Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub · About: simonw/fivethirtyeight-datasette

Custom SQL query

./index

dataset_url, article_url, live

190 rows

ahca-polls/ahca_polls

Start, End, Pollster, Favor, Oppose, Url, Text

15 rows

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

births/US_births_1994-2003_CDC_NCHS

year, month, date_of_month, day_of_week, births

3,652 rows

births/US_births_2000-2014_SSA

year, month, date_of_month, day_of_week, births

5,479 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

cabinet-turnover/cabinet-turnover

president, position, appointee, start, end, length, days

312 rows

candy-power-ranking/candy-data

competitorname, chocolate, fruity, caramel, peanutyalmondy, nougat, crispedricewafer, hard, bar, pluribus, sugarpercent, pricepercent, winpercent

85 rows

chess-transfers/transfers

url, ID, Federation, Form.Fed, Transfer Date

932 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/majors-list

FOD1P, Major, Major_Category

174 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

cousin-marriage/cousin-marriage-data

Country, Percent

70 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

democratic-bench/democratic-bench

cand, raised_exp, raised_act

67 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

fandango/fandango_scrape

FILM, STARS, RATING, VOTES

510 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

infrastructure-jobs/payroll-states

state_code, state_name

53 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/performer-scores

Performer, Score per year, Total score, Show

243 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

mayweather-mcgregor/tweets

created_at, emojis, id, link, retweeted, screen_name, text

12,118 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/aging-curve

Decade, Age, Male, Female, Male.1, Female.1

12 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/new-top-firstNames

Unnamed: 0, name, newPerct2013

100 rows

most-common-name/new-top-surnames

Unnamed: 0, name, perct2013

100 rows

most-common-name/state-pop

state, totalPop, hispPop

51 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_2015_final

city, state, 2014_murders, 2015_murders, change

83 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-draymond/draymond

season, player, possessions, DRAYMOND

3,009 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

18,013 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

28,179 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

3,539 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

5,492 rows

nba-tattoos/nba-tattoos-data

Player Name, Tattoos yes/no

636 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_castGender

MOVIE, ACTOR, CHARACTER_NAME, TYPE, BILLING, GENDER

2,075 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-suspensions/nfl-suspensions-data

