fivethirtyeight
Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub · About: simonw/fivethirtyeight-datasette
Tables
airline-safety/airline-safety
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
alcohol-consumption/drinks
country, beer_servings, spirit_servings, wine_servings, total_litres_of_pure_alcohol
193 rows
antiquities-act/actions_under_antiquities_act
current_name, states, original_name, current_agency, action, date, year, pres_or_congress, acres_affected
344 rows
august-senate-polls/august_senate_polls
cycle, state, senate_class, start_date, end_date, DEM_poll, REP_poll, DEM_result, REP_result, error, absolute_error
594 rows
avengers/avengers
URL, Name/Alias, Appearances, Current?, Gender, Probationary Introl, Full/Reserve Avengers Intro, Year, Years since joining, Honorary, Death1, Return1, Death2, Return2, Death3, Return3, Death4, Return4, Death5, Return5, Notes
173 rows
bachelorette/bachelorette
SHOW, SEASON, CONTESTANT, ELIMINATION-1, ELIMINATION-2, ELIMINATION-3, ELIMINATION-4, ELIMINATION-5, ELIMINATION-6, ELIMINATION-7, ELIMINATION-8, ELIMINATION-9, ELIMINATION-10, DATES-1, DATES-2, DATES-3, DATES-4, DATES-5, DATES-6, DATES-7, DATES-8, DATES-9, DATES-10
921 rows
bad-drivers/bad-drivers
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
bechdel/movies
year, imdb, title, test, clean_test, binary, budget, domgross, intgross, code, budget_2013$, domgross_2013$, intgross_2013$, period code, decade code
1,794 rows
biopics/biopics
title, site, country, year_release, box_office, director, number_of_subjects, subject, type_of_subject, race_known, subject_race, person_of_color, subject_sex, lead_actor_actress
761 rows
bob-ross/elements-by-episode
EPISODE, TITLE, APPLE_FRAME, AURORA_BOREALIS, BARN, BEACH, BOAT, BRIDGE, BUILDING, BUSHES, CABIN, CACTUS, CIRCLE_FRAME, CIRRUS, CLIFF, CLOUDS, CONIFER, CUMULUS, DECIDUOUS, DIANE_ANDRE, DOCK, DOUBLE_OVAL_FRAME, FARM, FENCE, FIRE, FLORIDA_FRAME, FLOWERS, FOG, FRAMED, GRASS, GUEST, HALF_CIRCLE_FRAME, HALF_OVAL_FRAME, HILLS, LAKE, LAKES, LIGHTHOUSE, MILL, MOON, MOUNTAIN, MOUNTAINS, NIGHT, OCEAN, OVAL_FRAME, PALM_TREES, PATH, PERSON, PORTRAIT, RECTANGLE_3D_FRAME, RECTANGULAR_FRAME, RIVER, ROCKS, SEASHELL_FRAME, SNOW, SNOWY_MOUNTAIN, SPLIT_FRAME, STEVE_ROSS, STRUCTURE, SUN, TOMB_FRAME, TREE, TREES, TRIPLE_FRAME, WATERFALL, WAVES, WINDMILL, WINDOW_FRAME, WINTER, WOOD_FRAMED
403 rows
candy-power-ranking/candy-data
competitorname, chocolate, fruity, caramel, peanutyalmondy, nougat, crispedricewafer, hard, bar, pluribus, sugarpercent, pricepercent, winpercent
85 rows
classic-rock/classic-rock-song-list
Song Clean, ARTIST CLEAN, Release Year, COMBINED, First?, Year?, PlayCount, F*G
2,229 rows
college-majors/all-ages
Major_code, Major, Major_category, Total, Employed, Employed_full_time_year_round, Unemployed, Unemployment_rate, Median, P25th, P75th
173 rows
college-majors/grad-students
Major_code, Major, Major_category, Grad_total, Grad_sample_size, Grad_employed, Grad_full_time_year_round, Grad_unemployed, Grad_unemployment_rate, Grad_median, Grad_P25, Grad_P75, Nongrad_total, Nongrad_employed, Nongrad_full_time_year_round, Nongrad_unemployed, Nongrad_unemployment_rate, Nongrad_median, Nongrad_P25, Nongrad_P75, Grad_share, Grad_premium
173 rows
college-majors/recent-grads
Rank, Major_code, Major, Total, Men, Women, Major_category, ShareWomen, Sample_size, Employed, Full_time, Part_time, Full_time_year_round, Unemployed, Unemployment_rate, Median, P25th, P75th, College_jobs, Non_college_jobs, Low_wage_jobs
173 rows
college-majors/women-stem
Rank, Major_code, Major, Major_category, Total, Men, Women, ShareWomen, Median
76 rows
comic-characters/dc-wikia-data
page_id, name, urlslug, ID, ALIGN, EYE, HAIR, SEX, GSM, ALIVE, APPEARANCES, FIRST APPEARANCE, YEAR
6,896 rows
comic-characters/marvel-wikia-data
page_id, name, urlslug, ID, ALIGN, EYE, HAIR, SEX, GSM, ALIVE, APPEARANCES, FIRST APPEARANCE, Year
16,376 rows
comma-survey/comma-survey
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, Age, Household Income, Education, Location (Census Region)
1,129 rows
congress-age/congress-terms
congress, chamber, bioguide, firstname, middlename, lastname, suffix, birthday, state, party, incumbent, termstart, age
18,635 rows
congress-generic-ballot/generic_topline_historical
subgroup, modeldate, dem_estimate, dem_hi, dem_lo, rep_estimate, rep_hi, rep_lo, timestamp
7,669 rows
congress-resignations/congressional_resignations
Member, Party, District, Congress, Resignation Date, Reason, Source, Category
615 rows
covid-geography/mmsa-icu-beds
MMSA, total_percent_at_risk, high_risk_per_ICU_bed, high_risk_per_hospital, icu_beds, hospitals, total_at_risk
136 rows
daily-show-guests/daily_show_guests
YEAR, GoogleKnowlege_Occupation, Show, Group, Raw_Guest_List
2,693 rows
drug-use-by-age/drug-use-by-age
age, n, alcohol-use, alcohol-frequency, marijuana-use, marijuana-frequency, cocaine-use, cocaine-frequency, crack-use, crack-frequency, heroin-use, heroin-frequency, hallucinogen-use, hallucinogen-frequency, inhalant-use, inhalant-frequency, pain-releiver-use, pain-releiver-frequency, oxycontin-use, oxycontin-frequency, tranquilizer-use, tranquilizer-frequency, stimulant-use, stimulant-frequency, meth-use, meth-frequency, sedative-use, sedative-frequency
17 rows
early-senate-polls/early-senate-polls
year, election_result, presidential_approval, poll_average
107 rows
elo-blatter/elo_blatter
country, elo98, elo15, confederation, gdp06, popu06, gdp_source, popu_source
209 rows
endorsements-june-30/endorsements-june-30
year, party, candidate, endorsement_points, percentage_endorsement_points, money_raised, percentage_of_money, primary_vote_percentage, won_primary
109 rows
fandango/fandango_score_comparison
FILM, RottenTomatoes, RottenTomatoes_User, Metacritic, Metacritic_User, IMDB, Fandango_Stars, Fandango_Ratingvalue, RT_norm, RT_user_norm, Metacritic_norm, Metacritic_user_nom, IMDB_norm, RT_norm_round, RT_user_norm_round, Metacritic_norm_round, Metacritic_user_norm_round, IMDB_norm_round, Metacritic_user_vote_count, IMDB_user_vote_count, Fandango_votes, Fandango_Difference
146 rows
fifa/fifa_countries_audience
country, confederation, population_share, tv_audience_share, gdp_weighted_share
191 rows
fight-songs/fight-songs
school, conference, song_name, writers, year, student_writer, official_song, contest, bpm, sec_duration, fight, number_fights, victory, win_won, victory_win_won, rah, nonsense, colors, men, opponents, spelling, trope_count, spotify_id
65 rows
flying-etiquette-survey/flying-etiquette
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?, Generally speaking, is it rude to say more than a few words tothe stranger sitting next to you on a plane?, On a 6 hour flight from NYC to LA, how many times is it acceptable to get up if you're not in an aisle seat?, Under normal circumstances, does a person who reclines their seat during a flight have any obligation to the person sitting behind them?, Is itrude to recline your seat on a plane?, Given the opportunity, would you eliminate the possibility of reclining seats on planes entirely?, Is it rude to ask someone to switch seats with you in order to be closer to friends?, Is itrude to ask someone to switch seats with you in order to be closer to family?, Is it rude to wake a passenger up if you are trying to go to the bathroom?, Is itrude to wake a passenger up if you are trying to walk around?, In general, is itrude to bring a baby on a plane?, In general, is it rude to knowingly bring unruly children on a plane?, Have you ever used personal electronics during take off or landing in violation of a flight attendant's direction?, Have you ever smoked a cigarette in an airplane bathroom when it was against the rules?, Gender, Age, Household Income, Education, Location (Census Region)
