA 12 Speier (D) 74 24 72 27 67 29
CA 13 Stark (D) 74 24 71 28 67 30
CA 14 Eshoo (D) 73 25 68 30 62 34
CA 15 Honda (D) 68 30 63 36 60 36
CA 16 Lofgren (D) 70 29 63 36 64 33
CA 17 Farr (D) 72 26 66 33 60 33
CA 18 Cardoza (D) 59 39 49 50 53 44
CA 19 Denham (R) 46 52 38 61 39 58
CA 20 Costa (D) 60 39 51 48 55 44
CA 21 Nunes (R) 42 56 34 65 37 61
CA 22 McCarthy, Kevin (R) 38 60 31 68 33 64
CA 23 Capps (D) 66 32 58 40 54 40
CA 24 Gallegly (R) 51 48 43 56 43 54
CA 25 McKeon (R) 49 48 40 59 42 56
CA 26 Dreier (R) 51 47 44 55 44 53
CA 27 Sherman (D) 66 32 59 39 60 36
CA 28 Berman (D) 76 22 71 28 73 24
CA 29 Schiff (D) 68 30 61 37 58 38
CA 30 Waxman (D) 70 28 66 33 68 28
CA 31 Becerra (D) 80 18 77 22 77 19
CA 32 Chu (D) 68 30 62 37 67 31
CA 33 Bass, Karen (D) 87 12 83 16 83 14
CA 34 Roybal-Allard (D) 75 23 69 30 72 26
CA 35 Waters (D) 84 14 79 20 82 17
CA 36 Hahn (D) 64 34 59 40 57 39
CA 37 Richardson (D) 80 19 74 25 76 22
CA 38 Napolitano (D) 71 27 65 34 70 28
CA 39 Sanchez, Linda (D) 65 32 59 40 62 36
CA 40 Royce (R) 47 51 39 60 41 56
CA 41 Lewis, Jerry (R) 44 54 37 62 41 56
CA 42 Miller, Gary (R) 45 53 37 62 39 59
CA 43 Baca (D) 68 30 58 41 64 34
CA 44 Calvert (R) 50 49 40 59 44 53
CA 45 Bono Mack (R) 52 47 43 56 47 51
CA 46 Rohrabacher (R) 48 50 42 57 42 55
CA 47 Sanchez, Loretta (D) 60 38 49 50 56 42
CA 48 Campbell (R) 49 49 40 58 40 58
CA 49 Issa (R) 45 53 36 63 39 59
CA 50 Bilbray (R) 51 47 44 55 43 54
CA 51 Filner (D) 63 35 53 46 57 41
CA 52 Hunter (R) 45 53 38 61 40 57
CA 53 Davis, Susan (D) 68 30 61 38 58 38
CO 1 DeGette (D) 74 24 68 31 61 33
CO 2 Polis (D) 64 34 58 41 52 43
CO 3 Tipton (R) 47 50 44 55 39 54
CO 4 Gardner (R) 49 50 41 58 37 57
CO 5 Lamborn (R) 40 59 33 66 31 63
CO 6 Coffman (R) 46 53 39 60 37 60
CO 7 Perlmutter (D) 59 40 51 48 50 49
CT 1 Larson (D) 66 33 60 39 62 33
CT 2 Courtney (D) 59 40 54 44 54 40
CT 3 DeLauro (D) 63 36 56 42 60 34
CT 4 Himes (D) 60 40 52 46 53 43
CT 5 Murphy, Chris (D) 56 42 49 49 52 43
DE AL Carney (D) 62 37 53 46 55 42
FL 1 Miller, Jeff (R) 32 67 28 72 31 69
FL 2 Southerland (R) 45 54 46 54 47 53
FL 3 Brown (D) 73 26 65 35 65 35
FL 4 Crenshaw (R) 38 61 31 69 34 66
FL 5 Nugent (R) 43 56 41 58 46 54
FL 6 Stearns (R) 43 56 39 61 42 58
FL 7 Mica (R) 46 53 43 57 46 54
FL 8 Webster (R) 53 47 45 55 46 54
FL 9 Bilirakis (R) 47 52 43 57 46 54
FL 10 Young, Bill (R) 51 47 49 51 51 49
FL 11 Castor (D) 66 33 58 41 61 39
FL 12 Ross, Dennis (R) 49 50 42 58 45 55
FL 13 Buchanan (R) 47 52 44 56 46 55
FL 14 Mack (R) 42 57 38 62 39 61
FL 15 Posey (R) 48 51 43 57 46 54
FL 16 Rooney (R) 47 52 46 54 47 53
FL 17 Wilson, Frederica (D) 87 12 83 17 85 15
FL 18 Ros-Lehtinen (R) 51 49 46 54 43 57
FL 19 Deutch (D) 65 34 66 34 73 27
FL 20 Wasserman Schultz (D) 63 36 64 36 69 31
FL 21 Diaz-Balart (R) 49 51 43 57 42 58
FL 22 West (R) 52 48 52 48 52 48
FL 23 Hastings, Alcee (D) 83 17 76 24 80 20
FL 24 Adams (R) 49 51 45 55 47 53
FL 25 Rivera (R) 49 50 44 56 45 55
