Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub
airline, avail_seat_km_per_week, incidents_85_99, fatal_accidents_85_99, fatalities_85_99, incidents_00_14, fatal_accidents_00_14, fatalities_00_14
56 rows
country, beer_servings, spirit_servings, wine_servings, total_litres_of_pure_alcohol
193 rows
current_name, states, original_name, current_agency, action, date, year, pres_or_congress, acres_affected
344 rows
cycle, state, senate_class, start_date, end_date, DEM_poll, REP_poll, DEM_result, REP_result...
594 rows
URL, Name/Alias, Appearances, Current?, Gender, Probationary Introl, Full/Reserve Avengers Intro, Year, Years since joining...
173 rows
SHOW, SEASON, CONTESTANT, ELIMINATION-1, ELIMINATION-2, ELIMINATION-3, ELIMINATION-4, ELIMINATION-5, ELIMINATION-6...
921 rows
State, Number of drivers involved in fatal collisions per billion miles, Percentage Of Drivers Involved In Fatal Collisions Who Were Speeding, Percentage Of Drivers Involved In Fatal Collisions Who Were Alcohol-Impaired, Percentage Of Drivers Involved In Fatal Collisions Who Were Not Distracted, Percentage Of Drivers Involved In Fatal Collisions Who Had Not Been Involved In Any Previous Accidents, Car Insurance Premiums ($), Losses incurred by insurance companies for collisions per insured driver ($)
51 rows
year, imdb, title, test, clean_test, binary, budget, domgross, intgross...
1,794 rows
title, site, country, year_release, box_office, director, number_of_subjects, subject, type_of_subject...
761 rows
EPISODE, TITLE, APPLE_FRAME, AURORA_BOREALIS, BARN, BEACH, BOAT, BRIDGE, BUILDING...
403 rows
competitorname, chocolate, fruity, caramel, peanutyalmondy, nougat, crispedricewafer, hard, bar...
85 rows
Song Clean, ARTIST CLEAN, Release Year, COMBINED, First?, Year?, PlayCount, F*G
2,229 rows
Major_code, Major, Major_category, Total, Employed, Employed_full_time_year_round, Unemployed, Unemployment_rate, Median...
173 rows
Major_code, Major, Major_category, Grad_total, Grad_sample_size, Grad_employed, Grad_full_time_year_round, Grad_unemployed, Grad_unemployment_rate...
173 rows
Rank, Major_code, Major, Total, Men, Women, Major_category, ShareWomen, Sample_size...
173 rows
Rank, Major_code, Major, Major_category, Total, Men, Women, ShareWomen, Median
76 rows
page_id, name, urlslug, ID, ALIGN, EYE, HAIR, SEX, GSM...
16,376 rows
RespondentID, In your opinion, which sentence is more gramatically correct?, Prior to reading about it above, had you heard of the serial (or Oxford) comma?, How much, if at all, do you care about the use (or lack thereof) of the serial (or Oxford) comma in grammar?, How would you write the following sentence?, When faced with using the word "data", have you ever spent time considering if the word was a singular or plural noun?, How much, if at all, do you care about the debate over the use of the word "data" as a singluar or plural noun?, In your opinion, how important or unimportant is proper use of grammar?, Gender...
1,129 rows
congress, chamber, bioguide, firstname, middlename, lastname, suffix, birthday, state...
18,635 rows
Member, Party, District, Congress, Resignation Date, Reason, Source, Category
615 rows
MMSA, total_percent_at_risk, high_risk_per_ICU_bed, high_risk_per_hospital, icu_beds, hospitals, total_at_risk
136 rows
YEAR, GoogleKnowlege_Occupation, Show, Group, Raw_Guest_List
2,693 rows
age, n, alcohol-use, alcohol-frequency, marijuana-use, marijuana-frequency, cocaine-use, cocaine-frequency, crack-use...
17 rows
year, election_result, presidential_approval, poll_average
107 rows
country, elo98, elo15, confederation, gdp06, popu06, gdp_source, popu_source
209 rows
year, party, candidate, endorsement_points, percentage_endorsement_points, money_raised, percentage_of_money, primary_vote_percentage, won_primary
109 rows
FILM, RottenTomatoes, RottenTomatoes_User, Metacritic, Metacritic_User, IMDB, Fandango_Stars, Fandango_Ratingvalue, RT_norm...