1,040 rows
food-world-cup/food-world-cup-data
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., Please rate how much you like the traditional cuisine of Cameroon., Please rate how much you like the traditional cuisine of Chile., Please rate how much you like the traditional cuisine of Colombia., Please rate how much you like the traditional cuisine of Costa Rica., Please rate how much you like the traditional cuisine of Croatia., Please rate how much you like the traditional cuisine of Ecuador., Please rate how much you like the traditional cuisine of England., Please rate how much you like the traditional cuisine of France., Please rate how much you like the traditional cuisine of Germany., Please rate how much you like the traditional cuisine of Ghana., Please rate how much you like the traditional cuisine of Greece., Please rate how much you like the traditional cuisine of Honduras., Please rate how much you like the traditional cuisine of Iran., Please rate how much you like the traditional cuisine of Italy., Please rate how much you like the traditional cuisine of Ivory Coast., Please rate how much you like the traditional cuisine of Japan., Please rate how much you like the traditional cuisine of Mexico., Please rate how much you like the traditional cuisine of the Netherlands., Please rate how much you like the traditional cuisine of Nigeria., Please rate how much you like the traditional cuisine of Portugal., Please rate how much you like the traditional cuisine of Russia., Please rate how much you like the traditional cuisine of South Korea., Please rate how much you like the traditional cuisine of Spain., Please rate how much you like the traditional cuisine of Switzerland., Please rate how much you like the traditional cuisine of United States., Please rate how much you like the traditional cuisine of Uruguay., Please rate how much you like the traditional cuisine of China., Please rate how much you like the traditional cuisine of India., Please rate how much you like the traditional cuisine of Thailand., Please rate how much you like the traditional cuisine of Turkey., Please rate how much you like the traditional cuisine of Cuba., Please rate how much you like the traditional cuisine of Ethiopia., Please rate how much you like the traditional cuisine of Vietnam., Please rate how much you like the traditional cuisine of Ireland., Gender, Age, Household Income, Education, Location (Census Region)
1,373 rows
forecast-methodology/historical-senate-predictions
state, year, candidate, forecast_prob, result, winflag
207 rows
forecast-review/forecast_results_2018
cycle, branch, race, forecastdate, version, Democrat_WinProbability, Republican_WinProbability, category, Democrat_Won, Republican_Won, uncalled
1,518 rows
foul-balls/foul-balls
matchup, game_date, type_of_hit, exit_velocity, predicted_zone, camera_zone, used_zone
906 rows
goose/goose_rawdata
name, year, team, league, goose_eggs, broken_eggs, mehs, league_average_gpct, ppf, replacement_gpct, gwar, key_retro
30,962 rows
hate-crimes/hate_crimes
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, share_voters_voted_trump, hate_crimes_per_100k_splc, avg_hatecrimes_per_100k_fbi
51 rows
hip-hop-candidate-lyrics/genius_hip_hop_lyrics
id, candidate, song, artist, sentiment, theme, album_release_date, line, url
377 rows
historical-ncaa-forecasts/historical-538-ncaa-tournament-model-results
year, round, favorite, underdog, favorite_probability, favorite_win_flag
253 rows
inconvenient-sequel/ratings
timestamp, respondents, category, link, average, mean, median, 1_votes, 2_votes, 3_votes, 4_votes, 5_votes, 6_votes, 7_votes, 8_votes, 9_votes, 10_votes, 1_pct, 2_pct, 3_pct, 4_pct, 5_pct, 6_pct, 7_pct, 8_pct, 9_pct, 10_pct
80,053 rows
librarians/librarians-by-msa
prim_state, area_name, tot_emp, emp_prse, jobs_1000, loc_quotient
373 rows
love-actually/love_actually_adjacencies
actors, bill_nighy, keira_knightley, andrew_lincoln, hugh_grant, colin_firth, alan_rickman, heike_makatsch, laura_linney, emma_thompson, liam_neeson, kris_marshall, abdul_salis, martin_freeman, rowan_atkinson
14 rows
love-actually/love_actually_appearances
scenes, bill_nighy, keira_knightley, andrew_lincoln, hugh_grant, colin_firth, alan_rickman, heike_makatsch, laura_linney, emma_thompson, liam_neeson, kris_marshall, abdul_salis, martin_freeman, rowan_atkinson
1,003 rows
mad-men/show-data
Performer, Show, Show Start, Show End, Status?, CharEnd, Years Since, #LEAD, #SUPPORT, #Shows, Score, Score/Y, lead_notes, support_notes, show_notes
248 rows
march-madness-predictions/bracket-00
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-01
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-02
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-03
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-04
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-05
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-06
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-07
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-08
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-09
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-10
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-11
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-12
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-13
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-14
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-15
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-16
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-17
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-18
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-19
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-20
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-21
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-22
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-23
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-24
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-25
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-26
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-27
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win
68 rows
march-madness-predictions/bracket-28
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win
68 rows
march-madness-predictions/bracket-29
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win
68 rows
march-madness-predictions/bracket-30
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win
68 rows
march-madness-predictions/bracket-31
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-32
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-33
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-34
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-35
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-36
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-37
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-38
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-39
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-40
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-41
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-42
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-43
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-44
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-45
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-46
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-47
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-48
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds, timestamp
68 rows
march-madness-predictions/bracket-49