GA 1 Kingston (R) 36 63 34 66 38 62
GA 2 Bishop, Sanford (D) 54 46 50 50 52 48
GA 3 Westmoreland (R) 35 64 29 70 33 67
GA 4 Johnson, Hank (D) 79 21 71 28 70 30
GA 5 Lewis, John (D) 79 20 74 26 73 27
GA 6 Price, Tom (R) 37 62 29 70 32 68
GA 7 Woodall (R) 39 60 30 70 31 69
GA 8 Scott, Austin (R) 43 56 39 61 42 58
GA 9 Graves, Tom (R) 24 75 23 77 29 71
GA 10 Broun (R) 38 61 35 65 37 63
GA 11 Gringrey (R) 33 66 29 71 35 66
GA 12 Barrow (D) 54 45 49 50 52 48
GA 13 Scott, David (D) 71 28 60 40 57 43
HI 1 Hanabusa (D) 70 28 53 47 55 39
HI 2 Hirono (D) 73 25 56 44 56 36
IA 1 Braley (D) 58 41 53 46 52 45
IA 2 Loebsack (D) 60 38 55 44 53 43
IA 3 Boswell (D) 54 44 50 50 49 48
IA 4 Latham (R) 53 45 48 51 48 49
IA 5 King, Steve (R) 44 54 39 60 40 57
ID 1 Labrador (R) 36 62 30 69 28 68
ID 2 Simpson (R) 36 61 30 69 28 67
IL 1 Rush (D) 87 13 83 17 84 16
IL 2 Jackson (D) 90 10 84 16 83 17
IL 3 Lipinski (D) 64 35 59 41 58 40
IL 4 Gutierrez (D) 85 13 79 21 79 20
IL 5 Quigley (D) 73 26 67 33 66 34
IL 6 Roskam (R) 56 43 47 53 44 53
IL 7 Davis, Danny (D) 88 12 83 17 83 16
IL 8 Walsh (R) 56 43 44 56 42 56
IL 9 Schakowsky (D) 72 26 68 32 67 31
IL 10 Dold (R) 61 38 53 47 51 47
IL 11 Kinzinger (R) 53 45 46 53 48 50
IL 12 Costello (D) 54 44 52 48 54 43
IL 13 Biggert (R) 54 45 45 55 42 55
IL 14 Hultgren (R) 55 44 44 55 43 54
IL 15 Johnson, Tim (R) 48 50 41 59 43 54
IL 16 Manzullo (R) 53 45 44 55 43 54
IL 17 Schilling (R) 56 42 51 48 54 44
IL 18 Schock (R) 48 50 42 58 44 54
IL 19 Shimkus (R) 44 54 39 61 41 56
IN 1 Visclosky (D) 62 37 55 44 56 42
IN 2 Donnelly (D) 54 45 43 56 45 53
IN 3 Stutzman (R) 43 56 31 68 33 66
IN 4 Rokita (R) 43 56 30 69 32 66
IN 5 Burton (R) 40 59 28 71 30 69
IN 6 Pence (R) 46 53 35 64 40 59
IN 7 Carson (D) 71 28 58 42 56 43
IN 8 Bucshon (R) 47 51 38 62 42 57
IN 9 Young, Todd (R) 49 50 40 59 42 56
KS 1 Huelskamp (R) 30 69 26 72 29 67
KS 2 Jenkins (R) 43 55 39 59 41 54
KS 3 Yoder (R) 51 48 44 55 42 53
KS 4 Pompeo (R) 40 58 34 64 37 59
KY 1 Whitfield (R) 37 62 36 63 40 58
KY 2 Guthrie (R) 38 61 34 65 37 62
KY 3 Yarmuth (D) 56 43 51 49 50 48
KY 4 Davis, Geoff (R) 38 60 36 63 37 61
KY 5 Rogers, Hal (R) 31 67 39 61 42 57
KY 6 Chandler (D) 43 55 41 58 42 56
LA 1 Scalise (R) 26 73 28 71 31 67
LA 2 Richmond (D) 74 25 75 24 76 22
LA 3 Landry (R) 37 61 41 58 45 52
LA 4 Fleming (R) 40 59 40 59 43 55
LA 5 Alexander (R) 37 62 37 62 40 57
LA 6 Cassidy (R) 41 57 40 59 43 55
LA 7 Boustany (R) 35 63 39 60 42 55
MA 1 Olver (D) 64 34 63 35 56 33
MA 2 Neal (D) 59 39 59 40 58 35
MA 3 McGovern (D) 59 39 59 40 59 35
MA 4 Frank (D) 64 35 65 33 65 29
MA 5 Tsongas (D) 59 39 57 41 57 36
MA 6 Tierney (D) 58 41 58 41 57 36
MA 7 Markey (D) 65 33 66 33 64 29
MA 8 Capuano (D) 86 14 79 19 73 15
MA 9 Lynch (D) 60 39 63 36 60 33
MA 10 Keating (D) 55 44 56 43 54 39
MD 1 Harris (R) 40 58 36 62 40 57
MD 2 Ruppersberger (D) 60 38 54 45 57 41
MD 3 Sarbanes (D) 59 39 54 45 55 41