name, team, games, category, desc., year, source

269 rows

nfl-ticket-prices/2014-average-ticket-price

Event, Division, Avg TP, $

108 rows

nfl-ticket-prices/jets-buyer

Raiders at Jets 9/7/14, Unnamed: 1, Unnamed: 2

62 rows

nfl-ticket-prices/national-average

Genre, Avg TP, $

32 rows

nfl-wide-receivers/advanced-historical

pfr_player_id, player_name, career_try, career_ranypa, career_wowy, bcs_rating

6,496 rows

nfl-wide-receivers/try-per-game-aging-curve

age_from, age_to, trypg_change

24 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/p_values_analysis

food, characteristic, p_values

27,716 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, HOTDOGQUAN, BACONSAUSAGEFREQ, BACONSAUSAGEQUAN, LUNCHMEATFREQ, LUNCHMEATQUAN, MEATBALLSFREQ, MEATBALLSQUAN, STEAKFREQ, STEAKQUAN, TACOFREQ, TACOQUAN, RIBSFREQ, RIBSQUAN, PORKCHOPSFREQ, PORKCHOPSQUAN, BEEFPORKDISHFREQ, BEEFPORKDISHQUAN, LIVERFREQ, LIVERQUAN, VARIETYMEATFREQ, VARIETYMEATQUAN, VEALLAMBGAMEFREQ, VEALLAMBGAMEQUAN, FRIEDORBREADEDCHICKENFREQ, FRIEDORBREADEDCHICKENQUAN, ROASTCHICKENFREQ, ROASTCHICKENQUAN, OTHERCHICKENDISHFREQ, OTHERCHICKENDISHQUAN, EATFISH, OYSTERSFREQ, OYSTERSQUAN, SHELLFISHFREQ, SHELLFISHQUAN, TUNAFREQ, TUNAQUAN, SALMONFREQ, SALMONQUAN, FRIEDORBREADEDFISHFREQ, FRIEDORBREADEDFISHQUAN, OTHERFISHFREQ, OTHERFISHQUAN, PEANUTBUTTERFREQ, PEANUTBUTTERQUAN, WALNUTSFREQ, WALNUTSQUAN, OTHERNUTSFREQ, OTHERNUTSQUAN, PROTEINBARSFREQ, PROTEINBARSQUAN, CEREALBARSFREQ, CEREALBARSQUAN, POPCORNFREQ, POPCORNQUAN, WHOLEGRAINCRACKERSFREQ, WHOLEGRAINCRACKERSQUAN, OTHERCRACKERSFREQ, OTHERCRACKERSQUAN, CORNCHIPSFREQ, CORNCHIPSQUAN, OTHERCHIPSFREQ, OTHERCHIPSQUAN, DONUTSFREQ, DONUTSQUAN, CAKESFREQ, CAKESQUAN, COOKIESFREQ, COOKIESQUAN, PUMPKINPIEFREQ, PUMPKINPIEQUAN, OTHERPIESFREQ, OTHERPIESQUAN, ICECREAMFREQ, ICECREAMQUAN, PUDDINGFREQ, PUDDINGQUAN, SAUCEICECREAMFREQ, SAUCEICECREAMQUAN, POPSICLESFREQ, POPSICLESQUAN, CHOCOLATECANDYFREQ, CHOCOLATECANDYQUAN, OTHERCANDIESFREQ, OTHERCANDIESQUAN, MARGARINEFREQ, MARGARINEQUAN, BUTTERFREQ, BUTTERQUAN, MAYOFREQ, MAYOQUAN, SALSAFREQ, SALSAQUAN, BARBECUESAUCEFREQ, BARBECUESAUCEQUAN, OTHERRICHSAUCESFREQ, OTHERRICHSAUCESQUAN, JAMFREQ, JAMQUAN, PICKLESFREQ, PICKLESQUAN, SALTFREQ, SALTQUAN, COCOAFREQ, COCOAQUAN, MILKFREQ, MILKQUAN, MEALREPLACEMENTDRINKSFREQ, MEALREPLACEMENTDRINKSQUAN, TOMATOJUICEFREQ, TOMATOJUICEQUAN, ORANGEJUICEFREQ, ORANGEJUICEQUAN, OTHERFRUITJUICESFREQ, OTHERFRUITJUICESQUAN, HICFREQ, HICQUAN, SOMEJUICEFREQ, SOMEJUICEQUAN, ICEDTEAFREQ, ICEDTEAQUAN, SPORTSDRINKSFREQ, SPORTSDRINKSQUAN, ENERGYDRINKSFREQ, ENERGYDRINKSQUAN, LEMONADEFREQ, LEMONADEQUAN, SODAFREQ, SODAQUAN, BEERFREQ, BEERQUAN, WINEFREQ, WINEQUAN, COCKTAILSFREQ, COCKTAILSQUAN, WATERFREQ, WATERQUAN, COFFEEDRINKSFREQ, COFFEEDRINKSQUAN, COFFEEFREQ, COFFEEQUAN, HOTTEAFREQ, HOTTEAQUAN, COFFEEDRINKSKIND, COFFEEDRINKSTYPE, DECAFCOFFEETYPE, REGULARCOFFEETYPE, BOTHKINDSCOFFEETYPE, DONTDRINKCOFFEETYPE, CREAMINCOFFEE, SUGARINCOFFEE, COFFEESUGARTEASPOONS, DECAFHOTTEATYPE, REGULARHOTTEATYPE, BOTHKINDSHOTTEATYPE, DONTDRINKHOTTEATYPE, CREAMINTEA, SUGARINTEA, TEASUGARTEASPOONS, MILKTYPE, MEALREPLACEMENTDRINKSTYPE, ORANGEJUICETYPE, ICEDTEATYPE, LEMONADETYPE, ENERGYDRINKSTYPE, SODATYPE, SODACAFFEINE, BEERTYPE, WINETYPE, SLICEDCHEESETYPE, YOGURTKIND, YOGURTTYPE, SALADDRESSINGSTYPE, SPAGHETTITYPE, OTHERNOODLESTYPE, HAMBURGERTYPE, FATONMEATTYPE, CHICKENSKINTYPE, HOTDOGTYPE, LUNCHMEATTYPE, CAKESTYPE, COOKIESTYPE, ICECREAMTYPE, PROTEINBARSTYPE, BAGELTYPE, BUNSTYPE, OTHERBREADSTYPE, TORTILLASTYPE, POPCORNTYPE, CRACKERSTYPE, MAYOTYPE, ALLBRANORIGTYPE, ALLBRANCOMPTYPE, APPLEJACKSTYPE, BRANFLAKESTYPE, CAPNCRUNCHTYPE, CHEERIOSPLAINTYPE, CHEERIOSHONNUTTYPE, CHEXWHEATTYPE, CHEXOTHERTYPE, CINNTOASTCRTYPE, COCOAKRISPIESTYPE, CORNFLAKESTYPE, CORNPOPSTYPE, FIBERONETYPE, FROOTLOOPSTYPE, FROSTEDFLAKESTYPE, FROSTEDMINIWHEATSTYPE, GRANOLATYPE, GRAPENUTSTYPE, HONBUNCHOATSTYPE, KASHIGOLNORHR2HRTYPE, LIFETYPE, LUCKYCHARMSTYPE, OATSQUARESTYPE, RAISINBRANTYPE, RICEKRISPIESTYPE, SHREDDEDWHEATTYPE, SPECIALKPLAINTYPE, SPECIALKFLAVSTYPE, TOTALTYPE, WHEATIESTYPE, OTHERSWEETCEREALTYPE, OTHERUNSWEETCEREALTYPE, OTHERWHOLEGRAINCEREALTYPE, OTHERFIBERCEREALTYPE, DONTEATORDONTKNOWCEREALTYPE, COOKINGFATPAMORNONE, COOKINGFATBUTTER, COOKINGFATHALF, COOKINGFATSTICKMARG, COOKINGFATSOFTTUBMARG, COOKINGFATLOWFATMARG, COOKINGFATOLIVE, COOKINGFATCANOLA, COOKINGFATCORN, COOKINGFATPEANUT, COOKINGFATLARD, COOKINGFATCRISCO, COOKINGFATOTHER, COOKINGFATDONTKNOW, USEVITSREGULARLY, PRENATALVITSAMOUNT, PRENATALVITSYEARS, ONEADAYAMOUNT, ONEADAYYEARS, BCOMPLEXTYPEVITSAMOUNT, BCOMPLEXTYPEVITSYEARS, ANTIOXIDANTCOMBOAMOUNT, ANTIOXIDANTCOMBOYEARS, VITAMINAAMOUNT, VITAMINAYEARS, VITAMINB6AMOUNT, VITAMINB6YEARS, VITAMINB12AMOUNT, VITAMINB12YEARS, VITAMINCAMOUNT, VITAMINCYEARS, VITAMINDAMOUNT, VITAMINDYEARS, VITAMINEAMOUNT, VITAMINEYEARS, FOLICACIDAMOUNT, FOLICACIDYEARS, CALCIUMAMOUNT, CALCIUMYEARS, IRONAMOUNT, IRONYEARS, ZINCAMOUNT, ZINCYEARS, OMEGASUPPFREQ, OMEGASUPPYEARS, FIBERSUPPAMOUNT, FIBERSUPPYEARS, MINERALSYESORNO, VITAMINCQUAN, VITAMINEQUAN, CALCIUMQUAN, VITAMINDQUAN, FISHOILTYPE, FLAXHEMPSEEDOILTYPE, KRILLOILTYPE, ALGAEOILTYPE, OMEGA3DONTKNOWTYPE, VEGGIESFREQ, FRUITSFREQ, FATOILFREQ, MEALS, SNACKS, LIGHTHOUSEFREQ, LIGHTHOUSETIME, SLOWWALKFREQ, SLOWWALKTIME, JOBSTANDFREQ, JOBSTANDTIME, CHILDCAREFREQ, CHILDCARETIME, WEEDYARDFREQ, WEEDYARDTIME, BRISKWALKFREQ, BRISKWALKTIME, JOBWALKFREQ, JOBWALKTIME, HEAVYWORKFREQ, HEAVYWORKTIME, JOBLIFTFREQ, JOBLIFTTIME, EXERGYMFREQ, EXERGYMTIME, BIKESWIMFREQ, BIKESWIMTIME, LATINO, WHITE, BLACK, ASIAN, NATIVEAMER, HAWAIIAN, NOTPROVIDED, GROUP_SOLID_COUNT, GROUP_SOLID_TOTAL_FREQUENCY, GROUP_SOLID_TOTAL_GRAMS, GROUP_ALCOHOLICBEVERAGES_TOTAL_KCAL, GROUP_ALCOHOLICBEVERAGES_TOTAL_GRAMS, GROUP_ALCOHOLICBEVERAGES_TOTAL_FREQUENCY, GROUP_SUGARYBEVG_TOTAL_KCAL, GROUP_SUGARYBEVG_TOTAL_GRAMS, GROUP_SUGARYBEVG_TOTAL_FREQUENCY, GROUP_A_SUGBEV_TOTAL_KCAL, GROUP_A_SUGBEV_TOTAL_FREQUENCY, GROUP_SWEETS_TOTAL_KCAL, GROUP_SWEETS_TOTAL_GRAMS, GROUP_SWEETS_TOTAL_FREQUENCY, DT_KCAL, DT_PROT, DT_CARB, DT_TFAT, DT_ALCO, DT_SUG_T, DT_FIBE, DT_MOIS, DT_SFAT, DT_MFAT, DT_PFAT, DT_CHOL, DT_S040, DT_S060, DT_S080, DT_S100, DT_S120, DT_S140, DT_S160, DT_S180, DT_M161, DT_M181, DT_M201, DT_M221, DT_P182, DT_P183, DT_P184, DT_P204, DT_P205, DT_P225, DT_P226, DT_VARAE, DT_RET, DT_ACARO, DT_BCARO, DT_CRYPT, DT_LYCO, DT_LUTZE, DT_ATOC, DT_ATAD, DT_VITD, DT_VITK, DT_VITC, DT_THIA, DT_RIBO, DT_NIAC, DT_VITB6, DT_TFOL, FOL_DFE, DT_FOLAC, DT_FOLFD, DT_VB12, DT_B12AD, DT_CHLN, DT_CALC, DT_IRON, DT_MAGN, DT_PHOS, DT_POTA, DT_SODI, DT_ZINC, DT_COPP, DT_SEL, DT_CAFFN, DT_THEO, CYAD, DELPH, MALVIDIN, PELARGDIN, PEONIDIN, PETUNIDIN, EPICATEC, EPICATECG3, EPICATEGC, EPICATEGC3G, CATECHIN, GALCATEGC, THEAFLAVIN, THEAFLV33D, THEAFLV3PG, THEAFLV3G, THEARBIGN, ERIODICTYL, HESPT, NARING, APIGEN, LUTEOL, ISORHMNTN, KAEMF, MYRIC, QUERCE, DDZEIN, GNSTEIN, GLYCTEIN, T_ANTHOCYADNS, T_FLAVAN3OLS, T_FLAVANONES, T_FLAVONES, T_FLAVONOLS, T_ISOFLAVONES, T_FLAVONOIDS, GI, GL, F_TOTAL, F_CITMLB, F_OTHER, F_JUICE, F_WHOLE, V_TOTAL, V_DRKGR, V_REDOR_TOTAL, V_REDOR_TOMATO, V_REDOR_OTHER, V_STARCHY_TOTAL, V_STARCHY_POTATO, V_STARCHY_OTHER, V_OTHER, V_LEGUMES, G_TOTAL, G_WHOLE, G_REFINED, PF_TOTAL, PF_MPS_TOTAL, PF_MEAT, PF_CUREDMEAT, PF_ORGAN, PF_POULT, PF_SEAFD_HI, PF_SEAFD_LOW, PF_EGGS, PF_SOY, PF_NUTSDS, PF_LEGUMES, D_TOTAL, D_MILK, D_YOGURT, D_CHEESE, OILS, SOLID_FATS, ADD_SUGARS, A_DRINKS, D_SOY, M_SOY_ND, ADSUG_NA, OILS_M, SOLID_FATS_M, A_BEV_KC, AA_BEV, AV_TOT_S, AF_TOT_S, GROUP_A_SUGBEV_TOTAL_GRAMS, R_MEAT_S, A_NUT_S, A_