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-50
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-51
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-52
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-53
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-54
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-55
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-56
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-57
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-58
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-59
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-60
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
march-madness-predictions/bracket-61
team_id, team_name, team_seed, team_region, playin_flag, team_alive, rd1_win, rd2_win, rd3_win, rd4_win, rd5_win, rd6_win, rd7_win, win_odds
68 rows
marriage/both_sexes
Unnamed: 0, year, date, all_2534, HS_2534, SC_2534, BAp_2534, BAo_2534, GD_2534, White_2534, Black_2534, Hisp_2534, NE_2534, MA_2534, Midwest_2534, South_2534, Mountain_2534, Pacific_2534, poor_2534, mid_2534, rich_2534, all_3544, HS_3544, SC_3544, BAp_3544, BAo_3544, GD_3544, White_3544, Black_3544, Hisp_3544, NE_3544, MA_3544, Midwest_3544, South_3544, Mountain_3544, Pacific_3544, poor_3544, mid_3544, rich_3544, all_4554, HS_4554, SC_4554, BAp_4554, BAo_4554, GD_4554, White_4554, Black_4554, Hisp_4554, NE_4554, MA_4554, Midwest_4554, South_4554, Mountain_4554, Pacific_4554, poor_4554, mid_4554, rich_4554, nokids_all_2534, kids_all_2534, nokids_HS_2534, nokids_SC_2534, nokids_BAp_2534, nokids_BAo_2534, nokids_GD_2534, kids_HS_2534, kids_SC_2534, kids_BAp_2534, kids_BAo_2534, kids_GD_2534, nokids_poor_2534, nokids_mid_2534, nokids_rich_2534, kids_poor_2534, kids_mid_2534, kids_rich_2534
17 rows
marriage/divorce
Unnamed: 0, year, date, all_3544, HS_3544, SC_3544, BAp_3544, BAo_3544, GD_3544, poor_3544, mid_3544, rich_3544, all_4554, HS_4554, SC_4554, BAp_4554, BAo_4554, GD_4554, poor_4554, mid_4554, rich_4554
17 rows
marriage/men
Unnamed: 0, year, date, all_2534, HS_2534, SC_2534, BAp_2534, BAo_2534, GD_2534, White_2534, Black_2534, Hisp_2534, NE_2534, MA_2534, Midwest_2534, South_2534, Mountain_2534, Pacific_2534, poor_2534, mid_2534, rich_2534, all_3544, HS_3544, SC_3544, BAp_3544, BAo_3544, GD_3544, White_3544, Black_3544, Hisp_3544, NE_3544, MA_3544, Midwest_3544, South_3544, Mountain_3544, Pacific_3544, poor_3544, mid_3544, rich_3544, all_4554, HS_4554, SC_4554, BAp_4554, BAo_4554, GD_4554, White_4554, Black_4554, Hisp_4554, NE_4554, MA_4554, Midwest_4554, South_4554, Mountain_4554, Pacific_4554, poor_4554, mid_4554, rich_4554, work_2534, nowork_2534, work_HS_2534, work_SC_2534, work_BAp_2534, work_BAo_2534, work_GD_2534, nowork_HS_2534, nowork_SC_2534, nowork_BAp_2534, nowork_BAo_2534, nowork_GD_2534, work_White_2534, work_Black_2534, work_Hisp_2534, nowork_White_2534, nowork_Black_2534, nowork_Hisp_2534, work_poor_2534, work_mid_2534, work_rich_2534, nowork_poor_2534, nowork_mid_2534, nowork_rich_2534, nokids_all_2534, kids_all_2534, nokids_HS_2534, nokids_SC_2534, nokids_BAp_2534, nokids_BAo_2534, nokids_GD_2534, kids_HS_2534, kids_SC_2534, kids_BAp_2534, kids_BAo_2534, kids_GD_2534, nokids_poor_2534, nokids_mid_2534, nokids_rich_2534, kids_poor_2534, kids_mid_2534, kids_rich_2534
17 rows
marriage/women
Unnamed: 0, year, date, all_2534, HS_2534, SC_2534, BAp_2534, BAo_2534, GD_2534, White_2534, Black_2534, Hisp_2534, NE_2534, MA_2534, Midwest_2534, South_2534, Mountain_2534, Pacific_2534, poor_2534, mid_2534, rich_2534, all_3544, HS_3544, SC_3544, BAp_3544, BAo_3544, GD_3544, White_3544, Black_3544, Hisp_3544, NE_3544, MA_3544, Midwest_3544, South_3544, Mountain_3544, Pacific_3544, poor_3544, mid_3544, rich_3544, all_4554, HS_4554, SC_4554, BAp_4554, BAo_4554, GD_4554, White_4554, Black_4554, Hisp_4554, NE_4554, MA_4554, Midwest_4554, South_4554, Mountain_4554, Pacific_4554, poor_4554, mid_4554, rich_4554, work_2534, nowork_2534, work_HS_2534, work_SC_2534, work_BAp_2534, work_BAo_2534, work_GD_2534, nowork_HS_2534, nowork_SC_2534, nowork_BAp_2534, nowork_BAo_2534, nowork_GD_2534, work_White_2534, work_Black_2534, work_Hisp_2534, nowork_White_2534, nowork_Black_2534, nowork_Hisp_2534, work_poor_2534, work_mid_2534, work_rich_2534, nowork_poor_2534, nowork_mid_2534, nowork_rich_2534, nokids_all_2534, kids_all_2534, nokids_HS_2534, nokids_SC_2534, nokids_BAp_2534, nokids_BAo_2534, nokids_GD_2534, kids_HS_2534, kids_SC_2534, kids_BAp_2534, kids_BAo_2534, kids_GD_2534, nokids_poor_2534, nokids_mid_2534, nokids_rich_2534, kids_poor_2534, kids_mid_2534, kids_rich_2534
17 rows
masculinity-survey/masculinity-survey
AMONG ADULT MEN, Unnamed: 1, Adult Men, Age, Unnamed: 4, Unnamed: 5, Race, Unnamed: 7, Children, Unnamed: 9, Sexual Orientation, Unnamed: 11
232 rows
masculinity-survey/raw-responses
Unnamed: 0, StartDate, EndDate, q0001, q0002, q0004_0001, q0004_0002, q0004_0003, q0004_0004, q0004_0005, q0004_0006, q0005, q0007_0001, q0007_0002, q0007_0003, q0007_0004, q0007_0005, q0007_0006, q0007_0007, q0007_0008, q0007_0009, q0007_0010, q0007_0011, q0008_0001, q0008_0002, q0008_0003, q0008_0004, q0008_0005, q0008_0006, q0008_0007, q0008_0008, q0008_0009, q0008_0010, q0008_0011, q0008_0012, q0009, q0010_0001, q0010_0002, q0010_0003, q0010_0004, q0010_0005, q0010_0006, q0010_0007, q0010_0008, q0011_0001, q0011_0002, q0011_0003, q0011_0004, q0011_0005, q0012_0001, q0012_0002, q0012_0003, q0012_0004, q0012_0005, q0012_0006, q0012_0007, q0013, q0014, q0015, q0017, q0018, q0019_0001, q0019_0002, q0019_0003, q0019_0004, q0019_0005, q0019_0006, q0019_0007, q0020_0001, q0020_0002, q0020_0003, q0020_0004, q0020_0005, q0020_0006, q0021_0001, q0021_0002, q0021_0003, q0021_0004, q0022, q0024, q0025_0001, q0025_0002, q0025_0003, q0026, q0028, q0029, q0030, q0034, q0035, q0036, race2, racethn4, educ3, educ4, age3, kids, orientation, weight
1,615 rows
media-mentions-2020/cable_weekly
date, name, matched_clips, all_candidate_clips, total_clips, pct_of_all_candidate_clips, query
1,008 rows
media-mentions-2020/online_weekly
date, name, matched_stories, all_candidate_stories, pct_of_all_candidate_stories, query
1,008 rows
mlb-allstar-teams/allstar_player_talent
bbref_ID, yearID, gameNum, gameID, lgID, startingPos, OFF600, DEF600, PITCH200, asg_PA, asg_IP, OFFper9innASG, DEFper9innASG, PITper9innASG, TOTper9innASG
3,930 rows
mlb-allstar-teams/allstar_team_talent
yearID, gameNum, gameID, lgID, tm_OFF_talent, tm_DEF_talent, tm_PIT_talent, MLB_avg_RPG, talent_RSPG, talent_RAPG, unadj_PYTH, timeline_adj, SOS, adj_PYTH, no_1_player, no_2_player
172 rows
mlb-quasi-win-shares/quasi_winshares
name_common, age, player_ID, year_ID, team_ID, lg_ID, pct_PT, WAR162, def_pos, quasi_ws, stint_ID, franch_id, prev_franch, year_acq, year_left, next_franch
98,796 rows
most-common-name/adjusted-name-combinations-list
Unnamed: 0, FirstName, Surname, Adjustment, cleanName, Estimate, finalEstimate
400 rows
most-common-name/adjusted-name-combinations-matrix
Unnamed: 0, FirstName, SMITH, JOHNSON, WILLIAMS, BROWN, JONES, GARCIA, RODRIGUEZ, MILLER, MARTINEZ, DAVIS, HERNANDEZ, LOPEZ, GONZALEZ, WILSON, ANDERSON, THOMAS, TAYLOR, LEE, MOORE, JACKSON
20 rows
most-common-name/adjustments
Unnamed: 0, Miller, Anderson, Martin, Smith, Thompson, Wilson, Moore, White, Taylor, Davis, Johnson, Brown, Jones, Thomas, Williams, Jackson, Lee, Garcia, Martinez, Rodriguez
20 rows
most-common-name/independent-name-combinations-by-pop