MD 4 Edwards (D) 85 14 78 21 77 21
MD 5 Hoyer (D) 65 33 57 42 57 41
MD 6 Bartlett (R) 40 58 34 65 36 61
MD 7 Cummings (D) 79 20 73 26 73 25
MD 8 Hollen (D) 74 25 69 30 66 31
ME 1 Pingree (D) 61 38 55 43 50 43
ME 2 Michaud (D) 55 43 52 46 48 45
MI 1 Benishek (R) 50 48 46 53 45 52
MI 2 Huizenga (R) 48 51 39 60 38 59
MI 3 Amash (R) 49 49 40 59 38 60
MI 4 Camp (R) 50 48 44 55 44 54
MI 5 Kildee (D) 64 35 59 41 61 37
MI 6 Upton (R) 54 45 46 53 45 52
MI 7 Walberg (R) 52 46 45 54 46 51
MI 8 Rogers, Mike J. (R) 53 46 45 54 47 51
MI 9 Peters (D) 56 43 49 51 47 51
MI 10 Miller, Candice (R) 48 50 43 57 45 53
MI 11 McCotter (R) 54 45 47 53 47 51
MI 12 Levin (D) 65 33 61 39 61 37
MI 13 Clarke, Hansen (D) 85 15 81 19 80 19
MI 14 Conyers (D) 86 14 83 17 81 18
MI 15 Dingell (D) 66 33 62 38 60 38
MN 1 Walz (D) 51 47 47 51 45 49
MN 2 Kline (R) 48 50 45 54 44 51
MN 3 Paulson (R) 52 46 48 51 46 50
MN 4 McCollum (D) 64 34 62 37 57 37
MN 5 Ellison (D) 74 24 71 28 63 29
MN 6 Bachmann (R) 45 53 42 57 42 52
MN 7 Peterson (D) 47 50 43 55 40 54
MN 8 Cravaack (R) 53 45 53 46 49 44
MO 1 Clay (D) 80 19 75 25 72 26
MO 2 Akin (R) 44 55 40 60 39 59
MO 3 Carnahan (D) 60 39 57 43 54 43
MO 4 Hartzler (R) 38 61 35 64 40 58
MO 5 Cleaver (D) 64 35 59 40 60 37
MO 6 Graves, Sam (R) 45 54 42 57 44 53
MO 7 Long (R) 35 63 32 67 36 62
MO 8 Emerson (R) 36 62 36 64 39 59
MO 9 Luetkemeyer (R) 44 55 41 59 42 55
MS 1 Nunnelee (R) 38 62 37 62 40 59
MS 2 Thompson, Bennie (D) 66 34 59 40 57 41
MS 3 Harper (R) 38 62 34 65 35 64
MS 4 Palazzo (R) 32 68 31 68 33 65
MT AL Rehberg (R) 47 49 39 59 33 58
NC 1 Butterfield (D) 62 37 57 42 57 42
NC 2 Ellmers (R) 52 47 46 54 46 53
NC 3 Jones (R) 38 61 32 68 35 64
NC 4 Price, David (D) 63 36 55 44 53 46
NC 5 Foxx (R) 38 61 33 66 33 66
NC 6 Coble (R) 36 63 30 69 32 67
NC 7 McIntyre (D) 47 52 44 56 48 52
NC 8 Kissell (D) 53 47 45 54 46 54
NC 9 Myrick (R) 45 55 36 63 36 63
NC 10 McHenry (R) 36 63 33 67 34 65
NC 11 Shuler (D) 47 52 43 57 40 58
NC 12 Watt (D) 70 29 63 37 57 42
NC 13 Miller, Brad (D) 59 40 52 47 49 50
ND AL Berg (R) 45 53 36 63 33 61
NE 1 Fortenberry (R) 44 54 36 63 36 59
NE 2 Terry (R) 50 49 38 60 39 57
NE 3 Smith, Adrian (R) 30 69 24 75 25 71
NH 1 Guinta (R) 53 47 48 51 46 49
NH 2 Bass, Charlie (R) 56 43 52 47 48 47
NJ 1 Andrews (D) 65 34 61 39 63 34
NJ 2 LoBiondo (R) 54 45 49 50 54 43
NJ 3 Runyan (R) 52 47 49 51 54 43
NJ 4 Smith, Chris (R) 47 52 44 56 50 46
NJ 5 Garrett (R) 45 54 43 57 45 52
NJ 6 Pallone (D) 60 39 57 43 61 35
NJ 7 Lance (R) 51 48 47 53 48 49
NJ 8 Pascrell (D) 63 36 59 41 60 37
NJ 9 Rothman (D) 61 38 59 41 63 34
NJ 10 Payne (D) 87 13 82 18 83 16
NJ 11 Frelinghuysen (R) 45 54 42 58 43 54
NJ 12 Holt (D) 58 41 54 46 56 40
NJ 13 Sires (D) 75 24 69 31 72 25
NM 1 Heinrich (D) 60 40 51 48 48 47
NM 2 Pearce (R) 49 50 41 58 43 54
NM 3 Lujan (D) 61 38 54 45 52 43
NV 1 Berkley (D) 64 34 57 42 56 41
NV 2 Amodei (R) 49 49 41 57 37 57
NV 3 Heck (R) 55 43 49 50 49 48