146 rows
country, confederation, population_share, tv_audience_share, gdp_weighted_share
191 rows
school, conference, song_name, writers, year, student_writer, official_song, contest, bpm...
65 rows
RespondentID, How often do you travel by plane?, Do you ever recline your seat when you fly?, How tall are you?, Do you have any children under 18?, In a row of three seats, who should get to use the two arm rests?, In a row of two seats, who should get to use the middle arm rest?, Who should have control over the window shade?, Is itrude to move to an unsold seat on a plane?...
1,040 rows
RespondentID, Generally speaking, how would you rate your level of knowledgeÊof cuisines from different parts of the world?, How much, if at all, are you interested in cuisines from different parts of the world?, Please rate how much you like the traditional cuisine of Algeria:, Please rate how much you like the traditional cuisine of Argentina., Please rate how much you like the traditional cuisine ofÊAustralia., Please rate how much you like the traditional cuisine of Belgium., Please rate how much you like the traditional cuisine of Bosnia and Herzegovina., Please rate how much you like the traditional cuisine of Brazil....
1,373 rows
state, year, candidate, forecast_prob, result, winflag
207 rows
cycle, branch, race, forecastdate, version, Democrat_WinProbability, Republican_WinProbability, category, Democrat_Won...
1,518 rows
matchup, game_date, type_of_hit, exit_velocity, predicted_zone, camera_zone, used_zone
906 rows
name, year, team, league, goose_eggs, broken_eggs, mehs, league_average_gpct, ppf...
30,962 rows
state, median_household_income, share_unemployed_seasonal, share_population_in_metro_areas, share_population_with_high_school_degree, share_non_citizen, share_white_poverty, gini_index, share_non_white...
51 rows
id, candidate, song, artist, sentiment, theme, album_release_date, line, url
377 rows
year, round, favorite, underdog, favorite_probability, favorite_win_flag
253 rows
timestamp, respondents, category, link, average, mean, median, 1_votes, 2_votes...
80,053 rows
prim_state, area_name, tot_emp, emp_prse, jobs_1000, loc_quotient
373 rows
actors, bill_nighy, keira_knightley, andrew_lincoln, hugh_grant, colin_firth, alan_rickman, heike_makatsch, laura_linney...
14 rows
scenes, bill_nighy, keira_knightley, andrew_lincoln, hugh_grant, colin_firth, alan_rickman, heike_makatsch, laura_linney...
1,003 rows
Performer, Show, Show Start, Show End, Status?, CharEnd, Years Since, #LEAD, #SUPPORT...
248 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win...
68 rows
Unnamed: 0, year, date, all_2534, HS_2534, SC_2534, BAp_2534, BAo_2534, GD_2534...
17 rows
Unnamed: 0, year, date, all_3544, HS_3544, SC_3544, BAp_3544, BAo_3544, GD_3544...
17 rows
Unnamed: 0, year, date, all_2534, HS_2534, SC_2534, BAp_2534, BAo_2534, GD_2534...
17 rows
Unnamed: 0, year, date, all_2534, HS_2534, SC_2534, BAp_2534, BAo_2534, GD_2534...
17 rows
AMONG ADULT MEN, Unnamed: 1, Adult Men, Age, Unnamed: 4, Unnamed: 5, Race, Unnamed: 7, Children...
232 rows
Unnamed: 0, StartDate, EndDate, q0001, q0002, q0004_0001, q0004_0002, q0004_0003, q0004_0004...
1,615 rows
date, name, matched_clips, all_candidate_clips, total_clips, pct_of_all_candidate_clips, query
1,008 rows
date, name, matched_stories, all_candidate_stories, pct_of_all_candidate_stories, query
1,008 rows
bbref_ID, yearID, gameNum, gameID, lgID, startingPos, OFF600, DEF600, PITCH200...