Unnamed: 0, SMITH, JOHNSON, WILLIAMS, BROWN, JONES, GARCIA, RODRIGUEZ, MILLER, MARTINEZ, DAVIS, HERNANDEZ, LOPEZ, GONZALEZ, WILSON, ANDERSON, THOMAS, TAYLOR, LEE, MOORE, JACKSON, PEREZ, MARTIN, THOMPSON, WHITE, SANCHEZ, HARRIS, RAMIREZ, CLARK, LEWIS, ROBINSON, WALKER, YOUNG, HALL, ALLEN, TORRES, NGUYEN, WRIGHT, FLORES, KING, SCOTT, RIVERA, GREEN, HILL, ADAMS, BAKER, NELSON, MITCHELL, CAMPBELL, GOMEZ, CARTER, ROBERTS, DIAZ, PHILLIPS, EVANS, TURNER, REYES, CRUZ, PARKER, EDWARDS, COLLINS, STEWART, MORRIS, MORALES, ORTIZ, GUTIERREZ, MURPHY, ROGERS, COOK, KIM, MORGAN, COOPER, RAMOS, PETERSON, GONZALES, BELL, REED, BAILEY, CHAVEZ, KELLY, HOWARD, RICHARDSON, WARD, COX, RUIZ, BROOKS, WATSON, WOOD, JAMES, MENDOZA, GRAY, BENNETT, ALVAREZ, CASTILLO, PRICE, HUGHES, VASQUEZ, SANDERS, JIMENEZ, LONG, FOSTER
100 rows
most-common-name/surnames
name, rank, count, prop100k, cum_prop100k, pctwhite, pctblack, pctapi, pctaian, pct2prace, pcthispanic
151,671 rows
mueller-polls/mueller-approval-polls
Start, End, Pollster, Sample Size, Population, Text, Approve, Disapprove, Unsure, Approve (Republican), Approve (Democrat), Url
65 rows
murder_2016/murder_2016_prelim
city, state, 2015_murders, 2016_murders, change, source, as_of
79 rows
nba-draft-2015/historical_projections
Player, Position, ID, Draft Year, Projected SPM, Superstar, Starter, Role Player, Bust
1,090 rows
nba-elo/nbaallelo
gameorder, game_id, lg_id, _iscopy, year_id, date_game, seasongame, is_playoffs, team_id, fran_id, pts, elo_i, elo_n, win_equiv, opp_id, opp_fran, opp_pts, opp_elo_i, opp_elo_n, game_location, game_result, forecast, notes
126,314 rows
nba-raptor/historical_RAPTOR_by_player
player_name, player_id, season, poss, mp, raptor_offense, raptor_defense, raptor_total, war_total, war_reg_season, war_playoffs, predator_offense, predator_defense, predator_total, pace_impact
18,553 rows
nba-raptor/historical_RAPTOR_by_team
player_name, player_id, season, season_type, team, poss, mp, raptor_offense, raptor_defense, raptor_total, war_total, war_reg_season, war_playoffs, predator_offense, predator_defense, predator_total, pace_impact
29,044 rows
nba-raptor/modern_RAPTOR_by_player
player_name, player_id, season, poss, mp, raptor_box_offense, raptor_box_defense, raptor_box_total, raptor_onoff_offense, raptor_onoff_defense, raptor_onoff_total, raptor_offense, raptor_defense, raptor_total, war_total, war_reg_season, war_playoffs, predator_offense, predator_defense, predator_total, pace_impact
4,079 rows
nba-raptor/modern_RAPTOR_by_team
player_name, player_id, season, season_type, team, poss, mp, raptor_box_offense, raptor_box_defense, raptor_box_total, raptor_onoff_offense, raptor_onoff_defense, raptor_onoff_total, raptor_offense, raptor_defense, raptor_total, war_total, war_reg_season, war_playoffs, predator_offense, predator_defense, predator_total, pace_impact
6,357 rows
ncaa-womens-basketball-tournament/ncaa-womens-basketball-tournament-history
Year, School, Seed, Conference, Conf. W, Conf. L, Conf. %, Conf. place, Reg. W, Reg. L, Reg. %, How qual, 1st game at home?, Tourney W, Tourney L, Tourney finish, Full W, Full L, Full %
2,092 rows
next-bechdel/nextBechdel_allTests
movie, bechdel, peirce, landau, feldman, villareal, hagen, ko, villarobos, waithe, koeze_dottle, uphold, white, rees-davies
50 rows
next-bechdel/nextBechdel_crewGender
MOVIE, DEPARTMENT, FULL_NAME, FIRST_NAME, IMDB, GENDER_PROB, GENDER_GUESS
10,029 rows
nfl-fandom/NFL_fandom_data-google_trends
Unnamed: 0, Pct. Of major sports searches, Unnamed: 2, Unnamed: 3, Unnamed: 4, Unnamed: 5, Unnamed: 6, Unnamed: 7, Unnamed: 8
208 rows
nfl-fandom/NFL_fandom_data-surveymonkey
Unnamed: 0, Unnamed: 1, Democrat, Unnamed: 3, Unnamed: 4, Unnamed: 5, Unnamed: 6, Unnamed: 7, Independent, Unnamed: 9, Unnamed: 10, Unnamed: 11, Unnamed: 12, Unnamed: 13, Republican, Unnamed: 15, Unnamed: 16, Unnamed: 17, Unnamed: 18, Unnamed: 19, Unnamed: 20, Unnamed: 21, Unnamed: 22, Unnamed: 23, Unnamed: 24
34 rows
nfl-favorite-team/team-picking-categories
TEAM, BMK, UNI, CCH, STX, SMK, AFF, SLP, NYP, FRL, BNG, TRD, BWG, FUT, PLA, OWN, BEH
32 rows
nfl-wide-receivers/advanced-historical
pfr_player_id, player_name, career_try, career_ranypa, career_wowy, bcs_rating
6,496 rows
non-voters/nonvoters_data
RespId, weight, Q1, Q2_1, Q2_2, Q2_3, Q2_4, Q2_5, Q2_6, Q2_7, Q2_8, Q2_9, Q2_10, Q3_1, Q3_2, Q3_3, Q3_4, Q3_5, Q3_6, Q4_1, Q4_2, Q4_3, Q4_4, Q4_5, Q4_6, Q5, Q6, Q7, Q8_1, Q8_2, Q8_3, Q8_4, Q8_5, Q8_6, Q8_7, Q8_8, Q8_9, Q9_1, Q9_2, Q9_3, Q9_4, Q10_1, Q10_2, Q10_3, Q10_4, Q11_1, Q11_2, Q11_3, Q11_4, Q11_5, Q11_6, Q14, Q15, Q16, Q17_1, Q17_2, Q17_3, Q17_4, Q18_1, Q18_2, Q18_3, Q18_4, Q18_5, Q18_6, Q18_7, Q18_8, Q18_9, Q18_10, Q19_1, Q19_2, Q19_3, Q19_4, Q19_5, Q19_6, Q19_7, Q19_8, Q19_9, Q19_10, Q20, Q21, Q22, Q23, Q24, Q25, Q26, Q27_1, Q27_2, Q27_3, Q27_4, Q27_5, Q27_6, Q28_1, Q28_2, Q28_3, Q28_4, Q28_5, Q28_6, Q28_7, Q28_8, Q29_1, Q29_2, Q29_3, Q29_4, Q29_5, Q29_6, Q29_7, Q29_8, Q29_9, Q29_10, Q30, Q31, Q32, Q33, ppage, educ, race, gender, income_cat, voter_category
5,836 rows
nutrition-studies/raw_anonymized_data
ID, cancer, diabetes, heart_disease, belly, ever_smoked, currently_smoke, smoke_often, smoke_rarely, never_smoked, quit_smoking, left_hand, right_hand, readingMath, mathReading, favCable, unfavCable, neutralCable, noCrash, yesCrash, uhCrash, rash, cat, dog, Dems, atheist, Jewish, BREAKFASTSANDWICHFREQ, BREAKFASTSANDWICHQUAN, EGGSFREQ, EGGSQUAN, YOGURTFREQ, YOGURTQUAN, COTTAGECHEESEFREQ, COTTAGECHEESEQUAN, CREAMCHEESEFREQ, CREAMCHEESEQUAN, SLICEDCHEESEFREQ, SLICEDCHEESEQUAN, COLDCEREALFREQ, COLDCEREALQUAN, WHOLEGRAINCEREALFREQ, WHOLEGRAINCEREALQUAN, GRITSFREQ, GRITSQUAN, MILKONCEREALFREQ, MILKONCEREALQUAN, BROWNRICEFREQ, BROWNRICEQUAN, WHITERICEFREQ, WHITERICEQUAN, PANCAKEFREQ, PANCAKEQUAN, PASTRIESFREQ, PASTRIESQUAN, BISCUITFREQ, BISCUITQUAN, CORNBREADFREQ, CORNBREADQUAN, BUNSFREQ, BUNSQUAN, BAGELFREQ, BAGELQUAN, TORTILLASFREQ, TORTILLASQUAN, OTHERBREADSFREQ, OTHERBREADSQUAN, BROCCOLIFREQ, BROCCOLIQUAN, CARROTSFREQ, CARROTSQUAN, CORNFREQ, CORNQUAN, GREENBEANSFREQ, GREENBEANSQUAN, COOKEDGREENSFREQ, COOKEDGREENSQUAN, CABBAGEFREQ, CABBAGEQUAN, GREENSALADFREQ, GREENSALADQUAN, RAWTOMATOESFREQ, RAWTOMATOESQUAN, SALADDRESSINGSFREQ, SALADDRESSINGSQUAN, AVOCADOFREQ, AVOCADOQUAN, SWEETPOTATOESFREQ, SWEETPOTATOESQUAN, FRIESFREQ, FRIESQUAN, POTATOESFREQ, POTATOESQUAN, OTHERVEGGIESFREQ, OTHERVEGGIESQUAN, MELONSFREQ, MELONSQUAN, BERRIESFREQ, BERRIESQUAN, BANANASFREQ, BANANASQUAN, APPLESFREQ, APPLESQUAN, ORANGESFREQ, ORANGESQUAN, PEACHESFREQ, PEACHESQUAN, OTHERFRESHFRUITFREQ, OTHERFRESHFRUITQUAN, DRIEDFRUITFREQ, DRIEDFRUITQUAN, CANNEDFRUITFREQ, CANNEDFRUITQUAN, REFRIEDBEANSFREQ, REFRIEDBEANSQUAN, BEANSFREQ, BEANSQUAN, TOFUFREQ, TOFUQUAN, MEATSUBSTITUTESFREQ, MEATSUBSTITUTESQUAN, LENTILSOUPFREQ, LENTILSOUPQUAN, VEGETABLESOUPFREQ, VEGETABLESOUPQUAN, OTHERSOUPFREQ, OTHERSOUPQUAN, PIZZAFREQ, PIZZAQUAN, MACANDCHEESEFREQ, MACANDCHEESEQUAN, SPAGHETTIFREQ, SPAGHETTIQUAN, OTHERNOODLESFREQ, OTHERNOODLESQUAN, EGGROLLFREQ, EGGROLLQUAN, EATMEAT, HAMBURGERFREQ, HAMBURGERQUAN, HOTDOGFREQ, 