BEAN_S, DHA_EPA, ADJ_PUFA, DT_TRFAT, PCTALCH, PSGTOT, PSGWHL, PSVEGNBP, PSVEGDKG, PSVEGORN, PSVEGOTH, PSVEGPOT, PSFRUIT, PSDAIRY, PSMFP, PSNUTSD, PSEGGS, PSLEGSOY, PSOILS, SUP_VITA, SUP_LZ, SUP_VITD, SUP_VITE, SUP_VK, SUP_B1, SUP_B2, SUP_NIAC, SUP_B6, SUP_FOL, SUP_B12, SUP_VITC, SUP_CA, SUP_CU, SUP_IRON, SUP_MG, SUP_SE, SUP_ZINC, SUP_ALA, SUP_OLEIC, SUP_OM_3, SUP_OM_6, SUP_EPA, SUP_DHA, SUP_FIBER, KCAL_EXPENDITURE_ALL, KCAL_EXPENDITURE_RECR, LOWMINS, MODMINS, VIGMINS, RECRMINS, METMINS, METMINRECR, GROUP_BREAKFAST_SANDWICH_WITH_EGG_OR_MEAT_TOTAL_GRAMS, GROUP_OTHER_EGGS_OR_OMELETS_TOTAL_GRAMS, GROUP_YOGURT_TOTAL_GRAMS, GROUP_YOGURT_PLAIN_LOW_FAT_TOTAL_GRAMS, GROUP_YOGURT_PLAIN_NON_FAT_TOTAL_GRAMS, GROUP_YOGURT_PLAIN_FULL_FAT_TOTAL_GRAMS, GROUP_YOGURT_SWEET_LOW_FAT_TOTAL_GRAMS, GROUP_YOGURT_SWEET_NON_FAT_TOTAL_GRAMS, GROUP_YOGURT_SWEET_FULL_FAT_TOTAL_GRAMS, GROUP_COTTAGE_CHEESE_RICOTTA_TOTAL_GRAMS, GROUP_CREAM_CHEESE_SOUR_CREAM_DIP_TOTAL_GRAMS, GROUP_CHEESE_TOTAL_GRAMS, GROUP_CHEESE_LOW_FAT_TOTAL_GRAMS, GROUP_CHEESE_FULL_FAT_TOTAL_GRAMS, GROUP_ALL_BRAN_ORIGINAL_TOTAL_GRAMS, GROUP_ALL_BRAN_COMPLETE_COMPLETE_TOTAL_GRAMS, GROUP_APPLE_JACKS_COOKIE_CRISP_TOTAL_GRAMS, GROUP_BRAN_FLAKES_TOTAL_GRAMS, GROUP_CAP_N_CRUNCH_TOTAL_GRAMS, GROUP_CHEERIOS_PLAIN_OR_MULTI_GRAIN_TOTAL_GRAMS, GROUP_CHEERIOS_HONEY_NUT_FLAVORS_TOTAL_GRAMS, GROUP_CHEX_WHEAT_TOTAL_GRAMS, GROUP_CHEX_OTHER_TOTAL_GRAMS, GROUP_CINNAMON_TOAST_CRUNCH_TOTAL_GRAMS, GROUP_COCOA_KRISPIES_PEBBLES_PUFFS_TOTAL_GRAMS, GROUP_CORN_FLAKES_CORN_PUFFS_TOTAL_GRAMS, GROUP_CORN_POPS_TOTAL_GRAMS, GROUP_FIBER_ONE_BRAN_BUDS_TOTAL_GRAMS, GROUP_FROOT_LOOPS_TOTAL_GRAMS, GROUP_FROSTED_FLAKES_TOTAL_GRAMS, GROUP_FROSTED_MINI_WHEATS_TOTAL_GRAMS, GROUP_GRANOLA_TOTAL_GRAMS, GROUP_GRAPE_NUTS_TOTAL_GRAMS, GROUP_HONEY_BUNCHES_OF_OATS_TOTAL_GRAMS, GROUP_KASHI_GOLEAN_HEART_2_HEART_TOTAL_GRAMS, GROUP_LIFE_TOTAL_GRAMS, GROUP_LUCKY_CHARMS_FRUITY_PEBBLES_TOTAL_GRAMS, GROUP_OATMEAL_SQUARES_OAT_BRAN_TOTAL_GRAMS, GROUP_RAISIN_BRAN_TOTAL_GRAMS, GROUP_RICE_KRISPIES_PUFFED_RICE_TOTAL_GRAMS, GROUP_SHREDDED_WHEAT_TOTAL_GRAMS, GROUP_SPECIAL_K_PLAIN_TOTAL_GRAMS, GROUP_SPECIAL_K_FLAVORS_TOTAL_GRAMS, GROUP_TOTAL_PRODUCT_19_TOTAL_GRAMS, GROUP_WHEATIES_TOTAL_GRAMS, GROUP_OTHER_NOT_WHOLEGRAIN_SWEET_CEREAL_TOTAL_GRAMS, GROUP_OTHER_NOT_WHOLEGRAIN_UNSWEETENED_CEREAL_TOTAL_GRAMS, GROUP_OTHER_WHOLE_GRAIN_CEREAL_TOTAL_GRAMS, GROUP_OTHER_FIBER_CEREAL_TOTAL_GRAMS, GROUP_DONT_EAT_CEREAL_TOTAL_GRAMS, GROUP_OATMEAL_WHOLEGRAIN_COOKED_CEREAL_TOTAL_GRAMS, GROUP_GRITS_CREAM_OF_WHEAT