| A | B | C | D | E | F | G | |
|---|---|---|---|---|---|---|---|
1 | variable | class | example | type | source | description | SQL table |
2 | file | character | CREC-2020-07-09-pt1-PgH3078-6-000108-20537.txt | member-behavior | congressional record | parsed congressional record speech file name in data/txt folder | speeches |
3 | speech_id | character | 000108 | member-behavior | parser | id assigned by parser. See https://judgelord.github.io/cr/speakers#Save_text_parsed_by_member_name | speeches |
4 | icpsr | integer | 20537 | member-key | voteview | legislator id, unique to a member in a party (party-switchers get a new ICPSR id) | speeches, members |
5 | date | Date | 2020-07-09 | member-behavior | congressional record | YYYY-MM-DD | speeches |
6 | year | integer | 2020 | member-behavior | congressional record | YYYY | speeches |
7 | congress | numeric | 116 | member | congressional record | speeches, members | |
8 | chamber | character | House | member | congressional record | speeches, members | |
9 | bioname | character | MOORE, Gwendolynne S. (Gwen) | member | voteview | voteview canonical name, unique to each legislator | speeches, members |
10 | id | character | MH11620537 | member | voteview | members | |
11 | party_code | integer | 100 | member-party | voteview | 100 = Democrat, 200 = Republican | members |
12 | cqlabel | character | (WI-04) | geographic identification | voteview | (state_abbrev-district_code) | members |
13 | state | character | wisconsin | geographic identification | voteview | members | |
14 | state_abbrev | character | WI | geographic identification | voteview | members | |
15 | bioImgURL | character | 020537.jpg | member | voteview | https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members |
16 | seo_name | character | gwendolynne-s-gwen-moore | member | voteview | https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members |
17 | district_code | numeric | 4 | geographic identification | voteview | Integer 0-99. Identifier for the district that the member represents within their state (e.g. 3 for the Alabama 3rd Congressional District). Senate members are given district_code 0. Members who represent historical “at-large” districts are assigned 99, 98, or 1 in various https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members, connectivity, demographics, partisanship |
18 | party_name | character | Democratic Party | member-party | voteview | Integer 1-9999. Identifying code for the member’s party. Please see documentation for Party Data for more information about which party_code identifiers refer to which parties. | members |
19 | nominate.dim2 | numeric | -0.249 | member-behavior | voteview | https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members |
20 | nominate.dim1 | numeric | -0.528 | member-behavior | voteview | https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members |
21 | nominate.geo_mean_probability | numeric | 0.9612078 | member-behavior | voteview | https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members |
22 | party_size | integer | 236 | member-party | voteview | https://github.com/voteview/Rvoteview/blob/master/vignettes/README.md | members |
23 | speeches_n | integer | 1 | member-behavior | congressional record | total number of speeches per icpsr YYYY-YYYY | members |
24 | facebook_sci | integer | 1088428 | connectivity | https://data.humdata.org | within-district facebook connections. The SCI uses an anonymized snapshot of active Facebook users and their friendship networks to measure the intensity of social connectedness between locations. Users are assigned to locations based on their information and activity on Facebook, including the stated city on their Facebook profile, and device and connection information. Formally, the Social Connectedness Index between two locations i and j is defined as: SCIi,j = Connections(i,j) Usersi ∗ Usersj Where Usersi and Usersj are the number of Facebook users in locations i and j, and Connections(i,j) is the total number of Facebook friendship connections between individuals in the two locations. | connectivity |
25 | flow_count | numeric | 4389604 | connectivity | https://www.safegraph.com/ | within-district travel | connectivity |
26 | flow_count_border | numeric | 667951 | connectivity | https://www.safegraph.com/ | within-district travel in border census blocks | |
27 | to_out | integer | 32 | ||||
28 | facebook_sci_out | integer | 180506 | connectivity | https://data.humdata.org | out-district facebook connections | |