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GROUP_MAC_AND_CHEESE_CHEESE_DISHES_TOTAL_GRAMS, GROUP_SPAGHETTI_PASTA_WITH_TOMATO_SAUCE_TOTAL_GRAMS, GROUP_SPAGHETTI_MEATLESS_TOTAL_GRAMS, GROUP_SPAGHETTI_WITH_MEAT_TOTAL_GRAMS, GROUP_OTHER_NOODLES_PASTA_SOPA_SECA_TOTAL_GRAMS, GROUP_OTHER_NOODLES_WHITE_PASTA_TOTAL_GRAMS, GROUP_OTHER_NOODLES_PASTA_MIX_TOTAL_GRAMS, GROUP_OTHER_NOODLES_WHOLE_GRAIN_TOTAL_GRAMS, GROUP_EGG_ROLLS_WANTONS_DUMPLINGS_SAMOSAS_TOTAL_GRAMS, GROUP_BURGERS_GROUND_MEATS_TOTAL_GRAMS, GROUP_HAMBURGER_PATTY_TOTAL_GRAMS, GROUP_CHEESEBURGER_MEAT_AND_CHEESE_TOTAL_GRAMS, GROUP_TURKEY_BURGER_THE_MEAT_TOTAL_GRAMS, GROUP_HOT_DOG_DINNER_SAUSAGE_TOTAL_GRAMS, GROUP_HOT_DOG_BEEF_OR_PORK_TOTAL_GRAMS, GROUP_HOT_DOG_POULTRY_LOW_FAT_TOTAL_GRAMS, GROUP_SAUSAGE_BACON_TOTAL_GRAMS, GROUP_LUNCH_MEATS_TOTAL_GRAMS, GROUP_LUNCH_MEATS_BEEF_OR_PORK_TOTAL_GRAMS, GROUP_LUNCH_MEATS_POULTRY_LOW_FAT_TOTAL_GRAMS, GROUP_MEAT_LOAF_MEAT_BALLS_TOTAL_GRAMS, GROUP_STEAK_ROAST_TOTAL_GRAMS, GROUP_STEAK_ROAST_FAT_OFF_TOTAL_GRAMS, GROUP_STEAK_ROAST_FAT_ON_TOTAL_GRAMS, GROUP_TACOS_BURRITOS_ENCHILADAS_WITH_MEAT_TOTAL_GRAMS, GROUP_RIBS_SPARERIBS_BBQ_TOTAL_GRAMS, GROUP_PORK_CHOPS_ROAST_HAM_TOTAL_GRAMS, GROUP_PORK_FAT_OFF_TOTAL_GRAMS, GROUP_PORK_FAT_ON_TOTAL_GRAMS, GROUP_MIXED_DISH_WITH_BEEF_PORK_TOTAL_GRAMS, GROUP_LIVER_LIVERWURST_TOTAL_GRAMS, GROUP_FEET_NECK_TAIL_TONGUE_CHITLINS_TOTAL_GRAMS, GROUP_VEAL_LAMB_GOAT_GAME_TOTAL_GRAMS, GROUP_FRIED_OR_COATED_CHICKEN_TURKEY_TOTAL_GRAMS, GROUP_FRIED_OR_COATED_CHIX_NO_SKIN_TOTAL_GRAMS, GROUP_FRIED_OR_COATED_CHIX_ATE_SKIN_TOTAL_GRAMS, GROUP_FRIED_OR_COATED_CHIX_ATE_SKIN_SOMETIMES_TOTAL_GRAMS, GROUP_POULTRY_UNCOATED_TOTAL_GRAMS, GROUP_POULTRY_UNCOATED_NO_SKIN_TOTAL_GRAMS, GROUP_POULTRY_UNCOATED_ATE_SKIN_TOTAL_GRAMS, GROUP_POULTRY_UNCOATED_ATE_SKIN_SOMETIMES_TOTAL_GRAMS, GROUP_CHICKEN_OR_TURKEY_MIXED_DISH_TOTAL_GRAMS, GROUP_OYSTERS_TOTAL_GRAMS, GROUP_SHELLFISH_EXCEPT_OYSTERS_TOTAL_GRAMS, GROUP_TUNA_TUNA_IN_DISHES_TOTAL_GRAMS, GROUP_HIGH_OMEGA3_FISH_TOTAL_GRAMS, GROUP_FRIED_FISH_FISH_STICKS_SANDWICH_BREADED_FILLETS_TOTAL_GRAMS, GROUP_OTHER_FISH_DISHES_LOW_OMEGA3_TOTAL_GRAMS, GROUP_PEANUT_BUTTER_NUT_BUTTER_TOTAL_GRAMS, GROUP_WALNUTS_FLAX_SEEDS_TOTAL_GRAMS, GROUP_PEANUTS_OTHER_NUTS_SEEDS_TOTAL_GRAMS, GROUP_PROTEIN_ENERGY_BARS_TOTAL_GRAMS, GROUP_HIGH_ENERGY_BAR_TOTAL_GRAMS, GROUP_HIGH_PROTEIN_BAR_TOTAL_GRAMS, GROUP_CEREAL_GRANOLA_BARS_TOTAL_GRAMS, GROUP_POPCORN_TOTAL_GRAMS, GROUP_POPCORN_AIR_POP_FAT_FREE_TOTAL_GRAMS, GROUP_POPCORN_LOW_FAT_LIGHT_TOTAL_GRAMS, GROUP_POPCORN_REGULAR_TOTAL_GRAMS, GROUP_POPCORN_CARAMEL_TOTAL_GRAMS, GROUP_WHOLE_GRAIN_CRACKERS_TOTAL_GRAMS, GROUP_WHOLE_GRAIN_CRACKERS_LOW_FAT_TOTAL_GRAMS, GROUP_WHOLE_GRAIN_CRACKERS_REGULAR_TOTAL_GRAMS, GROUP_OTHER_CRACKERS_PRETZELS_NOT_WHOLEGRAIN_TOTAL_GRAMS, GROUP_OTHER_CRACKERS_PRETZELS_LOW_FAT_TOTAL_GRAMS, GROUP_OTHER_CRACKERS_FILLED_PRETZELS_REGULAR_TOTAL_GRAMS, GROUP_TORTILLA_OR_CORN_CHIPS_CORN_NUTS_TOTAL_GRAMS, GROUP_CORN_PUFFS_TWISTS_SOY_POTATO_CHIPS_TOTAL_GRAMS, GROUP_DONUTS_TOTAL_GRAMS, GROUP_CAKE_CUPCAKES_TOTAL_GRAMS, GROUP_CAKE_LOW_SUGAR_TOTAL_GRAMS, GROUP_CAKE_LOW_FAT_TOTAL_GRAMS, GROUP_CAKE_REGULAR_TOTAL_GRAMS, GROUP_COOKIES_BROWNIES_TOTAL_GRAMS, GROUP_COOKIES_LOW_SUGAR_TOTAL_GRAMS, GROUP_COOKIES_LOW_FAT_TOTAL_GRAMS, GROUP_COOKIES_REGULAR_TOTAL_GRAMS, GROUP_PUMPKIN_SWEET_POTATO_PIE_TOTAL_GRAMS, GROUP_OTHER_PIE_OR_COBBLER_TOTAL_GRAMS, GROUP_ICE_CREAM_FROZEN_YOGURT_TOTAL_GRAMS, GROUP_ICE_CREAM_LOW_SUGAR_TOTAL_GRAMS, GROUP_ICE_CREAM_FROZEN_YOGURT_LOW_FAT_TOTAL_GRAMS, GROUP_ICE_CREAM_REGULAR_TOTAL_GRAMS, GROUP_PUDDING_CUSTARD_FLAN_TOTAL_GRAMS, GROUP_CHOCOLATE_SAUCE_TOPPINGS_TOTAL_GRAMS, GROUP_POPSICLES_SHERBET_ICES_JELLO_TOTAL_GRAMS, GROUP_CHOCOLATE_CANDY_TOTAL_GRAMS, GROUP_CANDY_NOT_CHOCOLATE_TOTAL_GRAMS, GROUP_MARGARINE_AT_TABLE_TOTAL_GRAMS, GROUP_BUTTER_AT_TABLE_TOTAL_GRAMS, GROUP_MAYO_SANDWICH_SPREAD_TOTAL_GRAMS, GROUP_MAYO_LIGHT_LOW_FAT_TOTAL_GRAMS, GROUP_MAYO_REGULAR_TOTAL_GRAMS, GROUP_KETCHUP_SALSA_TOTAL_GRAMS, GROUP_MUSTARD_BBQ_SAUCE_SOY_SAUCE_ETC_TOTAL_GRAMS, GROUP_GRAVY_RICH_SAUCE_PEANUT_SAUCE_MOLE_TOTAL_GRAMS, GROUP_JAM_JELLY_MARMALADE_TOTAL_GRAMS, GROUP_PICKLES_SAUERKRAUT_KIMCHI_TOTAL_GRAMS, GROUP_TABLE_SALT_TOTAL_GRAMS, GROUP_CHOCOLATE_MILK_COCOA_HOT_CHOCOLATE_TOTAL_GRAMS, GROUP_MILK_AND_MILK_SUBSTITUTES_TOTAL_GRAMS, GROUP_WHOLE_MILK_4_PCT_FAT_TOTAL_GRAMS, GROUP_REDUCED_FAT_2_PCT_MILK_TOTAL_GRAMS, GROUP_LOW_FAT_1_PCT_MILK_TOTAL_GRAMS, GROUP_NON_FAT_SKIM_MILK_TOTAL_GRAMS, GROUP_SOY_MILK_TOTAL_GRAMS, GROUP_RICE_MILK_TOTAL_GRAMS, GROUP_OTHER_MILK_ALMOND_TOTAL_GRAMS, GROUP_MEAL_DRINKS_PROTEIN_DRINKS_TOTAL_GRAMS, GROUP_SLIM_FAST_TYPE_REGULAR_TOTAL_GRAMS, GROUP_SLIM_FAST_TYPE_LOW_CARB_TOTAL_GRAMS, GROUP_HIGH_PROTEIN_DRINKS_REGULAR_TOTAL_GRAMS, GROUP_HIGH_PROTEIN_DRINKS_LOW_CARB_TOTAL_GRAMS, GROUP_TOMATO_VEGETABLE_JUICE_TOTAL_GRAMS, GROUP_ORANGE_GRAPEFRUIT_JUICE_TOTAL_GRAMS, GROUP_OJ_CALCIUM_FORTIFIED_TOTAL_GRAMS, GROUP_OJ_GRAPEFRUIT_JUICE_NOT_CALCIUM_FORTIFIED_TOTAL_GRAMS, GROUP_OTHER_100_PCT_JUICE_AND_BLENDS_TOTAL_GRAMS, GROUP_HI_C_CRANBERRY_JUICE_TANG_TOTAL_GRAMS, GROUP_DRINKS_WITH_SOME_JUICE_TOTAL_GRAMS, GROUP_ICED_TEA_ALL_KINDS_TOTAL_GRAMS, GROUP_ICE_TEA_HOME_NO_SUGAR_TOTAL_GRAMS, GROUP_ICE_TEA_HOME_SUGAR_TOTAL_GRAMS, GROUP_ICE_TEA_BOTTLE_NO_SUGAR_TOTAL_GRAMS, GROUP_ICE_TEA_BOTTLE_SUGAR_TOTAL_GRAMS, GROUP_GATORADE_POWERADE_TOTAL_GRAMS, GROUP_ENERGY_DRINKS_TOTAL_GRAMS, GROUP_ENERGY_DRINKS_LOW_SUGAR_TOTAL_GRAMS, GROUP_ENERGY_DRINKS_SUGAR_TOTAL_GRAMS, GROUP_KOOLAID_HORCHATA_TOTAL_GRAMS, GROUP_LOW_CAL_KOOLAID_TOTAL_GRAMS, GROUP_REGULAR_KOOLAID_TOTAL_GRAMS, GROUP_SODA_OR_POP_TOTAL_GRAMS, GROUP_SODA_DIET_NO_CAFFEINE_TOTAL_GRAMS, GROUP_SODA_DIET_CAFFEINE_TOTAL_GRAMS, GROUP_SODA_SUGAR_NO_CAFFEINE_TOTAL_GRAMS, GROUP_SODA_SUGAR_CAFFEINE_TOTAL_GRAMS, GROUP_SODA_DIET_UNSURE_CAFFEINE_TOTAL_GRAMS, GROUP_SODA_SUGAR_UNSURE_CAFFEINE_TOTAL_GRAMS, GROUP_SODA_DECAF_UNSURE_SUGAR_TOTAL_GRAMS, GROUP_SODA_CAFFEINE_UNSURE_SUGAR_TOTAL_GRAMS, GROUP_BEER_ANY_KIND_TOTAL_GRAMS, GROUP_BEER_REGULAR_TOTAL_GRAMS, GROUP_BEER_LIGHT_LOW_CARB_TOTAL_GRAMS, GROUP_BEER_NON_ALCOHOLIC_TOTAL_GRAMS, GROUP_WINE_WINE_COOLERS_ALL_KINDS_TOTAL_GRAMS, GROUP_WINE_RED_TOTAL_GRAMS, GROUP_WINE_WHITE_TOTAL_GRAMS, GROUP_BOTH_RED_AND_WHITE_WINE_TOTAL_GRAMS, GROUP_LIQUOR_COCKTAILS_TOTAL_GRAMS, GROUP_WATER_BOTTLED_OR_TAP_TOTAL_GRAMS, GROUP_MILKY_COFFEE_DRINK_ANY_KIND_TOTAL_GRAMS, GROUP_LATTE_CAPPUCCINO_1_PCT_OR_2_PCT_MILK_TOTAL_GRAMS, GROUP_LATTE_CAPPUCCINO_WHOLE_MILK_TOTAL_GRAMS, GROUP_LATTE_CAPPUCCINO_NON_FAT_MILK_TOTAL_GRAMS, GROUP_LATTE_CAPPUCCINO_SOY_MILK_TOTAL_GRAMS, GROUP_LATTE_CAPPUCCINO_SOMETHING_ELSE_TOTAL_GRAMS, GROUP_CAFE_LECHE_1_PCT_OR_2_PCT_MILK_TOTAL_GRAMS, GROUP_CAFE_LECHE_WHOLE_MILK_TOTAL_GRAMS, GROUP_CAFE_LECHE_NON_FAT_MILK_TOTAL_GRAMS, GROUP_CAFE_LECHE_SOY_MILK_TOTAL_GRAMS, GROUP_CAFE_LECHE_SOMETHING_ELSE_TOTAL_GRAMS, GROUP_MOCHA_1_PCT_OR_2_PCT_MILK_TOTAL_GRAMS, GROUP_MOCHA_WHOLE_MILK_TOTAL_GRAMS, GROUP_MOCHA_NON_FAT_MILK_TOTAL_GRAMS, GROUP_MOCHA_SOY_MILK_TOTAL_GRAMS, GROUP_MOCHA_SOMETHING_ELSE_TOTAL_GRAMS, GROUP_FRAPPUCCINO_1_PCT_OR_2_PCT_MILK_TOTAL_GRAMS, GROUP_FRAPPUCCINO_WHOLE_MILK_TOTAL_GRAMS, GROUP_FRAPPUCCINO_NON_FAT_MILK_TOTAL_GRAMS, GROUP_FRAPPUCCINO_SOY_MILK_TOTAL_GRAMS, GROUP_FRAPPUCCINO_SOMETHING_ELSE_TOTAL_GRAMS, GROUP_COFFEE_DECAF_TOTAL_GRAMS, GROUP_COFFEE_CAFFEINE_TOTAL_GRAMS, GROUP_COFFEE_BOTH_KINDS_TOTAL_GRAMS, GROUP_COFFEE_DONT_DRINK_TOTAL_GRAMS, GROUP_HOT_TEA_DECAF_TOTAL_GRAMS, GROUP_HOT_TEA_CAFFEINE_TOTAL_GRAMS, GROUP_HOT_TEA_BOTH_KINDS_TOTAL_GRAMS, GROUP_HOT_TEA_DONT_DRINK_TOTAL_GRAMS, GROUP_CREAM_OR_HALF_N_HALF_TOTAL_GRAMS, GROUP_NON_DAIRY_CREAMER_LIQUID_TOTAL_GRAMS, GROUP_CONDENSED_MILK_TOTAL_GRAMS, GROUP_SUGAR_OR_HONEY_TOTAL_GRAMS, GROUP_COOKING_FAT_POP_MIX_TOTAL_GRAMS, GROUP_NON_STICK_SPRAY_SR27_TOTAL_GRAMS, GROUP_COOK_FAT_BUTTER_OR_GHEE_TOTAL_GRAMS, GROUP_COOK_FAT_BUTTER_MARGARINE_BLEND_TOTAL_GRAMS, GROUP_COOK_FAT_MARGARINE_STICK_TOTAL_GRAMS, GROUP_COOK_FAT_MARGARINE_TUB_TOTAL_GRAMS, GROUP_COOK_FAT_MARGARINE_LOW_FAT_TOTAL_GRAMS, GROUP_COOK_FAT_OLIVE_OIL_TOTAL_GRAMS, GROUP_COOK_FAT_CANOLA_SAFFLOWER_OILS_TOTAL_GRAMS, GROUP_COOK_FAT_CORN_VEGETABLE_OIL_BLENDS_TOTAL_GRAMS, GROUP_COOK_FAT_PEANUT_OIL_TOTAL_GRAMS, GROUP_COOK_FAT_ANIMAL_FAT_TOTAL_GRAMS, GROUP_COOK_FAT_VEG_SHORTENING_CRISCO_TOTAL_GRAMS, GROUP_COOK_FAT_OTHER_OIL_COCONUT_VARIOUS_NFS_VEGETABLE_OILS_TOTAL_GRAMS, ASH, SUCS, GLUS, FRUS, LACS, MALS, GALS, STARCH, MN, FLD, NIACIN_EQUIV_NE, PANTAC, B_CAROTENE_EQUIV, VITA_IU, TOCPHB, TOCPHG, TOCPHD, TOCTRA, TOCTRB, TOCTRG, TOCTRD, ERGCAL, CHOCAL, VITD_IU, VITE_IU, VITK1D, MK4, F13D0, F15D0, F17D0, F20D0, F22D0, F24D0, F14D1, F15D1, F16D1C, F17D1, F18D1C, F22D1C, F24D1C, F18D2CN6, F18D2CLA, F18D2I, F18D3CN3, F18D3CN6, F18D3I, F20D2CN6, F20D3, F20D3N3, F20D3N6, F20D4N6, F21D5, F22D4, F16D1T, F18D1T, F18D1TN7, F22D1T, F18D2TT, F18D2T, FATRNM, FATRNP, PHYSTR, STID7, CAMD5, SITSTR, TRP_G, THR_G, ILE_G, LEU_G, LYS_G, MET_G, CYS_G, PHE_G, TYR_G, VAL_G, ARG_G, HISTN_G, ALA_G, ASP_G, GLU_G, GLY_G, PRO_G, SER_G, HYP, PAC_1, PAC_2, PAC_3, PAC_4, PAC_7, PAC10, BETN_C, CHOLNFR, CHOLNGPC, CHOLNPC, CHOLNPTC, CHOLNSM, DT_FIBER_INSOL, DT_FIBER_SOL, DT_PROT_ANIMAL, DT_PROT_VEGETABLE, DT_NITROGEN, PHYTIC_ACID, OXALIC_ACID, COUMESTROL, BIOCHANIN_A, FORMONONETIN