_MUSH_TOTAL_GRAMS, GROUP_BROWN_RICE_DISHES_WITH_TOTAL_GRAMS, GROUP_WHITE_RICE_DISHES_WITH_TOTAL_GRAMS, GROUP_PANCAKES_WAFFLES_FRENCH_TOAST_CREPES_WITH_SYRUP_TOTAL_GRAMS, GROUP_BREAKFAST_PASTRY_MUFFINS_QUICK_BREAD_TOTAL_GRAMS, GROUP_BISCUITS_SCONES_CROISSANTS_TOTAL_GRAMS, GROUP_CORN_BREAD_HUSH_PUPPIES_TOTAL_GRAMS, GROUP_SANDWICH_BUNS_TOTAL_GRAMS, GROUP_SANDWICH_BUNS_WHITE_TOTAL_GRAMS, GROUP_SANDWICH_BUNS_MULTIGRAIN_TOTAL_GRAMS, GROUP_SANDWICH_BUNS_WHOLEGRAIN_TOTAL_GRAMS, GROUP_SANDWICH_BUNS_MIX_TOTAL_GRAMS, GROUP_BAGELS_ENG_MUFFIN_PITA_TOTAL_GRAMS, GROUP_BAGELS_WHITE_TOTAL_GRAMS, GROUP_BAGELS_MULTIGRAIN_TOTAL_GRAMS, GROUP_BAGELS_WHOLEGRAIN_TOTAL_GRAMS, GROUP_BAGELS_MIX_TOTAL_GRAMS, GROUP_TORTILLAS_TOTAL_GRAMS, GROUP_TORTILLAS_CORN_TOTAL_GRAMS, GROUP_TORTILLAS_FLOUR_WHEAT_TOTAL_GRAMS, GROUP_TORTILLA_MIX_TOTAL_GRAMS, GROUP_BREAD_DINNER_ROLLS_TOTAL_GRAMS, GROUP_BREAD_WHITE_TOTAL_GRAMS, GROUP_BREAD_MULTI_GRAIN_TOTAL_GRAMS, GROUP_BREAD_WHOLE_GRAIN_TOTAL_GRAMS, GROUP_BREAD_MIX_TOTAL_GRAMS, GROUP_BROCCOLI_BRUSSEL_SPROUTS_CHINESE_BROCCOLI_TOTAL_GRAMS, GROUP_CARROTS_CARROT_MIXES_TOTAL_GRAMS, GROUP_CORN_TOTAL_GRAMS, GROUP_GREEN_BEANS_PEAS_TOTAL_GRAMS, GROUP_GREENS_SPINACH_COOKED_TOTAL_GRAMS, GROUP_CABBAGE_SLAW_CHINESE_CABBAGES_TOTAL_GRAMS, GROUP_GREEN_SALAD_RAW_SPINACH_TOTAL_GRAMS, GROUP_RAW_TOMATOES_TOTAL_GRAMS, GROUP_SALAD_DRESSING_TOTAL_GRAMS, GROUP_SALAD_DRESSING_LOW_FAT_TOTAL_GRAMS, GROUP_SALAD_DRESSING_FAT_FREE_TOTAL_GRAMS, GROUP_SALAD_DRESSING_REGULAR_TOTAL_GRAMS, GROUP_SALAD_DRESSING_OIL_AND_VINEGAR_TOTAL_GRAMS, GROUP_AVOCADO_GUACAMOLE_TOTAL_GRAMS, GROUP_SWEET_POTATO_YAM_TOTAL_GRAMS, GROUP_FRENCH_FRIES_FRIED_POTATOES_TOTAL_GRAMS, GROUP_WHITE_POTATOES_NOT_FRIED_TOTAL_GRAMS, GROUP_ANY_OTHER_VEGETABLE_TOTAL_GRAMS, GROUP_MELONS_YEAR_ROUND_TOTAL_GRAMS, GROUP_STRAWBERRIES_YEAR_ROUND_TOTAL_GRAMS, GROUP_BANANAS_TOTAL_GRAMS, GROUP_APPLES_PEARS_RAW_TOTAL_GRAMS, GROUP_ORANGE_TANGERINE_GRAPEFRUIT_FRESH_TOTAL_GRAMS, GROUP_PEACH_NECTARINE_TOTAL_GRAMS, GROUP_OTHER_FRESH_FRUIT_FRUIT_SALAD_TOTAL_GRAMS, GROUP_RAISINS_DRIED_FRUIT_TOTAL_GRAMS, GROUP_CANNED_FRUIT_APPLESAUCE_WITH_CANNED_CITRUS_TOTAL_GRAMS, GROUP_REFRIED_BEANS_HUMMUS_TOTAL_GRAMS, GROUP_OTHER_BEANS_LENTIL_CHILI_NOT_RICE_AND_BEANS_TOTAL_GRAMS, GROUP_TOFU_OR_TEMPEH_TOTAL_GRAMS, GROUP_MEAT_SUBSTITUTES_VEGETABLE_MEATS_TOTAL_GRAMS, GROUP_BEAN_SPLIT_PEA_LENTIL_SOUP_TOTAL_GRAMS, GROUP_VEGETABLE_SOUP_TOTAL_GRAMS, GROUP_OTHER_SOUP_TOTAL_GRAMS, GROUP_PIZZA_PIZZA_POCKETS_TOTAL_GRAMS, 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