29 | flow_count_out | numeric | 2103750 | connectivity | https://www.safegraph.com/ | out-district travel | |
30 | flow_count_border_out | numeric | 620362 | connectivity | https://www.safegraph.com/ | out-district travel from and to border census blocks | |
31 | facebook_sci_ratio | numeric | 6.029872 | connectivity | https://data.humdata.org | ratio of within-district to out-district facebook connections | |
32 | flow_ratio | numeric | 2.086562 | connectivity | https://www.safegraph.com/ | ratio of within-district to out-district travel | |
33 | flow_ratio_border | numeric | 1.076712 | connectivity | https://www.safegraph.com/ | ratio of within-district to out-district travel from and to border census blocks | |
34 | GEO_ID | character | 5001500US5504 | geographic identification | US Census | us congress district unique id | demographics |
35 | district_name | character | Congressional District 4 (115th Congress), Wisconsin | district-demographics | US Census | demographics | |
36 | name | character | SF1DP1002 | district-demographics | US Census | demographics | |
37 | value | numeric | 100 | district-demographics | US Census | party code? | demographics |
38 | format | character | Percent | district-demographics | US Census | "Number" or "Percent" (row 2 of the CD_DEMO_DATA") | demographics |
39 | type | character | SEX AND AGE | district-demographics | US Census | Census variable catagory (row 3 of CD_DEMO_DATA) | demographics |
40 | measure | character | Total population | district-demographics | US Census | Row 4 of CD_DEMO_DATA | demographics |
41 | group | character | district-demographics | US Census | Row 5 of CD_DEMO_DATA | demographics | |
42 | GEOID | character | 55079054500001 | geographic identification | WI LTSB/US Census | ward unique id | demographics |
43 | CNTY_FIPS | numeric | 55079 | geographic identification | WI LTSB/US Census | county unique id | demographics |
44 | CNTY_NAME | character | Milwaukee | geographic identification | WI LTSB/US Census | county name | demographics |
45 | COUSUBFP | numeric | 5450 | geographic identification | WI LTSB/US Census | county sub id | demographics |
46 | MCD_FIPS | numeric | 5507905450 | geographic identification | WI LTSB/US Census | mcd unique id | demographics |
47 | MCD_NAME | character | Bayside | geographic identification | WI LTSB/US Census | mcd name | demographics |
48 | CTV | character | V | geographic identification | WI LTSB/US Census | type value | demographics |
49 | LABEL | character | Bayside - V 0001 | geographic identification | WI LTSB/US Census | precinct label | demographics |
50 | LSAD | numeric | 47 | geographic identification | WI LTSB/US Census | designation | demographics |
51 | DISTRICT | numeric | 23 | geographic identification | WI LTSB/US Census | assembly district | demographics |
52 | ASM | numeric | 23 | geographic identification | WI LTSB/US Census | assembly district | demographics |
53 | SEN | numeric | 8 | geographic identification | WI LTSB/US Census | senate district | demographics |
54 | CON | numeric | 4 | geographic identification | WI LTSB/US Census | congressional district | demographics |
55 | STR_WARDS | character | 0001 | geographic identification | WI LTSB/US Census | ward simple | demographics |
56 | PERSONS | numeric | 938 | ward demographics | WI LTSB/US Census | total persons | demographics |
57 | PERSONS18 | numeric | 785 | ward demographics | WI LTSB/US Census | total persons over 18 | demographics |
58 | WHITE | numeric | 775 | ward demographics | WI LTSB/US Census | white persons | demographics |
59 | BLACK | numeric | 61 | ward demographics | WI LTSB/US Census | black persons | demographics |
60 | HISPANIC | numeric | 24 | ward demographics | WI LTSB/US Census | hispanic persons | demographics |
61 | ASIAN | numeric | 67 | ward demographics | WI LTSB/US Census | asian persons | demographics |
62 | AMINDIAN | numeric | 3 | ward demographics | WI LTSB/US Census | native american persons | demographics |
63 | PISLAND | numeric | 0 | ward demographics | WI LTSB/US Census | pacific islander persons | demographics |
64 | OTHER | numeric | 5 | ward demographics | WI LTSB/US Census | other persons | demographics |
65 | OTHERMLT | numeric | 3 | ward demographics | WI LTSB/US Census | other persons | demographics |
66 | WHITE18 | numeric | 664 | ward demographics | WI LTSB/US Census | white persons over 18 | demographics |
67 | BLACK18 | numeric | 45 | ward demographics | WI LTSB/US Census | black persons over 18 | demographics |
68 | HISPANIC18 | numeric | 19 | ward demographics | WI LTSB/US Census | hispanic persons over 18 | demographics |