54 rows
pew-religions/current
0.00719424460432, 0.213771839671, 0.261048304214, 0.00719424460432.1, 0.0668036998972, 0.0082219938335, 0.0195272353546, 0.151079136691, 0.016443987667, 0.00924974306269, 0.00513874614594, 0.234326824255
100 rows
police-deaths/clean_data
person, dept, eow, cause, cause_short, date, year, canine, dept_name, state
22,800 rows
police-killings/police_killings
name, age, gender, raceethnicity, month, day, year, streetaddress, city, state, latitude, longitude, state_fp, county_fp, tract_ce, geo_id, county_id, namelsad, lawenforcementagency, cause, armed, pop, share_white, share_black, share_hispanic, p_income, h_income, county_income, comp_income, county_bucket, nat_bucket, pov, urate, college
467 rows
police-locals/police-locals
city, police_force_size, all, white, non-white, black, hispanic, asian
75 rows
poll-quiz-guns/guns-polls
Question, Start, End, Pollster, Population, Support, Republican Support, Democratic Support, URL
57 rows
polls/pres_pollaverages_1968-2016
cycle, state, modeldate, candidate_name, candidate_id, pct_estimate, pct_trend_adjusted, timestamp, comment, election_date, election_qdate, last_qdate, last_enddate, _medpoly2, trend_medpoly2, _shortpoly0, trend_shortpoly0, sum_weight_medium, sum_weight_short, sum_influence, sum_nat_influence, _minpoints, _defaultbasetime, _numloops, _state_houseeffects_weight, _state_trendline_weight, _out_of_state_house_discount, _house_effects_multiplier, _attenuate_endpoints, _nonlinear_polynomial_degree, _shortpoly_combpoly_weight, _nat_shortpoly_combpoly_weight
217,473 rows
polls/pres_primary_avgs_1980-2016
race, state, modeldate, candidate_name, candidate_id, pct_estimate, pct_trend_adjusted, timestamp, comment, contestdate
301,695 rows
pollster-ratings/2016/pollster-ratings
ID, Pollster, Polls, Live Caller With Cellphones, Internet, NCPP/AAPOR/Roper, Polls.1, Simple Average Error, Races Called Correctly, Advanced Plus-Minus, Predictive Plus-Minus, 538 Grade, Banned by 538, Mean-Reverted Bias
372 rows
pollster-ratings/2016/raw-polls
pollno, race, year, location, type_simple, type_detail, pollster, partisan, polldate, samplesize, cand1_name, cand1_pct, cand2_name, cand2_pct, cand3_pct, margin_poll, electiondate, cand1_actual, cand2_actual, margin_actual, error, bias, rightcall, comment
7,977 rows
pollster-ratings/2018/pollster-ratings
Pollster, # of Polls, NCPP / AAPOR / Roper, Exclusively Live Caller With Cellphones, Methodology, Banned by 538, Historical Advanced Plus-Minus, Predictive Plus-Minus, 538 Grade, Mean-Reverted Bias, Races Called Correctly, Misses Outside MOE, Simple Average Error, Simple Expected Error, Simple Plus-Minus, Advanced Plus-Minus, Mean-Reverted Advanced Plus Minus, Predictive Plus-Minus, # of Polls for Bias Analysis, Bias, Mean-Reverted Bias.1, House Effect
396 rows
pollster-ratings/2018/raw-polls
pollno, race, year, location, type_simple, type_detail, pollster, partisan, polldate, samplesize, cand1_name, cand1_pct, cand2_name, cand2_pct, cand3_pct, margin_poll, electiondate, cand1_actual, cand2_actual, margin_actual, error, bias, rightcall, comment
8,512 rows
pollster-ratings/2019/pollster-ratings
Pollster, Pollster Rating ID, # of Polls, NCPP / AAPOR / Roper, Live Caller With Cellphones, Methodology, Banned by 538, Historical Advanced Plus-Minus, Predictive Plus-Minus, 538 Grade, Mean-Reverted Bias, Races Called Correctly, Misses Outside MOE, Simple Average Error, Simple Expected Error, Simple Plus-Minus, Advanced Plus-Minus, Mean-Reverted Advanced Plus Minus, Predictive Plus-Minus, # of Polls for Bias Analysis, Bias, Mean-Reverted Bias.1, House Effect, Average Distance from Polling Average (ADPA), Herding Penalty
430 rows
pollster-ratings/2019/raw-polls
pollno, race, year, location, type_simple, type_detail, pollster, pollster_rating_id, polldate, samplesize, cand1_name, cand1_pct, cand2_name, cand2_pct, cand3_pct, margin_poll, electiondate, cand1_actual, cand2_actual, margin_actual, error, bias, rightcall, comment, partisan
9,133 rows
pollster-ratings/2020/pollster-ratings
Pollster, Pollster Rating ID, # of Polls, NCPP / AAPOR / Roper, Live Caller With Cellphones, Methodology, Banned by 538, Predictive Plus-Minus, 538 Grade, Mean-Reverted Bias, Races Called Correctly, Misses Outside MOE, Simple Average Error, Simple Expected Error, Simple Plus-Minus, Advanced Plus-Minus, Mean-Reverted Advanced Plus Minus, # of Polls for Bias Analysis, Bias, House Effect, Average Distance from Polling Average (ADPA), Herding Penalty, latest_poll
453 rows
pollster-ratings/2020/raw-polls
poll_id, question_id, race_id, year, race, location, type_simple, type_detail, pollster, pollster_rating_id, polldate, samplesize, cand1_name, cand1_party, cand1_pct, cand2_name, cand2_party, cand2_pct, cand3_pct, margin_poll, electiondate, cand1_actual, cand2_actual, margin_actual, error, bias, rightcall, comment, partisan
9,559 rows
pollster-ratings/pollster-ratings
Rank, Pollster, Pollster Rating ID, Polls Analyzed, NCPP/AAPOR/Roper, Banned by 538, Predictive Plus-Minus, 538 Grade, Mean-Reverted Bias, Races Called Correctly, Misses Outside MOE, Simple Average Error, Simple Expected Error, Simple Plus-Minus, Advanced Plus-Minus, Mean-Reverted Advanced Plus Minus, # of Polls for Bias Analysis, Bias, House Effect, Average Distance from Polling Average (ADPA), Herding Penalty
493 rows
pollster-ratings/raw-polls
poll_id, question_id, race_id, year, race, location, type_simple, type_detail, pollster, pollster_rating_id, methodology, partisan, polldate, samplesize, cand1_name, cand1_id, cand1_party, cand1_pct, cand2_name, cand2_id, cand2_party, cand2_pct, cand3_pct, margin_poll, electiondate, cand1_actual, cand2_actual, margin_actual, error, bias, rightcall, advancedplusminus, comment
10,776 rows
potential-candidates/2015_01_14/events
Person, Party, State, Event, Type, Date, Link, Snippet
42 rows
potential-candidates/2015_01_14/statements
Person, Party, Statement Date, Latest Statement, Statement Score
25 rows
potential-candidates/2015_01_30/events
Person, Party, State, Event, Type, Date, Link, Snippet
74 rows
potential-candidates/2015_01_30/statements
Person, Party, Statement Date, Latest Statement, Statement Score
27 rows
presidential-candidate-favorables-2019/favorability_polls_rv_2019
question_id, start_date, end_date, pollster_id, pollster, sponsors, sample_size, population, methodology, url, politician, favorable, unfavorable, very_favorable, somewhat_favorable, somewhat_unfavorable, very_unfavorable
1,631 rows
presidential-commencement-speeches/commencement_speeches
president, president_name, title, date, city, state, building, room
154 rows
primary-candidates-2018/dem_candidates
Candidate, State, District, Office Type, Race Type, Race Primary Election Date, Primary Status, Primary Runoff Status, General Status, Partisan Lean, Primary %, Won Primary, Race, Veteran?, LGBTQ?, Elected Official?, Self-Funder?, STEM?, Obama Alum?, Party Support?, Emily Endorsed?, Guns Sense Candidate?, Biden Endorsed?, Warren Endorsed? , Sanders Endorsed?, Our Revolution Endorsed?, Justice Dems Endorsed?, PCCC Endorsed?, Indivisible Endorsed?, WFP Endorsed?, VoteVets Endorsed?, No Labels Support?
