library(tidyverse)
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2018/2018-10-23/movie_profit.csv") %>% head() %>% knitr::kable()
X1 release_date movie production_budget domestic_gross worldwide_gross distributor mpaa_rating genre
1 6/22/2007 Evan Almighty 1.75e+08 100289690 174131329 Universal PG Comedy
2 7/28/1995 Waterworld 1.75e+08 88246220 264246220 Universal PG-13 Action
3 5/12/2017 King Arthur: Legend of the Sword 1.75e+08 39175066 139950708 Warner Bros. PG-13 Adventure
4 12/25/2013 47 Ronin 1.75e+08 38362475 151716815 Universal PG-13 Action
5 6/22/2018 Jurassic World: Fallen Kingdom 1.70e+08 416769345 1304866322 Universal PG-13 Action
6 8/1/2014 Guardians of the Galaxy 1.70e+08 333172112 771051335 Walt Disney PG-13 Action 
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2018/2018-10-16/recent-grads.csv") %>% head() %>% knitr::kable()
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
1 2419 PETROLEUM ENGINEERING 2339 2057 282 Engineering 0.1205643 36 1976 1849 270 1207 37 0.0183805 110000 95000 125000 1534 364 193
2 2416 MINING AND MINERAL ENGINEERING 756 679 77 Engineering 0.1018519 7 640 556 170 388 85 0.1172414 75000 55000 90000 350 257 50
3 2415 METALLURGICAL ENGINEERING 856 725 131 Engineering 0.1530374 3 648 558 133 340 16 0.0240964 73000 50000 105000 456 176 0
4 2417 NAVAL ARCHITECTURE AND MARINE ENGINEERING 1258 1123 135 Engineering 0.1073132 16 758 1069 150 692 40 0.0501253 70000 43000 80000 529 102 0
5 2405 CHEMICAL ENGINEERING 32260 21239 11021 Engineering 0.3416305 289 25694 23170 5180 16697 1672 0.0610977 65000 50000 75000 18314 4440 972
6 2418 NUCLEAR ENGINEERING 2573 2200 373 Engineering 0.1449670 17 1857 2038 264 1449 400 0.1772264 65000 50000 102000 1142 657 244 
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-01-08/IMDb_Economist_tv_ratings.csv") %>% head() %>% knitr::kable()
titleId seasonNumber title date av_rating share genres
tt2879552 1 11.22.63 2016-03-10 8.4890 0.51 Drama,Mystery,Sci-Fi
tt3148266 1 12 Monkeys 2015-02-27 8.3407 0.46 Adventure,Drama,Mystery
tt3148266 2 12 Monkeys 2016-05-30 8.8196 0.25 Adventure,Drama,Mystery
tt3148266 3 12 Monkeys 2017-05-19 9.0369 0.19 Adventure,Drama,Mystery
tt3148266 4 12 Monkeys 2018-06-26 9.1363 0.38 Adventure,Drama,Mystery
tt1837492 1 13 Reasons Why 2017-03-31 8.4370 2.38 Drama,Mystery 
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-02-26/full_trains.csv") %>% head() %>% knitr::kable()
year month service departure_station arrival_station journey_time_avg total_num_trips num_of_canceled_trains comment_cancellations num_late_at_departure avg_delay_late_at_departure avg_delay_all_departing comment_delays_at_departure num_arriving_late avg_delay_late_on_arrival avg_delay_all_arriving comment_delays_on_arrival delay_cause_external_cause delay_cause_rail_infrastructure delay_cause_traffic_management delay_cause_rolling_stock delay_cause_station_management delay_cause_travelers num_greater_15_min_late avg_delay_late_greater_15_min num_greater_30_min_late num_greater_60_min_late
2017 9 National PARIS EST METZ 85.13378 299 0 NA 15 11.55000 0.7520067 NA 17 13.79412 0.4198439 NA 0.2500000 0.0000000 0.1666667 0.4166667 0.1666667 0.0000000 6 24.03333 1 0
2017 9 National REIMS PARIS EST 47.06452 218 1 NA 10 14.65333 1.2635177 NA 23 13.57029 1.1375576 NA 0.2500000 0.3750000 0.1250000 0.1250000 0.0625000 0.0625000 9 21.49815 1 0
2017 9 National PARIS EST STRASBOURG 116.23494 333 1 NA 20 13.69417 1.1392570 NA 19 21.53246 1.5863956 NA 0.2142857 0.2142857 0.0714286 0.2857143 0.2142857 0.0000000 14 24.69405 3 0
2017 9 National PARIS LYON AVIGNON TGV 161.08958 481 1 NA 36 20.98843 1.4062153 NA 61 26.56667 4.7885417 NA 0.1551724 0.1206897 0.3103448 0.3448276 0.0344828 0.0344828 40 34.04750 21 5
2017 9 National PARIS LYON BELLEGARDE (AIN) 164.45263 190 0 NA 16 20.96354 1.7289474 NA 38 23.15175 6.0088596 NA 0.1666667 0.2500000 0.2500000 0.3055556 0.0000000 0.0277778 26 28.40128 8 1
2017 9 National PARIS LYON BESANCON FRANCHE COMTE TGV 128.52105 191 1 NA 18 19.96389 1.8387719 NA 18 31.58796 5.0336842 NA 0.1111111 0.1111111 0.2222222 0.5000000 0.0000000 0.0555556 15 35.79667 8 1 
readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-21/spotify_songs.csv") %>% head() %>% knitr::kable()
track_id track_name track_artist track_popularity track_album_id track_album_name track_album_release_date playlist_name playlist_id playlist_genre playlist_subgenre danceability energy key loudness mode speechiness acousticness instrumentalness liveness valence tempo duration_ms
6f807x0ima9a1j3VPbc7VN I Don’t Care (with Justin Bieber) - Loud Luxury Remix Ed Sheeran 66 2oCs0DGTsRO98Gh5ZSl2Cx I Don’t Care (with Justin Bieber) [Loud Luxury Remix] 2019-06-14 Pop Remix 37i9dQZF1DXcZDD7cfEKhW pop dance pop 0.748 0.916 6 -2.634 1 0.0583 0.1020 0.00e+00 0.0653 0.518 122.036 194754
0r7CVbZTWZgbTCYdfa2P31 Memories - Dillon Francis Remix Maroon 5 67 63rPSO264uRjW1X5E6cWv6 Memories (Dillon Francis Remix) 2019-12-13 Pop Remix 37i9dQZF1DXcZDD7cfEKhW pop dance pop 0.726 0.815 11 -4.969 1 0.0373 0.0724 4.21e-03 0.3570 0.693 99.972 162600
1z1Hg7Vb0AhHDiEmnDE79l All the Time - Don Diablo Remix Zara Larsson 70 1HoSmj2eLcsrR0vE9gThr4 All the Time (Don Diablo Remix) 2019-07-05 Pop Remix 37i9dQZF1DXcZDD7cfEKhW pop dance pop 0.675 0.931 1 -3.432 0 0.0742 0.0794 2.33e-05 0.1100 0.613 124.008 176616
75FpbthrwQmzHlBJLuGdC7 Call You Mine - Keanu Silva Remix The Chainsmokers 60 1nqYsOef1yKKuGOVchbsk6 Call You Mine - The Remixes 2019-07-19 Pop Remix 37i9dQZF1DXcZDD7cfEKhW pop dance pop 0.718 0.930 7 -3.778 1 0.1020 0.0287 9.40e-06 0.2040 0.277 121.956 169093
1e8PAfcKUYoKkxPhrHqw4x Someone You Loved - Future Humans Remix Lewis Capaldi 69 7m7vv9wlQ4i0LFuJiE2zsQ Someone You Loved (Future Humans Remix) 2019-03-05 Pop Remix 37i9dQZF1DXcZDD7cfEKhW pop dance pop 0.650 0.833 1 -4.672 1 0.0359 0.0803 0.00e+00 0.0833 0.725 123.976 189052
7fvUMiyapMsRRxr07cU8Ef Beautiful People (feat. Khalid) - Jack Wins Remix Ed Sheeran 67 2yiy9cd2QktrNvWC2EUi0k Beautiful People (feat. Khalid) [Jack Wins Remix] 2019-07-11 Pop Remix 37i9dQZF1DXcZDD7cfEKhW pop dance pop 0.675 0.919 8 -5.385 1 0.1270 0.0799 0.00e+00 0.1430 0.585 124.982 163049 
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-02-04/standings.csv") %>% head() %>% knitr::kable()
team team_name year wins loss points_for points_against points_differential margin_of_victory strength_of_schedule simple_rating offensive_ranking defensive_ranking playoffs sb_winner
Miami Dolphins 2000 11 5 323 226 97 6.1 1.0 7.1 0.0 7.1 Playoffs No Superbowl
Indianapolis Colts 2000 10 6 429 326 103 6.4 1.5 7.9 7.1 0.8 Playoffs No Superbowl
New York Jets 2000 9 7 321 321 0 0.0 3.5 3.5 1.4 2.2 No Playoffs No Superbowl
Buffalo Bills 2000 8 8 315 350 -35 -2.2 2.2 0.0 0.5 -0.5 No Playoffs No Superbowl
New England Patriots 2000 5 11 276 338 -62 -3.9 1.4 -2.5 -2.7 0.2 No Playoffs No Superbowl
Tennessee Titans 2000 13 3 346 191 155 9.7 -1.3 8.3 1.5 6.8 Playoffs No Superbowl 
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-10-08/ipf_lifts.csv") %>% head() %>% knitr::kable()
name sex event equipment age age_class division bodyweight_kg weight_class_kg best3squat_kg best3bench_kg best3deadlift_kg place date federation meet_name
Hiroyuki Isagawa M SBD Single-ply NA NA NA 67.5 67.5 205 140.0 225 1 1985-08-03 IPF World Games
David Mannering M SBD Single-ply 24.0 24-34 NA 67.5 67.5 225 132.5 235 2 1985-08-03 IPF World Games
Eddy Pengelly M SBD Single-ply 35.5 35-39 NA 67.5 67.5 245 157.5 270 3 1985-08-03 IPF World Games
Nanda Talambanua M SBD Single-ply 19.5 20-23 NA 67.5 67.5 195 110.0 240 4 1985-08-03 IPF World Games
Göran Henrysson M SBD Single-ply NA NA NA 67.5 67.5 240 140.0 215 5 1985-08-03 IPF World Games
PJ Joseph M SBD Single-ply NA NA NA 67.5 67.5 200 100.0 230 6 1985-08-03 IPF World Games 
read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv") %>% head() %>% knitr::kable()
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex year
Adelie Torgersen 39.1 18.7 181 3750 male 2007
Adelie Torgersen 39.5 17.4 186 3800 female 2007
Adelie Torgersen 40.3 18.0 195 3250 female 2007
Adelie Torgersen NA NA NA NA NA 2007
Adelie Torgersen 36.7 19.3 193 3450 female 2007
Adelie Torgersen 39.3 20.6 190 3650 male 2007