69 | ASIAN18 | numeric | 50 | ward demographics | WI LTSB/US Census | asian persons over 18 | demographics |
70 | AMINDIAN18 | numeric | 2 | ward demographics | WI LTSB/US Census | native american persons over 18 | demographics |
71 | PISLAND18 | numeric | 0 | ward demographics | WI LTSB/US Census | pacific islander persons over 18 | demographics |
72 | OTHER18 | numeric | 2 | ward demographics | WI LTSB/US Census | other persons over 18 | demographics |
73 | OTHERMLT18 | numeric | 3 | ward demographics | WI LTSB/US Census | other persons over 18 | demographics |
74 | TOT_CUM_10 | numeric | 9044 | cumulative value | Calculated | cumulative raw vote of statewide elections from 2002-2010 under the 2002 district maps | partisanship |
75 | REP_CUM_10 | numeric | 3357 | cumulative value | Calculated | cumulative raw vote of statewide elections for rep candidates from 2002-2010 under the 2002 district maps | partisanship |
76 | DEM_CUM_10 | numeric | 5576 | cumulative value | Calculated | cumulative raw vote of statewide elections for dem candidates from 2002-2010 under the 2002 district maps | partisanship |
77 | TOT_CUM_18 | numeric | 7500 | cumulative value | Calculated | cumulative raw vote of statewide elections from 2012-2020 under the 2012 district maps | partisanship |
78 | REP_CUM_18 | numeric | 2900 | cumulative value | Calculated | cumulative raw vote of statewide elections for rep candidates from 2012-2020 under the 2012 district maps | partisanship |
79 | DEM_CUM_18 | numeric | 4454 | cumulative value | Calculated | cumulative raw vote of statewide elections for dem candidates from 2012-2020 under the 2012 district maps | partisanship |
80 | REP_PCT_PROJECTION | numeric | 0.3711853 | cumulative value | Calculated | unweighted percentage projection of rep vote share based on previous ten years - 2002-2010 included | partisanship |
81 | DEM_PCT_PROJECTION | numeric | 0.6165414 | cumulative value | Calculated | unweighted percentage projection of dem vote share based on previous ten years - 2002-2010 included | partisanship |
82 | REP_PCT_PROJ_18 | numeric | 0.3866667 | cumulative value | Calculated | unweighted percentage projection of rep vote share based on previous ten years - same but from 2012-2018 | partisanship |
83 | DEM_PCT_PROJ_18 | numeric | 0.5938667 | cumulative value | Calculated | unweighted percentage projection of dem vote share based on previous ten years - same but from 2012-2018 | partisanship |
84 | REP_PCT_DIF_GOV18 | numeric | 0.01599406 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-GOVREP18_P | partisanship |
85 | REP_PCT_DIF_PRE16 | numeric | 0.05138836 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-PREREP16_P | partisanship |
86 | REP_PCT_DIF_GOV14 | numeric | -0.07963436 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-GOVREP14_P | partisanship |
87 | REP_PCT_DIF_PRE12 | numeric | -0.04898275 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-PREREP12_P | partisanship |
88 | REP_PCT_DIF_USH18 | numeric | 0.04706009 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-USHREP18_P | partisanship |
89 | REP_PCT_DIF_USH16 | numeric | 0.3711853 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-USHREP16_P | partisanship |
90 | REP_PCT_DIF_USH14 | numeric | -0.06974295 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-USHREP14_P | partisanship |
91 | REP_PCT_DIF_USH12 | numeric | -0.0740837 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-USHREP12_P | partisanship |
92 | REP_PCT_DIF_WSA18 | numeric | 0.006716452 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-WSAREP18_P | partisanship |
93 | REP_PCT_DIF_WSA16 | numeric | -0.584955 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-WSAREP16_P | partisanship |
94 | REP_PCT_DIF_WSA14 | numeric | -0.110768 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-WSAREP14_P | partisanship |
95 | REP_PCT_DIF_WSA12 | numeric | -0.1111895 | cumulative value | Calculated | difference in projection and specific race - REP_PCT_PROJECTION-WSAREP12_P | partisanship |
96 | GOVREP18_P | numeric | 0.3551913 | election result | WI LTSB | governor rep % vote share 2018 | partisanship |
97 | GOVDEM18_P | numeric | 0.6284153 | election result | WI LTSB | governor dem % vote share 2018 | partisanship |
98 | PREREP16_P | numeric | 0.319797 | election result | WI LTSB | president rep % vote share 2016 | partisanship |
99 | PREDEM16_P | numeric | 0.6175973 | election result | WI LTSB | president dem % vote share 2016 | partisanship |
100 | GOVREP14_P | numeric | 0.4508197 | election result | WI LTSB | governor 2014 p | partisanship |