NY 1 Bishop, Tim (D) 52 48 49 49 52 44
NY 2 Israel (D) 56 43 53 45 57 39
NY 3 King, Peter (R) 47 52 47 52 52 44
NY 4 McCarthy, Carolyn (D) 58 41 55 44 59 38
NY 5 Ackerman (D) 63 36 63 36 67 30
NY 6 Meeks (D) 89 11 84 15 87 11
NY 7 Crowley (D) 79 20 74 25 75 21
NY 8 Nadler (D) 74 26 72 27 74 18
NY 9 Turner (R) 55 44 56 44 67 30
NY 10 Towns (D) 91 9 86 13 88 8
NY 11 Clarke, Yvette (D) 91 9 86 13 83 9
NY 12 Velazquez (D) 86 13 80 19 77 15
NY 13 Grimm (R) 49 51 45 55 52 44
NY 14 Maloney (D) 78 21 74 25 70 23
NY 15 Rangel (D) 93 6 90 9 87 7
NY 16 Serrano (D) 95 5 89 10 92 5
NY 17 Engel (D) 72 28 67 33 69 27
NY 18 Lowey (D) 62 38 58 42 58 39
NY 19 Hayworth (R) 51 48 45 54 47 49
NY 20 Gibson (R) 51 48 46 54 44 51
NY 21 Tonko (D) 58 40 55 43 56 39
NY 22 Hinchey (D) 59 39 54 45 51 42
NY 23 Owens (D) 52 47 47 51 47 49
NY 24 Hannah (R) 51 48 47 53 47 48
NY 25 Buerkle (R) 56 43 50 48 51 45
NY 26 Hochul (D) 46 52 43 55 44 51
NY 27 Higgins (D) 54 44 53 45 53 41
NY 28 Slaughter (D) 69 30 63 36 60 35
NY 29 Reed (R) 48 51 42 56 43 53
OH 1 Chabot (R) 55 44 49 51 46 51
OH 2 Schmidt (R) 40 59 36 64 34 63
OH 3 Turner (R) 47 51 46 54 45 52
OH 4 Jordan (R) 38 60 34 65 35 62
OH 5 Latta (R) 45 53 39 61 37 59
OH 6 Johnson, Bill (R) 48 50 49 51 47 49
OH 7 Austria (R) 45 54 43 57 42 56
OH 8 Boehner (R) 38 60 35 64 36 61
OH 9 Kaptur (D) 62 36 58 42 55 41
OH 10 Kucinich (D) 59 39 58 41 53 42
OH 11 Fudge (D) 85 14 81 18 79 18
OH 12 Tiberi (R) 53 46 49 51 46 52
OH 13 Sutton (D) 57 42 56 44 53 44
OH 14 LaTourette (R) 49 49 47 53 44 52
OH 15 Stivers (R) 54 45 50 50 44 52
OH 16 Renacci (R) 48 50 46 54 42 53
OH 17 Ryan, Tim (D) 62 36 63 37 60 35
OH 18 Gibbs (R) 45 52 43 57 41 55
OK 1 Sullivan (R) 36 64 35 65 37 62
OK 2 Boren (D) 34 66 41 59 47 52
OK 3 Lucas (R) 27 73 28 72 34 65
OK 4 Cole (R) 34 66 33 67 38 61
OK 5 Lankford (R) 41 59 36 64 38 62
OR 1 (D) 61 36 55 44 50 44
OR 2 Walden (R) 43 54 38 61 35 60
OR 3 Blumenauer (D) 71 26 67 33 61 32
OR 4 DeFazio (D) 54 43 49 49 44 49
OR 5 Schrader (D) 54 43 49 50 47 48
PA 1 Brady, Bob (D) 88 12 84 15 84 15
PA 2 Fattah (D) 90 10 87 12 87 12
PA 3 Kelly (R) 49 49 47 53 47 51
PA 4 Altmire (D) 44 55 45 54 46 52
PA 5 Thompson, Glenn (R) 44 55 39 61 38 59
PA 6 Gerlach (R) 58 41 52 48 49 49
PA 7 Meehan (R) 56 43 53 47 51 47
PA 8 Fitzpatrick (R) 54 45 51 48 51 46
PA 9 Schuster (R) 35 63 33 67 34 64
PA 10 Marino (R) 45 54 40 60 41 56
PA 11 Barletta (R) 57 42 53 47 54 43
PA 12 Critz (D) 49 50 51 49 55 44
PA 13 Schwarz (D) 59 41 56 43 56 42
PA 14 Doyle (D) 70 29 69 30 70 28
PA 15 Dent (R) 56 43 50 50 49 48
PA 16 Pitts (R) 48 51 38 61 36 62
PA 17 Holden (D) 48 51 42 58 41 56
PA 18 Murphy, Tim (R) 44 55 46 54 47 52
PA 19 Platts (R) 43 56 36 64 36 61
RI 1 Cicilline (D) 65 33 62 36 63 31
RI 2 Langevin (D) 61 37 57 41 60 33
SC 1 Scott, Tim (R) 42 57 39 61 38 59
SC 2 Wilson, Joe (R) 45 54 39 60 39 58
SC 3 Duncan, Jeff (R) 35 64 34 66 35 63