obama-commutations/obama_commutations

key, info

7,077 rows

partisan-lean/2018/fivethirtyeight_partisan_lean_DISTRICTS

district, 2018

435 rows

partisan-lean/2018/fivethirtyeight_partisan_lean_STATES

state, 2018

50 rows

partisan-lean/2020/fivethirtyeight_partisan_lean_DISTRICTS

district, 2020

435 rows

partisan-lean/2020/fivethirtyeight_partisan_lean_STATES

state, 2020

50 rows

partisan-lean/fivethirtyeight_partisan_lean_DISTRICTS

district, 2021

435 rows

partisan-lean/fivethirtyeight_partisan_lean_STATES

state, 2021

51 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/all_data

person, dept, eow, cause

22,800 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

political-elasticity-scores/elasticity-by-district

district, elasticity

435 rows

political-elasticity-scores/elasticity-by-state

state, elasticity

51 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-campaign-trail/clinton

date, location, lat, lng

71 rows

presidential-campaign-trail/trump

date, location, lat, lng

106 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_hurricanes

Date, Harvey, Irma, Maria, Jose

38 rows

puerto-rico-media/mediacloud_states

Date, Texas, "Puerto Rico", Florida

51 rows

puerto-rico-media/mediacloud_top_online_news

name, url

49 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

puerto-rico-media/tv_hurricanes

Date, Harvey, Irma, Maria, Jose

37 rows

puerto-rico-media/tv_hurricanes_by_network

Date, Query, BBC News, CNN, FOX News, MSNBC

84 rows

puerto-rico-media/tv_states

Date, Florida, Texas, Puerto Rico

52 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/blocks_timestamps

Block, Timestamp

78,265 rows

rare-pepes/ordermatches_all

Block, ForwardAsset, ForwardQuantity, BackwardAsset, BackwardQuantity

26,038 rows

rare-pepes/pepecash_prices

Timestamp, Price

491 rows

rare-pepes/xcp_prices

Timestamp, Price

520 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

riddler-pick-lowest/low_numbers

Your Number, Show Your Work

3,660 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

science-giving/science_federal_giving

version https://git-lfs.github.com/spec/v1

2 rows

scrabble-games/scrabble_games

version https://git-lfs.github.com/spec/v1

2 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?ξ, 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/index

state, governor, party, filename, url

50 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

tarantino/tarantino

movie, type, word, minutes_in

1,894 rows

tennis-time/events_time

tournament, surface, seconds_added_per_point, years

205 rows

tennis-time/players_time

player, seconds_added_per_point

218 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

terrorism/eu_terrorism_fatalities_by_year

iyear, fatalities

29 rows

terrorism/france_terrorism_fatalities_by_year

iyear, fatalities

43 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-news/trump_news_data

date, major_category, detail

286 rows

trump-twitter/realDonaldTrump_poll_tweets

id, created_at, text

448 rows

trump-world-trust/TRUMPWORLD-issue-1

country, net_approval, Approve, Disapprove, DK/Refused

37 rows

trump-world-trust/TRUMPWORLD-issue-2

country, net_approval, Approve, Disapprove, DK/Refused

37 rows

trump-world-trust/TRUMPWORLD-issue-3

country, net_approval, Approve, Disapprove, DK/Refused

37 rows

trump-world-trust/TRUMPWORLD-issue-4

country, net_approval, Approve, Disapprove, DK/Refused

37 rows

trump-world-trust/TRUMPWORLD-issue-5

country, net_approval, Approve, Disapprove, DK/Refused

37 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/BarackObama

created_at, text, url, replies, retweets, favorites, user

3,207 rows

twitter-ratio/realDonaldTrump

created_at, text, url, replies, retweets, favorites, user

3,232 rows

twitter-ratio/senators

created_at, text, url, replies, retweets, favorites, user, bioguide_id, party, state

288,615 rows

undefeated-boxers/undefeated

name, url, date, wins

2,125 rows

unisex-names/aging_curve

decade, age, male, female, male_perct, female_perct

12 rows

unisex-names/unisex_names_table

Unnamed: 0, name, total, male_share, female_share, gap

919 rows

urbanization-index/urbanization-census-tract

statefips, state, gisjoin, lat_tract, long_tract, population, adj_radiuspop_5, urbanindex

