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.

51 thoughts on “Crowdsourcing Pres-by-CD: First Wave of Results”

  5. to have such clear easy accessible numbers. One nitpick though. CQ says Kerry got 82% in MA-08 in 2004. Even the MN numbers were okay. Michigan is what has the truly amazing numbers. Its also kind of funny that the Republican legislature drew PA-17 for Tim Holden so that it would be unwinnable for a Democrat, but not only did Holden upset Gekas, the ten term incumbent, it looks like Obama won the district, having carried Dauphin and Berks county.

  6. great. Look at the gains Obama made in the historically always heavily Republican Grand Rapids area. Wisconsin just looked great though. Look how far Green Bay has moved the past few years. Look forward to a big Senate contest in 2012 between Representative Ron Kind and Paul Ryan, though Kind has the clear early advantage due to the political layout of the state, (isn’t that a great name for a politician though, Kind).  

  7. NM-01 and NM-02 are particularly good, Obama greatly outperformed both Gore and Kerry in the Albuquerque area and in the southern district, makes me feel a lot more comfortable about both Teague and Heinrich.

  8. I’ll get around to them at some point, perhaps when I’m visiting my family for Christmas.  The Massachusetts data is also missing data for Fall River and Hanson.  Hanson is small, though conservative, but Fall River is reasonably large and strongly Democratic.  If no precinct level data can be found we may want to estimate. Fall River effects the 3rd and 4th districts, Hanson the 9th and 10th.

  9. I’ve been on the prowl for this for a long, long time! Fascinating numbers.

    We really need to field bigtime challanges to Rob Whitman and Randy Forbes. It’s pretty amazing that a relatively liberal Democrat like Rick Boucher represents Virginia’s most Republican district.  

  10. I was looking at numbers from my region, and the notable examples I see are KY and VA.  All this talk about places not voting for Obama because he was black and there was hardly any change in VA-09 (my roots).  He actually had a slight improvement over Kerry.  The only place in either state where he plummeted was KY-05, which is somewhat of a disappointment, but still not as bad as I expected.  There was also a drop in WV-03, but the other two looked alright.  I guess it just shows that there wasn’t this groundswell of racism that overtook him there.

  12. Ridiculous 70%+ and even 80%+ numbers in some urban areas.  No Republican district in the country is even close to being that lopsided.  When redistricting comes up we need to spread the wealth a little.

    Overall, impressive numbers where I would expect them (Michigan, Indiana, Wisconsin, Virginia, New Mexico).  WI, VA, and especially MI reveal a whole raft of newly vulnerable Republicans that will never see it coming.

    Disappointing numbers also where I would expect them (Louisiana, West Virginia).  On another note it’s interesting that Shelley Capito’s district is the one that Obama did best in from WV.  Almost forgot Gore actually won WV-03, those days are long gone.  In Louisiana, Cassidy and Fleming have won districts that went against Obama, and the state as a whole is getting tough, but those districts are still entirely winnable as long as the election is on a regular day and there is no third-party Dem taking votes.  Boustany’s though is probably lost for good.

    The pair of Texas results show the continuing evolution of the state, us getting stronger in the historically Republican suburbs, while treading water or falling behind further in historically Democratic rural areas.  We tore the lid off Yarmuth’s KY-03, a previously evenly divided Louisville district, but cratered in old-time Dem east Kentucky.  This is a pattern that is being repeated nationwide, but it shows us where to target our resources.  There are a ton of suburban Republicans who have never had to run a tough race, but are now in districts that Obama surged in.

  13. Sadly, I can’t post the Wisconsin long form b/c it exceeds the 1MB size limit for Google Spreadsheets.

    The data is available from the Board of Elections here though:

    http://elections.state.wi.us/d…

    Since the CD, Senate district and Assembly district are given for each individual precinct, there wasn’t a need to look through individual counties; the data was all summarized within one PivotTable.

  14. The entire counties are filled in and I’ve been through the pdf for Honolulu County and worked out which precincts belong to what, but I haven’t followed through with that as it’s 400 pages, my time is limited and Obama won both districts by miles.

    If anybody else wants to take over, I’ve edited the permissions on that spreadsheet. Jump in if you feel keen.

    According to my notes, District 1 is pages 194-414, 421-3, 435-42, 447-65 and 538. District 2 is page 466-537 and 539. All other pages refer to non-Honolulu portions of Hawaii and are therefore included in the county numbers.

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