811 rows
primary-candidates-2018/rep_candidates
Candidate, State, District, Office Type, Race Type, Race Primary Election Date, Primary Status, Primary Runoff Status, General Status, Primary %, Won Primary, Rep Party Support?, Trump Endorsed?, Bannon Endorsed?, Great America Endorsed?, NRA Endorsed?, Right to Life Endorsed?, Susan B. Anthony Endorsed?, Club for Growth Endorsed?, Koch Support?, House Freedom Support?, Tea Party Endorsed?, Main Street Endorsed?, Chamber Endorsed?, No Labels Support?
774 rows
puerto-rico-media/google_trends
Day, "Hurricane Harvey": (United States), "Hurricane Irma": (United States), "Hurricane Maria": (United States), "Hurricane Jose": (United States)
37 rows
puerto-rico-media/mediacloud_trump
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
pulitzer/pulitzer-circulation-data
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
rare-pepes/ordermatches_all
Block, ForwardAsset, ForwardQuantity, BackwardAsset, BackwardQuantity
26,038 rows
redistricting-2022-state-legislatures/fivethirtyeight_state_legislative_district_analysis
year, state, chamber, district, metric, value, pct
56,023 rows
redlining/metro-grades
metro_area, holc_grade, white_pop, black_pop, hisp_pop, asian_pop, other_pop, total_pop, pct_white, pct_black, pct_hisp, pct_asian, pct_other, lq_white, lq_black, lq_hisp, lq_asian, lq_other, surr_area_white_pop, surr_area_black_pop, surr_area_hisp_pop, surr_area_asian_pop, surr_area_other_pop, surr_area_pct_white, surr_area_pct_black, surr_area_pct_hisp, surr_area_pct_asian, surr_area_pct_other
551 rows
redlining/zone-block-matches
holc_city, holc_state, holc_grade, holc_id, holc_neighborhood_id, block_geoid20, pct_match
752,351 rows
region-survey/MIDWEST
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, Unnamed: 9, Unnamed: 10, Unnamed: 11, Unnamed: 12, Unnamed: 13, Unnamed: 14, Unnamed: 15, Unnamed: 16, Unnamed: 17, Unnamed: 18, Unnamed: 19, Unnamed: 20, Unnamed: 21, Unnamed: 22, Unnamed: 23, Unnamed: 24, Unnamed: 25, In what ZIP code is your home located? (enter 5-digit ZIP code; for example, 00544 or 94305), Gender, Unnamed: 28, Age, Unnamed: 30, Unnamed: 31, Unnamed: 32, Unnamed: 33, Household Income, Unnamed: 35, Unnamed: 36, Unnamed: 37, Unnamed: 38, Education, Unnamed: 40, Unnamed: 41, Unnamed: 42, Unnamed: 43, Location (Census Region), Unnamed: 45, Unnamed: 46, Unnamed: 47, Unnamed: 48, Unnamed: 49, Unnamed: 50, Unnamed: 51, Unnamed: 52
2,779 rows
region-survey/SOUTH
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, Unnamed: 9, Unnamed: 10, Unnamed: 11, Unnamed: 12, Unnamed: 13, Unnamed: 14, Unnamed: 15, Unnamed: 16, Unnamed: 17, Unnamed: 18, Unnamed: 19, Unnamed: 20, Unnamed: 21, Unnamed: 22, Unnamed: 23, Unnamed: 24, Unnamed: 25, Unnamed: 26, Unnamed: 27, Unnamed: 28, Unnamed: 29, Unnamed: 30, In what ZIP code is your home located? (enter 5-digit ZIP code; for example, 00544 or 94305), Gender, Unnamed: 33, Age, Unnamed: 35, Unnamed: 36, Unnamed: 37, Unnamed: 38, Household Income, Unnamed: 40, Unnamed: 41, Unnamed: 42, Unnamed: 43, Education, Unnamed: 45, Unnamed: 46, Unnamed: 47, Unnamed: 48, Location (Census Region), Unnamed: 50, Unnamed: 51, Unnamed: 52, Unnamed: 53, Unnamed: 54, Unnamed: 55, Unnamed: 56, Unnamed: 57
2,529 rows
religion-survey/religion-survey-results
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, How often do you: Bring up your religion, unprompted, in conversation, How often do you: Ask others about their religion, unprompted, in conversation, How often do you: Decline some kind of food or beverage for religious reasons (kosher, halal, fasting rules, etc), How often do you: Wear religious clothing/jewelry (hijab, kippah, wig, kara, turban, cross, etc), How often do you: Participate in a public religious event on the streets (Corpus Christi procession, inauguration of Torah scrolls, etc), How comfortable do you feel when you: Pray in public with visible motions (sign of the cross, bowing, prostration, shokeling, etc), How comfortable do you feel when you: Pray in public using some kind of physical object (rosary, tefillin, etc), How comfortable do you feel when you: Pray aloud before meals in the presence of people who don't belong to your religion, How comfortable do you feel when you: Tell someone you'll pray for him or her, How comfortable do you feel when you: Ask or offer to pray with someone, How comfortable do you feel when you: Bring up your religion, unprompted, in conversation, How comfortable do you feel when you: Ask others about their religion, unprompted, in conversation, How comfortable do you feel when you: Decline some kind of food or beverage for religious reasons (kosher, halal, fasting rules, etc), How comfortable do you feel when you: Wear religious clothing/jewelry (hijab, kippah, wig, kara, turban, cross, etc), How comfortable do you feel when you: Participate in a public religious event on the streets (Corpus Christi procession, inauguration of Torah scrolls, etc), How comfortable do you think someone outside your religion would be if they saw you: Pray in public with visible motions (sign of the cross, bowing, prostration, shokeling, etc), How comfortable do you think someone outside your religion would be if they saw you: Pray in public using some kind of physical object (rosary, tefillin, etc), How comfortable do you think someone outside your religion would be if they saw you: Pray aloud before meals in the presence of people who don't belong to your religion, How comfortable do you think someone outside your religion would be if they saw you: Tell someone you'll pray for him or her, How comfortable do you think someone outside your religion would be if they saw you: Ask or offer to pray with someone, How comfortable do you think someone outside your religion would be if they saw you: Bring up your religion, unprompted, in conversation, How comfortable do you think someone outside your religion would be if they saw you: Ask others about their religion, unprompted, in conversation, How comfortable do you think someone outside your religion would be if they saw you: Decline some kind of food or beverage for religious reasons (kosher, halal, fasting rules, etc), How comfortable do you think someone outside your religion would be if they saw you: Wear religious clothing/jewelry (hijab, kippah, wig, kara, turban, cross, etc), How comfortable do you think someone outside your religion would be if they saw you: Participate in a public religious event on the streets (Corpus Christi procession, inauguration of Torah scrolls, etc), How comfortable would you be seeing someone who practices a different religion from you: Pray in public with visible motions (sign of the cross, bowing, prostration, shokeling, etc), How comfortable would you be seeing someone who practices a different religion from you: Pray in public using some kind of physical object (rosary, tefillin, etc), How comfortable would you be seeing someone who practices a different religion from you: Pray aloud before meals in the presence of people who don't belong to that religion, How comfortable would you be seeing someone who practices a different religion from you: Tell someone "I'll pray for you", How comfortable would you be seeing someone who practices a different religion from you: Ask or offer to pray with you, How comfortable would you be seeing someone who practices a different religion from you: Bring up his or her own religion, unprompted, in conversation, How comfortable would you be seeing someone who practices a different religion from you: Ask you about your religion, unprompted, in conversation, How comfortable would you be seeing someone who practices a different religion from you: Decline some kind of food or beverage for religious reasons (kosher, halal, fasting rules, etc), How comfortable would you be seeing someone who practices a different religion from you: Wear religious clothing/jewelry (hijab, kippah, wig, kara, turban, cross, etc), How comfortable would you be seeing someone who practices a different religion from you: Participate in a public religious event on the streets (Corpus Christi procession, inauguration of Torah scrolls, etc), What is your age?, What is your gender?, How much total combined money did all members of your HOUSEHOLD earn last year?, US Region
1,040 rows
reluctant-trump/february_2018_rawdata
q1, issue_matters_most, trump_approval, q4, q5, q6, q7, q8, q9, q10, q11, q12, q13, q14, q15, new_who_vote_for_in_election, q17, q18, q19, q20, registered_voter, ideology, party_id, party_lean, gender, race, education, state, zip_code, q30, age, race2, racethn4, educ3, educ4, region, division, age6, q39, party5, q41, q42, q43, q44, q45, q46, q47, q48, q49, q50, q51, q52, q53, q54, q55, q56, q57, q58, q59, q60, q61, q62, q63, q64, weight, filter__
7,169 rows
riddler-castles/castle-solutions
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9, Castle 10, Why did you choose your troop deployment?