73,280 rows

urbanization-index/urbanization-state

state, urbanindex

56 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

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-20150613-205441

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-20150615-175745

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-20150615-213540

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-20150616-190139

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-20150616-220036

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-20150617-175941

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-20150617-210614

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-20150620-180614

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-20150620-213513

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-20150621-145724

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-20150621-175918

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-20150621-213134

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-20150622-185345

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-20150622-215702

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-20150623-235546

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-20150626-184421

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-20150626-212544

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-20150627-180119

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-20150627-213532

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-20150630-210243

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-20150701-205548

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-20150705-205539

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-matches-20150602-093000

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150606-200029

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150606-230045

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150607-150137

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150607-180420

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150608-175420

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150608-210138

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150608-212619

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150608-235509

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150609-145605

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150609-175933

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150609-205725

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150611-182114

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150611-200059

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150611-210229

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150611-232844

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150612-185329

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150612-205525

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150612-215533

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150612-235650

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150613-145639

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150613-175552

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150613-205441

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150615-175745

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150615-213540

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150616-190139

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150616-220036

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150617-175941

date, group, team1, team2, team1_win, team2_win, tie

36 rows

womens-world-cup-predictions/wwc-matches-20150617-210614

date, group, team1, team2, team1_win, team2_win, tie

44 rows

womens-world-cup-predictions/wwc-matches-20150620-180614

date, group, team1, team2, team1_win, team2_win, tie

44 rows

womens-world-cup-predictions/wwc-matches-20150620-213513

date, group, team1, team2, team1_win, team2_win, tie

44 rows

womens-world-cup-predictions/wwc-matches-20150621-145724

date, group, team1, team2, team1_win, team2_win, tie

44 rows

womens-world-cup-predictions/wwc-matches-20150621-175918

date, group, team1, team2, team1_win, team2_win, tie

45 rows

womens-world-cup-predictions/wwc-matches-20150621-213134

date, group, team1, team2, team1_win, team2_win, tie

45 rows

womens-world-cup-predictions/wwc-matches-20150622-185345

date, group, team1, team2, team1_win, team2_win, tie

46 rows

womens-world-cup-predictions/wwc-matches-20150622-215702

date, group, team1, team2, team1_win, team2_win, tie

47 rows

womens-world-cup-predictions/wwc-matches-20150623-235546

date, group, team1, team2, team1_win, team2_win, tie

48 rows

womens-world-cup-predictions/wwc-matches-20150626-184421

date, group, team1, team2, team1_win, team2_win, tie

48 rows

womens-world-cup-predictions/wwc-matches-20150626-212544

date, group, team1, team2, team1_win, team2_win, tie

49 rows

womens-world-cup-predictions/wwc-matches-20150627-180119

date, group, team1, team2, team1_win, team2_win, tie

49 rows

womens-world-cup-predictions/wwc-matches-20150627-213532

date, group, team1, team2, team1_win, team2_win, tie

50 rows

womens-world-cup-predictions/wwc-matches-20150630-210243

date, group, team1, team2, team1_win, team2_win, tie

50 rows

womens-world-cup-predictions/wwc-matches-20150701-205548

date, group, team1, team2, team1_win, team2_win, tie

52 rows

womens-world-cup-predictions/wwc-matches-20150705-205539

date, group, team1, team2, team1_win, team2_win, tie

52 rows

world-cup-predictions/wc-20140609-140000

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140611-132709

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140612-094254

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140612-220228

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140613-091928

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140613-180212

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140613-205820

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140614-000045

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140614-091756

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140614-180027

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140614-210740

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140615-001554

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140615-030217

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140615-092237

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140615-180820

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140615-210736

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140616-100604

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140616-182949

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140616-185551

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140616-205307

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140617-000315

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140617-091836

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140617-175702

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140617-205249

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140617-235154

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140618-100110

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140618-175722

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140618-210231

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140618-235413

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140619-091907

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140619-180248

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140619-205931

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140619-235903

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140620-094015

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140620-175706

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140620-205534

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140620-235753

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140621-092639

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140621-175630

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140621-205738

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140621-235521

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140622-091255

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140622-175429

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140622-205351

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140622-235721

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140623-095120

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140623-175427

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140623-220333

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140624-100611

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140624-181518

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140625-091929

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140625-180355

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140625-220012

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140626-095930

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140626-180150

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140626-221022

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140627-100126

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140628-094211

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140628-185951

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140628-215357

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140629-091813

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140629-180901

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140629-225940

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140630-095330

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140630-175910

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140630-223910

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

32 rows

world-cup-predictions/wc-20140701-092605

country, country_id, group, spi, spi_offense, spi_defense, win_group, sixteen, quarter, semi, cup, win

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 274.2 MB