SC 4 Gowdy (R) 38 60 34 65 33 64
SC 5 Mulvaney (R) 46 53 42 57 43 55
SC 6 Clyburn (D) 64 35 61 39 58 40
SD AL Noem (R) 45 53 38 60 38 60
TN 1 Roe (R) 29 70 31 68 38 61
TN 2 Duncan, John (R) 34 64 35 64 39 59
TN 3 Fleischmann (R) 37 62 38 61 41 57
TN 4 DesJarlais (R) 34 64 41 58 49 50
TN 5 Cooper (D) 56 43 52 48 57 42
TN 6 Black (R) 37 62 40 60 49 49
TN 7 Blackburn (R) 34 65 33 66 40 59
TN 8 Fincher (R) 43 56 47 53 51 48
TN 9 Cohen (D) 77 22 70 30 63 36
TX 1 Gohmert (R) 31 69 31 69 33 68
TX 2 Poe (R) 40 60 37 63 37 63
TX 3 Johnson, Sam (R) 42 57 33 67 30 70
TX 4 Hall (R) 30 69 30 70 34 66
TX 5 Hensarling (R) 36 63 33 67 34 66
TX 6 Barton (R) 40 60 34 66 34 66
TX 7 Culberson (R) 41 58 36 64 31 69
TX 8 Brady, Kevin (R) 26 74 28 72 31 69
TX 9 Green, Al (D) 77 23 70 30 69 31
TX 10 McCaul (R) 44 55 38 62 34 67
TX 11 Conaway (R) 24 76 22 78 25 75
TX 12 Granger (R) 36 63 33 67 36 64
TX 13 Thornberry (R) 23 77 22 78 26 74
TX 14 Paul (R) 33 66 33 67 36 64
TX 15 Hinojosa (D) 60 40 49 51 54 46
TX 16 Reyes (D) 66 34 57 44 59 41
TX 17 Flores (R) 32 67 30 70 32 68
TX 18 Jackson-Lee (D) 77 22 72 28 72 28
TX 19 Neugebauer (R) 27 72 23 77 25 75
TX 20 Gonzalez (D) 63 36 55 45 58 42
TX 21 Smith, Lamar (R) 41 58 34 66 31 69
TX 22 Olson (R) 41 58 36 64 33 67
TX 23 Canseco (R) 51 48 43 57 47 54
TX 24 Marchant (R) 44 55 35 65 32 68
TX 25 Doggett (D) 59 40 54 46 47 53
TX 26 Burgess (R) 41 58 35 65 38 62
TX 27 Farenthold (R) 53 46 45 55 50 50
TX 28 Cuellar (D) 56 44 46 54 50 50
TX 29 Green, Gene (D) 62 38 56 44 57 43
TX 30 Johnson, E.B. (D) 82 18 75 25 74 26
TX 31 Carter (R) 42 58 33 67 32 69
TX 32 Sessions (R) 46 53 40 60 36 64
UT 1 Bishop, Rob (R) 33 64 25 73 27 68
UT 2 Matheson (D) 39 57 31 66 31 67
UT 3 Chaffetz (R) 29 67 20 77 24 75
VA 1 Wittman (R) 48 51 39 60 39 58
VA 2 Rigell (R) 51 49 42 58 43 55
VA 3 Scott, Bobby (D) 76 24 66 33 66 32
VA 4 Forbes (R) 50 49 43 57 44 54
VA 5 Hurt (R) 48 51 43 56 41 55
VA 6 Goodlatte (R) 42 57 36 63 37 60
VA 7 Cantor (R) 46 53 38 61 37 61
VA 8 Moran (D) 69 30 64 35 57 38
VA 9 Griffith (R) 40 59 39 60 42 55
VA 10 Wolf (R) 53 46 44 55 41 56
VA 11 Connolly (D) 57 42 49 50 45 52
VT AL Welch (D) 68 31 59 39 51 41
WA 1 Inslee (D) 62 36 56 42 53 42
WA 2 Larsen (D) 56 42 51 47 48 46
WA 3 Herrera Beutler (R) 52 46 48 50 46 48
WA 4 Hastings, Doc (R) 40 58 35 63 34 62
WA 5 McMorris Rodgers (R) 46 52 41 57 40 56
WA 6 Dicks (D) 57 41 53 45 52 43
WA 7 McDermott (D) 84 15 79 19 72 21
WA 8 Reichert (R) 57 42 51 48 49 47
WA 9 Smith, Adam (D) 59 40 53 46 53 43
WI 1 Ryan, Paul (R) 51 48 46 54 45 51
WI 2 Baldwin (D) 69 30 62 37 58 36
WI 3 Kind (D) 58 41 51 48 49 46
WI 4 Moore (D) 75 24 70 30 66 30
WI 5 Sensenbrenner (R) 41 58 36 63 35 62
WI 6 Petri (R) 50 49 43 56 42 53
WI 7 Duffy (R) 56 43 50 49 48 47
WI 8 Ribble (R) 54 45 44 55 43 52
WV 1 McKinley (R) 42 57 42 58 43 54
WV 2 Capito (R) 44 55 42 57 44 54
WV 3 Rahall (D) 42 56 46 53 51 47
WY AL Lummis (R) 33 65 29 69 28 69