1,387 rows
riddler-castles/castle-solutions-2
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9, Castle 10, Why did you choose your troop deployment?
932 rows
riddler-castles/castle-solutions-3
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9, Castle 10, Why did you choose your troop deployment?
1,466 rows
riddler-castles/castle-solutions-4
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9, Castle 10
1,013 rows
riddler-castles/castle-solutions-5
Castle 1, Castle 2, Castle 3, Castle 4, Castle 5, Castle 6, Castle 7, Castle 8, Castle 9, Castle 10, Castle 11, Castle 12, Castle 13
963 rows
russia-investigation/russia-investigation
investigation, investigation-start, investigation-end, investigation-days, name, indictment-days , type, cp-date, cp-days, overturned, pardoned, american, president
194 rows
san-andreas/earthquake_data
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?, How much total combined money did all members of your HOUSEHOLD earn last year?, US Region
1,013 rows
sandy-311-calls/sandy-311-calls-by-day
date, NYC-3-1-1, ACS, BPSI, CAU, CHALL, DEP, DOB, DOE, DOF, DOHMH, DPR, FEMA, HPD, HRA, MFANYC, MOSE, NYCEM, NYCHA, NYCSERVICE, NYPD, NYSDOL, SBS, NYSEMERGENCYMG, total
1,783 rows
sleeping-alone-data/sleeping-alone-data
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, What are the reasons that you sleep in separate beds? Please select all that apply., Unnamed: 10, Unnamed: 11, Unnamed: 12, Unnamed: 13, Unnamed: 14, Unnamed: 15, Unnamed: 16, Unnamed: 17, Unnamed: 18, Unnamed: 19, When was the first time you slept in separate beds?, To what extent do you agree with the following statement: "sleeping in separate beds helps us to stay together.", To what extent do you agree with the following statement: "we sleep better when we sleep in separate beds.", To what extent do you agree with the following statement:ë_"our sex life has improved as a result of sleeping in separate beds."ë_, Which of the following best describes your current occupation?, Unnamed: 25, Gender, Age, Household Income, Education, Location (Census Region)
1,094 rows
special-elections/special-elections
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
sports-political-donations/sports-political-donations
Owner, Team, League, Recipient, Amount, Election Year, Party
2,798 rows
star-wars-survey/StarWars
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, Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film., Unnamed: 10, Unnamed: 11, Unnamed: 12, Unnamed: 13, Unnamed: 14, Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her., Unnamed: 16, Unnamed: 17, Unnamed: 18, Unnamed: 19, Unnamed: 20, Unnamed: 21, Unnamed: 22, Unnamed: 23, Unnamed: 24, Unnamed: 25, Unnamed: 26, Unnamed: 27, Unnamed: 28, Which character shot first?, Are you familiar with the Expanded Universe?, Do you consider yourself to be a fan of the Expanded Universe?æ, Do you consider yourself to be a fan of the Star Trek franchise?, Gender, Age, Household Income, Education, Location (Census Region)
1,187 rows
state-of-the-state/words
phrase, category, d_speeches, r_speeches, total, percent_of_d_speeches, percent_of_r_speeches, chi2, pval
2,223 rows
steak-survey/steak-risk-survey
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?, How do you like your steak prepared?, Gender, Age, Household Income, Education, Location (Census Region)
551 rows
tennis-time/serve_times
server, seconds_before_next_point, day, opponent, game_score, set, game
120 rows
tenth-circuit/tenth-circuit
Title, Date, Federal Reporter Citation, Westlaw Citation, Issue, Weight, Judge1, Judge2, Judge3, Vote1, Vote2, Vote3, Category
954 rows
terrorism/country_stats_1993_appendix2
Country, Number of Incidents, Percent, Number Killed, Number Injured, Number US Killed, Number US Injured
129 rows
terrorism/eu_terrorism_fatalities_by_country
iyear, Belgium, Denmark, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, United Kingdom
45 rows
thanksgiving-2015/thanksgiving-2015-poll-data
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?, What type of cranberry saucedo you typically have? - Other (please specify), Do you typically have gravy?, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Brussel sprouts, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Carrots, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Cauliflower, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Corn, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Cornbread, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Fruit salad, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Green beans/green bean casserole, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Macaroni and cheese, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Mashed potatoes, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Rolls/biscuits, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Squash, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Vegetable salad, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Yams/sweet potato casserole, Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify), Which of these side dishes aretypically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify).1, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Apple, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Buttermilk, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Cherry, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Chocolate, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Coconut cream, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Key lime, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Peach, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Pecan, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Pumpkin, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Sweet Potato, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - None, Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify), Which type of pie is typically served at your Thanksgiving dinner? Please select all that apply. - Other (please specify).1, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Apple cobbler, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Blondies, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Brownies, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Carrot cake, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Cheesecake, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Cookies, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Fudge, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Ice cream, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Peach cobbler, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - None, Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Other (please specify), Which of these desserts do you typically have at Thanksgiving dinner? Please select all that apply. - Other (please specify).1, Do you typically pray before or after the Thanksgiving meal?, How far will you travel for Thanksgiving?, Will you watch any of the following programs on Thanksgiving? Please select all that apply. - Macy's Parade, What's the age cutoff at your "kids' table" at Thanksgiving?, Have you ever tried to meet up with hometown friends on Thanksgiving night?, Have you ever attended a "Friendsgiving?", Will you shop any Black Friday sales on Thanksgiving Day?, Do you work in retail?, Will you employer make you work on Black Friday?, How would you describe where you live?, Age, What is your gender?, How much total combined money did all members of your HOUSEHOLD earn last year?, US Region
1,058 rows
trump-lawsuits/trump-lawsuits
docketNumber, dateFiled, caseName, plaintiff, defendant, currentLocation, previousLocation, jurisdiction, judge, nature, TrumpCategory, capacity, type, issue, docketOrig, status
57 rows
trump-world-trust/TRUMPWORLD-pres
year, avg, Canada, France, Germany, Greece, Hungary, Italy, Netherlands, Poland, Spain, Sweden, UK, Russia, Australia, India, Indonesia, Japan, Philippines, South Korea, Vietnam, Israel, Jordan, Lebanon, Tunisia, Turkey, Ghana, Kenya, Nigeria, Senegal, South Africa, Tanzania, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela
15 rows
trump-world-trust/TRUMPWORLD-us
year, avg, Canada, France, Germany, Greece, Hungary, Italy, Netherlands, Poland, Spain, Sweden, UK, Russia, Australia, India, Indonesia, Japan, Philippines, South Korea, Vietnam, Israel, Jordan, Lebanon, Tunisia, Turkey, Ghana, Kenya, Nigeria, Senegal, South Africa, Tanzania, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela
17 rows
twitter-ratio/senators
created_at, text, url, replies, retweets, favorites, user, bioguide_id, party, state
288,615 rows
urbanization-index/urbanization-census-tract
statefips, state, gisjoin, lat_tract, long_tract, population, adj_radiuspop_5, urbanindex
73,280 rows
us-weather-history/KCLT
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KCQT
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KHOU
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KIND
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KJAX
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KMDW
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KNYC
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KPHL
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KPHX
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
us-weather-history/KSEA
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, record_max_temp_year, actual_precipitation, average_precipitation, record_precipitation
365 rows
voter-registration/new-voter-registrations
Jurisdiction, Year, Month, New registered voters
106 rows
weather-check/weather-check
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
womens-world-cup-predictions/wwc-forecast-20150602-093000
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150606-200029
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150606-230045
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150607-150137
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150607-180420
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150608-175420
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150608-210138
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150608-212619
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150608-235509
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150609-145605
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150609-175933
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150609-205725
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150611-182114
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150611-200059
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150611-210229
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150611-232844
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150612-185329
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150612-205525
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150612-215533
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150612-235650
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150613-145639
team, group, wspi, wspi_offense, wspi_defense, group_first, group_second, group_third_advance, group_third_no_advance, group_fourth, sixteen, quarter, semi, final, win
24 rows
womens-world-cup-predictions/wwc-forecast-20150613-175552
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womens-world-cup-predictions/wwc-forecast-20150620-213513
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world-cup-predictions/wc-20140619-235903
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world-cup-predictions/wc-20140620-205534
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world-cup-predictions/wc-20140701-092605
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32 rows
world-cup-predictions/wc-20140701-184332
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140701-224103
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140702-094046
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140703-094053
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140704-180211
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140704-220110
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140705-093245
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140705-225331
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140706-091537
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140707-100337
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140708-092538
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140708-215459
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140709-095047
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140709-231617
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140710-164509
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140711-102258
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
world-cup-predictions/wc-20140713-113900
country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win
32 rows
Download SQLite DB: fivethirtyeight.db 307.3 MB