3,930 rows
yearID, gameNum, gameID, lgID, tm_OFF_talent, tm_DEF_talent, tm_PIT_talent, MLB_avg_RPG, talent_RSPG...
172 rows
name_common, age, player_ID, year_ID, team_ID, lg_ID, pct_PT, WAR162, def_pos...
98,796 rows
Unnamed: 0, FirstName, Surname, Adjustment, cleanName, Estimate, finalEstimate
400 rows
Unnamed: 0, FirstName, SMITH, JOHNSON, WILLIAMS, BROWN, JONES, GARCIA, RODRIGUEZ...
20 rows
Unnamed: 0, Miller, Anderson, Martin, Smith, Thompson, Wilson, Moore, White...
20 rows
Unnamed: 0, SMITH, JOHNSON, WILLIAMS, BROWN, JONES, GARCIA, RODRIGUEZ, MILLER...
100 rows
name, rank, count, prop100k, cum_prop100k, pctwhite, pctblack, pctapi, pctaian...
151,671 rows
Start, End, Pollster, Sample Size, Population, Text, Approve, Disapprove, Unsure...
65 rows
city, state, 2015_murders, 2016_murders, change, source, as_of
79 rows
Player, Position, ID, Draft Year, Projected SPM, Superstar, Starter, Role Player, Bust
1,090 rows
gameorder, game_id, lg_id, _iscopy, year_id, date_game, seasongame, is_playoffs, team_id...
126,314 rows
player_name, player_id, season, poss, mp, raptor_offense, raptor_defense, raptor_total, war_total...
17,483 rows
player_name, player_id, season, season_type, team, poss, mp, raptor_offense, raptor_defense...
27,371 rows
player_name, player_id, season, poss, mp, raptor_box_offense, raptor_box_defense, raptor_box_total, raptor_onoff_offense...
3,009 rows
player_name, player_id, season, season_type, team, poss, mp, raptor_box_offense, raptor_box_defense...
4,684 rows
Year, School, Seed, Conference, Conf. W, Conf. L, Conf. %, Conf. place, Reg. W...
2,092 rows
movie, bechdel, peirce, landau, feldman, villareal, hagen, ko, villarobos...
50 rows
MOVIE, DEPARTMENT, FULL_NAME, FIRST_NAME, IMDB, GENDER_PROB, GENDER_GUESS
10,029 rows
Unnamed: 0, Pct. Of major sports searches, Unnamed: 2, Unnamed: 3, Unnamed: 4, Unnamed: 5, Unnamed: 6, Unnamed: 7, Unnamed: 8
208 rows
Unnamed: 0, Unnamed: 1, Democrat, Unnamed: 3, Unnamed: 4, Unnamed: 5, Unnamed: 6, Unnamed: 7, Independent...
34 rows
pfr_player_id, player_name, career_try, career_ranypa, career_wowy, bcs_rating
6,496 rows
ID, cancer, diabetes, heart_disease, belly, ever_smoked, currently_smoke, smoke_often, smoke_rarely...
54 rows
0.00719424460432, 0.213771839671, 0.261048304214, 0.00719424460432.1, 0.0668036998972, 0.0082219938335, 0.0195272353546, 0.151079136691, 0.016443987667...
100 rows
person, dept, eow, cause, cause_short, date, year, canine, dept_name...
22,800 rows
name, age, gender, raceethnicity, month, day, year, streetaddress, city...
467 rows
city, police_force_size, all, white, non-white, black, hispanic, asian
75 rows
Question, Start, End, Pollster, Population, Support, Republican Support, Democratic Support, URL
57 rows
cycle, state, modeldate, candidate_name, candidate_id, pct_estimate, pct_trend_adjusted, timestamp, comment...
217,473 rows
race, state, modeldate, candidate_name, candidate_id, pct_estimate, pct_trend_adjusted, timestamp, comment...
301,695 rows
ID, Pollster, Polls, Live Caller With Cellphones, Internet, NCPP/AAPOR/Roper, Polls.1, Simple Average Error, Races Called Correctly...
372 rows
pollno, race, year, location, type_simple, type_detail, pollster, partisan, polldate...
7,977 rows
Pollster, # of Polls, NCPP / AAPOR / Roper, Exclusively Live Caller With Cellphones, Methodology, Banned by 538, Historical Advanced Plus-Minus, Predictive Plus-Minus, 538 Grade...
396 rows
pollno, race, year, location, type_simple, type_detail, pollster, partisan, polldate...
8,512 rows
Pollster, Pollster Rating ID, # of Polls, NCPP / AAPOR / Roper, Live Caller With Cellphones, Methodology, Banned by 538, Historical Advanced Plus-Minus, Predictive Plus-Minus...
430 rows
pollno, race, year, location, type_simple, type_detail, pollster, pollster_rating_id, polldate...
9,133 rows
Pollster, Pollster Rating ID, # of Polls, NCPP / AAPOR / Roper, Live Caller With Cellphones, Methodology, Banned by 538, Predictive Plus-Minus, 538 Grade...
453 rows
poll_id, question_id, race_id, year, race, location, type_simple, type_detail, pollster...
9,559 rows
Person, Party, State, Event, Type, Date, Link, Snippet
42 rows
Person, Party, Statement Date, Latest Statement, Statement Score
25 rows
Person, Party, State, Event, Type, Date, Link, Snippet
74 rows
Person, Party, Statement Date, Latest Statement, Statement Score
27 rows
question_id, start_date, end_date, pollster_id, pollster, sponsors, sample_size, population, methodology...
1,631 rows
president, president_name, title, date, city, state, building, room
154 rows
Candidate, State, District, Office Type, Race Type, Race Primary Election Date, Primary Status, Primary Runoff Status, General Status...
811 rows
Candidate, State, District, Office Type, Race Type, Race Primary Election Date, Primary Status, Primary Runoff Status, General Status...
774 rows
Day, "Hurricane Harvey": (United States), "Hurricane Irma": (United States), "Hurricane Maria": (United States), "Hurricane Jose": (United States)
37 rows
Date, title:"Puerto Rico", title:"Puerto Rico" AND (title:Trump OR title:President), title:Florida, title:Florida AND (title:Trump OR title:President), title:Texas, title:Texas AND (title:Trump OR title:President)
51 rows
Newspaper, Daily Circulation, 2004, Daily Circulation, 2013, Change in Daily Circulation, 2004-2013, Pulitzer Prize Winners and Finalists, 1990-2003, Pulitzer Prize Winners and Finalists, 2004-2014, Pulitzer Prize Winners and Finalists, 1990-2014
50 rows
Block, ForwardAsset, ForwardQuantity, BackwardAsset, BackwardQuantity
26,038 rows
RespondentID, In your own words, what would you call the part of the country you live in now?, How much, if at all, do you personally identify as a Midwesterner?, Unnamed: 3, Unnamed: 4, Unnamed: 5, Which of the following states do you consider part of the Midwest? Please select all that apply. , Unnamed: 7, Unnamed: 8...
2,779 rows
RespondentID, In your own words, what would you call the part of the country you live in now?, How much, if at all, do you personally identify as a Southerner?, Unnamed: 3, Unnamed: 4, Unnamed: 5, Which of the following states do you consider part of the South? Please select all that apply. , Unnamed: 7, Unnamed: 8...
2,529 rows
What is your present religion, if any?, Unnamed: 1, Do you consider yourself to be an evangelical?, Do you attend religious services, How often do you: Pray in public with visible motions (sign of the cross, bowing, prostration, shokeling, etc), How often do you: Pray in public using some kind of physical object (rosary, tefillin, etc), How often do you: Pray aloud before meals in the presence of people who don't belong to your religion, How often do you: Tell someone you'll pray for him or her, How often do you: Ask or offer to pray with someone...
1,040 rows
q1, issue_matters_most, trump_approval, q4, q5, q6, q7, q8, q9...
7,169 rows
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9...
1,387 rows
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9...
932 rows
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9...
1,466 rows
investigation, investigation-start, investigation-end, investigation-days, name, indictment-days , type, cp-date, cp-days...