Continue reading Presidential Results by Congressional District, 2000-2008

Crowdsourcing Pres-by-CD: Florida Precinct Results

According to the Census Bureau, thirty of Florida’s 67 counties are split between multiple Congressional districts. (The remainder are all located entirely within single CDs.) Unfortunately for us, the state of Florida does not publish results by CD, which means that calculating pres-by-CD for FL requires digging down into precinct-level results.

Frustratingly, the Florida Division of elections doesn’t publish that information either. However, there is good news: Florida’s county-level election departments almost universally do. I’ve gone through all thirty split-county websites to try to track down this information. I was successful in all but two counties – let us know if you have any luck with Alachua and Jefferson. (UPDATE: Jefferson County sent me a spreadsheet in response to my email request to them, which you can find here.)

Anyhow, I’ve posted links for every set of precinct data I could find in this new spreadsheet. The linked files are in a variety of formats. Some are nicely parsed Excel or CSV files, some are clean TXT or HTML files, and some are thorny PDFs. (One non-split county, Glades, even posted a handwritten chart!) The most sophisticated sites will give you a choice of formats.

No matter how you slice it (and at the precinct level, you’re slicing it awful thin), there’s a lot of data to work with. Miami-Dade’s file, for instance, is over 2,700 pages. As Crisitunity observed, we’ve picked off most of the low-hanging fruit already, so bigger projects are what remains. But as Crisitunity also noted, with a million nerds pecking away at a million keyboards, we can accomplish just about anything we set our nerdly minds to.

So if you want to start tackling the big prize of Florida, check out the spreadsheet and have at it! And if you have any thoughts or strategies for how best to pursue this project, please share them in comments.

Crowdsourcing Pres-by-CD: First Wave of Results

Enough things have happened (such as states certifying their results) that we’re ready to roll out our first wave of results from Swing State Project’s big crowdsourcing project of compiling presidential results by congressional district. Usually, knowing presidential results by CD requires waiting for Polidata to compile this data and make it public in March… but the power of an infinite number of nerds typing on an infinite number of spreadsheets makes it possible for us to short-circuit the process. (There’s still tons of stuff left for enterprising nerds to do, especially if you have access to precinct-level data. Check our database in progress.)

Without further Apu, here’s the first wave, representing nearly one quarter of all congressional districts. Explanation of many of the technicalities follows below the chart (and a simple spreadsheet of just the 2008 numbers is available here):

District Obama # McCain # Other # 2008 % 2004 % 2000 %
AL-01 117,804
(114,847-
120,761)		 184,257
(180,524-
187,990)		 2,195
(2,167-
2,222)		 38.7/60.6 35/64 38/60
AK-AL 123,594 193,841 8,762 37.9/59.4 36/61 28/59
AR-01 95,102 145,340 7,185 38.4/58.7 47/52 50/48
AR-02 131,891 161,540 5,855 44.1/54.0 48/51 48/49
AR-03 96,485 185,055 6,894 33.5/64.2 36/62 37/60
AR-04 98,832 146,082 6,356 39.3/58.1 48/51 49/48
CO-03 160,746
(158,973-
162,519)		 169,233
(167,036-
171,429)		 5,602
(5,539-
5,664)		 47.4/50.4 44/55 39/54
CO-05 129,101
(126,976-
131,226)		 189,532
(187,084-
191,980)		 4,982
(4,863-
5,100)		 39.9/58.6 33/66 31/63
CT-01 218,367 108,315 4,365 66.0/32.7 60/39 62/33
CT-02 209,546 139,888 5,055 59.1/39.5 54/44 54/40
CT-03 201,334 116,962 3,872 62.5/36.3 56/42 60/34
CT-04 189,142 125,978 2,108 59.6/39.7 52/46 53/43
CT-05 181,902 136,898 4,048 56.3/42.4 49/49 52/43
DE-AL 255,459 152,374 4,579 61.9/37.0 53/46 55/42
ID-01 128,134 220,787 8,210 35.9/61.8 30/69 28/68
ID-02 108,693 183,022 7,387 36.3/61.2 30/69 28/67
IN-08 139,500
(137,953-
141,047)		 150,945
(148,866-
153,024)		 3,813
(3,734-
3,892)		 47.4/51.3 38/62 42/57
IA-01 175,394 122,629 4,327 58.0/40.6 53/46 52/45
IA-02 190,973 122,395 5,671 59.9/38.4 55/44 53/43
IA-03 173,932 143,771 5,785 53.8/44.4 50/50 49/48
IA-04 166,104 142,396 5,724 52.9/45.3 48/51 48/49
IA-05 122,537 151,188 4,297 44.1/54.4 39/60 40/57
KY-01 104,626 176,807 4,424 36.6/61.9 36/63 40/58
KY-02 118,700 188,955 4,473 38.0/60.5 34/65 37/62
KY-03 193,260 150,552 3,393 55.7/43.4 51/49 50/48
KY-04 118,773 189,008 5,086 38.0/60.4 36/63 37/61
KY-05 75,815 162,614 4,241 31.2/67.0 39/61 42/57
KY-06 140,811 180,526 4,444 43.2/55.4 41/58 42/56
LA-01 74,405 214,479 4,708 25.3/73.1 28/71 31/67
LA-02 130,741 43,459 1,782 74.3/24.7 75/24 76/22
LA-03 97,420 163,294 5,306 36.6/61.4 41/58 45/52
LA-04 108,084 161,853 3,134 39.6/59.3 40/59 43/55
LA-05 103,707 175,097 3,638 36.7/62.0 37/62 40/57
LA-06 130,398 180,708 4,212 41.4/57.3 40/59 43/55
LA-07 103,500 187,607 4,915 35.0/63.4 39/60 42/55
ME-01 232,145 144,604 6,885 60.5/37.7 55/43 50/43
ME-02 189,778 150,669 7,090 54.6/43.4 52/46 48/45
MA-01 198,880 102,445 n/a 66.0/34.0 63/35 56/33
MA-02 178,090 117,272 n/a 60.3/39.7 59/40 58/35
MA-05 175,871 117,654 n/a 59.9/40.1 57/41 57/36
MA-06 192,502 135,956 n/a 58.6/41.4 58/41 57/36
MA-07 189,329 97,173 n/a 66.1/33.9 66/33 64/29
MA-08 202,962 32,749 n/a 86.1/13.9 79/19 73/15
MA-09 169,042 107,281 n/a 61.2/38.8 63/36 60/33
MA-10 196,218 155,288 n/a 55.8/44.2 56/43 54/39
MI-01 166,194 160,130 6,588 49.9/48.1 46/53 45/52
MI-02 167,607 179,427 5,878 47.5/50.8 39/60 38/59
MI-03 169,283 171,255 7,344 48.7/49.2 40/59 38/60
MI-04 170,275 163,886 5,928 50.2/48.2 44/55 44/54
MI-05 207,479 113,013 5,521 63.6/34.7 59/41 61/37
MI-06 177,324 146,377 3,365 54.2/44.8 46/53 45/52
MI-07 171,535 154,244 6,524 51.6/46.4 45/54 46/51
MI-08 198,207 172,346 6,412 52.6/45.7 45/54 47/51
MI-09 202,689 155,719 2,960 56.1/43.1 49/51 47/51
MI-10 160,971 166,932 7,452 48.0/49.8 43/57 45/53
MN-01 173,880 158,964 8,383 51.0/46.9 47/51 45/49
MN-02 193,218 198,966 7,683 48.3/49.8 45/54 44/51
MN-03 200,239 175,730 6,110 52.4/46.0 48/51 46/50
MN-04 217,982 113,600 6,835 64.4/33.6 62/37 57/37
MN-05 254,764 81,749 7,076 74.1/23.8 71/28 63/29
MN-06 183,950 219,939 8,519 44.6/53.3 42/57 42/52
MN-07 154,127 162,938 8,177 47.4/50.1 43/55 40/54
MN-08 195,128 163,506 8,810 53.1/44.5 53/46 49/44
MS-01 129,939 213,478 n/a 37.8/62.2 37/62 40/59
MS-02 196,400 99,428 n/a 66.4/33.6 59/40 57/41
MS-03 131,292 216,256 n/a 37.8/62.2 34/65 35/64
MS-04 93,661 198,756 n/a 32.0/68.0 31/68 33/65
MO-08 104,252
(100,910-
107,593)		 178,358
(170,990-
185,726)		 4,729
(4,606-
4,851)		 36.3/62.1 36/64 39/59
MT-AL 231,667 242,763 16,662 47.2/49.4 39/59 33/58
NH-01 186,370 164,403 3,026 52.7/46.5 48/51 46/49
NH-02 198,456 152,131 3,225 56.1/43.0 52/47 48/47
NM-01 180,833 119,342 873 60.1/39.6 51/48 48/47
NM-02 114,928 118,063 3,298 48.6/50.0 41/58 43/54
NM-03 176,661 109,427 3,456 61.0/37.8 54/45 52/43
ND-AL 141,278 168,601 7,786 44.5/53.1 36/63 33/61
OR-01 228,817 135,975 10,108 61.0/36.3 55/44 50/44
OR-03 260,128 93,931 10,297 71.4/25.8 67/33 61/32
OR-05 192,355 154,488 9,385 54.0/43.4 49/50 47/48
RI-01 148,388 75,747 3,694 65.1/33.3 62/36 63/31
RI-02 148,159 89,642 4,110 61.3/37.1 57/41 60/33
SD-AL 170,924 203,054 7,997 44.8/53.2 38/60 38/60
TX-01 83,252
(81,507-
84,997)		 187,768
(183,628-
191,907)		 1,940
(1,901-
1,978)		 30.5/68.8 31/69 33/68
TX-31 125,321
(123,983-
126,658)		 173,294
(171,304-
175,284)		 3,563
(3,535-
3,590)		 41.5/57.3 33/67 32/69
VT-AL 219,262 98,974 6,790 67.5/30.5 59/39 51/41
VA-01 179,442 193,273 3,652 47.7/51.4 39/60 39/58
VA-02 142,257 136,725 2,991 50.5/48.5 42/58 43/55
VA-03 229,822 72,249 2,223 75.5/23.7 66/33 66/32
VA-04 178,795 173,358 3,087 50.3/48.8 43/57 44/54
VA-05 157,362 164,874 3,621 48.3/50.6 43/56 41/55
VA-06 134,212 182,573 3,869 41.9/56.9 36/63 37/60
VA-07 177,789 205,949 3,648 45.9/53.2 38/61 37/61
VA-08 234,203 100,234 3,594 69.3/29.7 64/35 57/38
VA-09 108,220 160,430 4,596 39.6/58.7 39/60 42/55
VA-10 205,964 179,337 4,025 52.9/46.1 44/55 41/56
VA-11 211,466 156,003 3,417 57.0/42.1 49/50 45/52
WV-01 103,096 141,016 4,279 41.5/56.8 42/58 43/54
WV-02 113,853 142,112 4,175 43.8/54.6 42/57 44/54
WV-03 87,178 114,933 4,011 42.3/55.8 46/53 51/47
WI-01 191,901 177,162 4,281 51.4/47.5 46/54 45/51
WI-02 286,089 123,495 5,054 69.0/29.8 62/37 58/36
WI-03 213,211 150,618 5,327 57.8/40.8 51/48 49/46
WI-04 234,468 73,447 3,108 75.4/23.6 70/30 66/30
WI-05 174,174 243,597 4,191 41.3/57.7 36/63 35/62
WI-06 181,198 176,871 4,996 49.9/48.7 43/56 42/53
WI-07 200,562 152,507 5,624 55.9/42.5 50/49 48/47
WI-08 195,608 164,696 4,711 53.6/45.1 44/55 43/52
WY-AL 82,868 164,958 6,832 32.5/64.8 29/69 28/69