194 rows
In general, how worried are you about earthquakes?, How worried are you about the Big One, a massive, catastrophic earthquake?, Do you think the "Big One" will occur in your lifetime?, Have you ever experienced an earthquake?, Have you or anyone in your household taken any precautions for an earthquake (packed an earthquake survival kit, prepared an evacuation plan, etc.)?, How familiar are you with the San Andreas Fault line?, How familiar are you with the Yellowstone Supervolcano?, Age, What is your gender?...
1,013 rows
date, NYC-3-1-1, ACS, BPSI, CAU, CHALL, DEP, DOB, DOE...
1,783 rows
StartDate, EndDate, Which of the following best describes your current relationship status?, How long have you been in your current relationship? If you are not currently in a relationship, please answer according to your last relationship., When both you and your partner are at home, how often do you sleep in separate beds?, When you're not sleeping in the same bed as your partner, where do you typically sleep?, Unnamed: 6, When you're not sleeping in the same bed, where does your partner typically sleep?, Unnamed: 8...
1,094 rows
Date, State, Race, Median Household Income, % Bachelor's Degree or Higher, Clinton Margin Improvement Over Obama, 2017-2018 Dem Margin Improvement Over Partisan Lean
200 rows
RespondentID, Have you seen any of the 6 films in the Star Wars franchise?, Do you consider yourself to be a fan of the Star Wars film franchise?, Which of the following Star Wars films have you seen? Please select all that apply., Unnamed: 4, Unnamed: 5, Unnamed: 6, Unnamed: 7, Unnamed: 8...
1,187 rows
phrase, category, d_speeches, r_speeches, total, percent_of_d_speeches, percent_of_r_speeches, chi2, pval
2,223 rows
RespondentID, Consider the following hypothetical situations: <br>In Lottery A, you have a 50% chance of success, with a payout of $100. <br>In Lottery B, you have a 90% chance of success, with a payout of $20. <br><br>Assuming you have $10 to bet, would you play Lottery A or Lottery B?, Do you ever smoke cigarettes?, Do you ever drink alcohol?, Do you ever gamble?, Have you ever been skydiving?, Do you ever drive above the speed limit?, Have you ever cheated on your significant other?, Do you eat steak?...
551 rows
server, seconds_before_next_point, day, opponent, game_score, set, game
120 rows
Title, Date, Federal Reporter Citation, Westlaw Citation, Issue, Weight, Judge1, Judge2, Judge3...
954 rows
Country, Number of Incidents, Percent, Number Killed, Number Injured, Number US Killed, Number US Injured
129 rows
iyear, Belgium, Denmark, France, Germany, Greece, Ireland, Italy, Luxembourg...
45 rows
RespondentID, Do you celebrate Thanksgiving?, What is typically the main dish at your Thanksgiving dinner?, What is typically the main dish at your Thanksgiving dinner? - Other (please specify), How is the main dish typically cooked?, How is the main dish typically cooked? - Other (please specify), What kind of stuffing/dressing do you typically have?, What kind of stuffing/dressing do you typically have? - Other (please specify), What type of cranberry saucedo you typically have?...
1,058 rows
docketNumber, dateFiled, caseName, plaintiff, defendant, currentLocation, previousLocation, jurisdiction, judge...
57 rows
year, avg, Canada, France, Germany, Greece, Hungary, Italy, Netherlands...
15 rows
year, avg, Canada, France, Germany, Greece, Hungary, Italy, Netherlands...
17 rows
created_at, text, url, replies, retweets, favorites, user, bioguide_id, party...
288,615 rows
statefips, state, gisjoin, lat_tract, long_tract, population, adj_radiuspop_5, urbanindex
73,280 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
date, actual_mean_temp, actual_min_temp, actual_max_temp, average_min_temp, average_max_temp, record_min_temp, record_max_temp, record_min_temp_year...
365 rows
Jurisdiction, Year, Month, New registered voters
106 rows
RespondentID, Do you typically check a daily weather report?, How do you typically check the weather?, A specific website or app (please provide the answer), If you had a smartwatch (like the soon to be released Apple Watch), how likely or unlikely would you be to check the weather on that device?, Age, What is your gender?, How much total combined money did all members of your HOUSEHOLD earn last year?, US Region
928 rows
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24 rows
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