The easy ones to do were the at-large states, and states where the SoS has already reported by congressional district (Connecticut, Idaho, Kentucky, Minnesota, and Virginia). Also easy were states where district lines precisely follow county lines (Arkansas, Iowa, and West Virginia).

We also have a number of excellent spreadsheets in our portfolio where people were able to locate precinct, ward, or town data. (A huge thank you to everyone who has contributed, and one more reminder that there are still many more states to do, although they get progressively harder from here on out.) These include Louisiana, Maine, Massachusetts, Michigan, Mississippi, New Hampshire, New Mexico, Oregon, Rhode Island, and Wisconsin.

You may notice that not all the districts from MA, MI, and OR are included. That’s because in each of these states, there’s one pesky jursidiction that hasn’t reported at the precinct level yet: Fall River in Massachusetts, Wayne County in Michigan, and Josephine County in Oregon. If you find this data anywhere, please let us know! (A few other minor requests for our anonymous spreadsheet wizards: if the persons who did MA and MS have “other” data, could you add those to the databases? And whoever did WI, could you provide the “Wisconsin long” form that shows precinct-level data in split counties? Thanks in advance!)

You’re probably wondering about those ones where there’s a total and then a range of numbers in parentheses. These districts (AL-01, CO-03, CO-05, IN-08, MO-08, TX-01, and TX-31) are ones where there were county splits but I felt confident proceeding even without precinct data, because there was only one split county and it represented such a small percent of the total that even if I allocated the votes within the county completely wrong it still wouldn’t affect the total percentages by more than a fraction of one percent. In these cases, I’m presenting both range values (of the maximum and minimum possible) and a point estimate (calculated by allocating half of those counties’ votes for each candidate to the district in question, and half to the other district).

As we get more states done, we’ll roll more of them out. We’re expecting California and Nebraska to report by CD soon (which will give us another 56 CDs right there), but for almost all the other states, we’re missing precinct-level data. If you like this resource and have access to useful information, but don’t have the time or stamina to spreadsheet it all, please just let us know in the comments or the master database, and I’m sure someone else will pounce on it.

Crowdsourcing Pres-by-CD, 4th Thread

Right now we’re in a bit of a holding pattern with the presidential results by CD project. Most states haven’t yet certified final vote tallies, and some haven’t even finished counting. But the good news is that we have some preliminary numbers for the following states:

Connecticut

Iowa

Kentucky

Minnesota

New Hampshire

Rhode Island

Virginia

West Virginia

You can find these by clicking on the links in the “Calculations” column (column E) in the collaborative spreadsheet.

On the flipside, we still need links to official data sources for the following states:

Alabama

Florida

Indiana

Louisiana

Mississippi

New Jersey

Oklahoma

South Carolina

Tennessee

Utah

If you know the proper links to official results for any of these states, please enter them as a TinyURL on the spreadsheet. Even if official 2008 results haven’t yet been released (and as I say, in most states they have not), links to where you expect the official data to show up at some point would be greatly appreciated.

As always, please share any thoughts about this project in comments. Also, a couple of helpful resources from the US Census Bureau:

Crowdsourcing Pres-by-CD, 3rd Thread

Just a quick update on our project to crowdsource presidential results by congressional district. The following states are all in need of links to official data sources and “plans of attack”:

Alabama

Colorado

Florida

Illinois

Indiana

Louisiana

Mississippi

New Jersey

Oklahoma

South Carolina

Tennessee

Texas

Utah

Washington

The data sources don’t have to have actual numbers available yet – in fact, since most states won’t certify their vote totals for a while yet, that is only to be expected. And as for “plan of attack,” I’m talking about how we expect to crunch the numbers – do the states publish results by CD? Do they divide up (relatively) neatly by towns or counties? Or will we have to rely on raw precinct data?

Please input any relevant links or information into this spreadsheet. Thanks!