插补后如何加入列
How to join to column after imputation
我运行多重插补为数据框的2个变量插补缺失数据，然后我得到了一个新的数据框（2列用于2个插补变量）。
现在，我想用新数据框中的两个新估算的列替换原始数据框中的 2 列。
我该怎么办？
Original data frame
new data frame for imputed variables
这是我使用的代码。此数据框中只有 2 列缺少数据，所以我只估算了这两列。那样行吗？你能给我一个更好的方法吗？
library("mice")
imi<-mice(subset(data,select=c('ABV','EBC')),m=5,maxit=10)
数据
structure(list(Name = structure(c(58L, 188L, 40L, 155L, 32L,
88L, 92L, 55L, 135L, 31L, 139L, 26L, 126L, 10L, 166L, 104L, 75L,
180L, 35L, 175L, 77L, 99L, 4L, 71L, 141L, 176L, 53L, 39L, 172L,
196L, 123L, 107L, 16L, 96L, 82L, 185L, 30L, 15L, 94L, 129L, 187L,
151L, 33L, 23L, 28L, 44L, 157L, 69L, 132L, 83L, 131L, 11L, 182L,
181L, 54L, 115L, 116L, 183L, 150L, 195L, 45L, 144L, 1L, 110L,
17L, 114L, 9L, 117L, 112L, 70L, 34L, 169L, 27L, 66L, 3L, 73L,
133L, 91L, 154L, 130L, 160L, 105L, 90L, 165L, 67L, 100L, 162L,
98L, 29L, 68L, 189L, 192L, 102L, 190L, 134L, 136L, 52L, 12L,
81L, 59L, 63L, 122L, 93L, 109L, 178L, 138L, 5L, 43L, 140L, 95L,
2L, 174L, 76L, 51L, 156L, 60L, 149L, 128L, 177L, 142L, 103L,
7L, 8L, 14L, 164L, 74L, 145L, 148L, 113L, 86L, 108L, 48L, 163L,
6L, 186L, 89L, 36L, 191L, 125L, 120L, 62L, 65L, 124L, 168L, 147L,
79L, 173L, 84L, 193L, 25L, 146L, 121L, 127L, 153L, 13L, 106L,
119L, 161L, 49L, 97L, 101L, 61L, 137L, 24L, 85L, 194L, 78L, 41L,
170L, 47L, 118L, 184L, 179L, 72L, 42L, 111L, 87L, 57L, 38L, 37L,
171L, 22L, 50L, 80L, 159L, 18L, 152L, 64L, 56L, 158L, 167L, 46L,
19L, 21L, 20L, 143L), .Label = c("#Mashtag 2013", "#Mashtag 2014",
"#Mashtag 2015", "10 Heads High", "5am Saint", "77 Lager", "AB:02",
"AB:03", "AB:04", "AB:06", "AB:08", "AB:10", "AB:11", "AB:13",
"AB:15", "AB:17", "AB:18", "AB:20", "Ace Of Chinook", "Ace Of Citra",
"Ace Of Equinox", "Ace Of Simcoe", "Albino Squid Assasin", "Alice Porter",
"All Day Long - Prototype Challenge", "Alpha Dog", "Alpha Pop",
"Amarillo - IPA Is Dead", "American Ale", "Anarchist Alchemist",
"Arcade Nation", "Avery Brown Dredge", "Baby Dogma", "Baby Saison - B-Sides",
"Bad Pixie", "Barley Wine - Russian Doll", "Barrel Aged Albino Squid Assassin",
"Barrel Aged Hinterland", "Berliner Weisse With Raspberries And Rhubarb - B-Sides",
"Berliner Weisse With Yuzu - B-Sides", "Bitch Please (w/ 3 Floyds)",
"Black Dog", "Black Eye Joe (w/ Stone Brewing Co)", "Black Eyed King Imp",
"Black Eyed King Imp - Vietnamese Coffee Edition", "Black Hammer",
"Black Jacques", "Black Tokyo Horizon (w/Nøgne Ã0 & Mikkeller)",
"Blitz Berliner Weisse", "Blitz Series", "Born To Die", "Bounty Hunter - Shareholder Brew",
"Bourbon Baby", "Bracken's Porter", "Bramling X", "Brewdog Vs Beavertown",
"Brixton Porter", "Buzz", "Candy Kaiser", "Cap Dog (w/ Cap Brewery)",
"Catherine's Pony (w/ Beavertown)", "Challenger", "Chaos Theory",
"Chili Hammer", "Chinook - IPA Is Dead", "Citra", "Clown King",
"Cocoa Psycho", "Coffee Imperial Stout", "Comet", "Dana - IPA Is Dead",
"Dead Metaphor", "Dead Pony Club", "Deaf Mermaid - B-Sides",
"Devine Rebel (w/ Mikkeller)", "Dog A", "Dog B", "Dog C", "Dog D",
"Dog E", "Dog Fight (w/ Flying Dog)", "Dog Wired (w/8 Wired)",
"Dogma", "Doodlebug", "Double IPA - Russian Doll", "Edge", "El Dorado - IPA Is Dead",
"Electric India", "Ella - IPA Is Dead", "Elvis Juice V2.0 - Prototype Challenge",
"Everday Anarchy", "Fake Lager", "Galaxy", "Goldings - IPA Is Dead",
"Growler", "Hardcore IPA", "Hardkogt IPA", "HBC 366 - IPA Is Dead",
"HBC 369", "Hello My Name Is Beastie", "Hello My Name Is Holy Moose",
"Hello My Name Is Ingrid", "Hello My Name Is Little Ingrid",
"Hello My Name Is Mette-Marit", "Hello My Name Is PaÌ0ivi",
"Hello My Name is Sonja (w/ Evil Twin)", "Hello My Name is Vladimir",
"Hello My Name Is ZeÌ1 (w/ 2Cabeças)", "Hinterland", "Hobo Pop",
"Hop Fiction - Prototype Challenge", "Hopped-Up Brown Ale - Prototype Challenge",
"Hoppy Christmas", "Hops Kill Nazis", "Hunter Foundation Pale Ale",
"Hype", "India Session Lager - Prototype Challenge", "International Arms Race (w/ Flying Dog)",
"Interstellar", "Jack Hammer", "Jasmine IPA", "Jet Black Heart",
"Kohatu - IPA Is Dead", "Konnichiwa Kitsune", "Libertine Black Ale",
"Libertine Porter", "Lichtenstein Pale Ale", "Lizard Bride - Prototype Challenge",
"Lost Dog (w/Lost Abbey)", "Lumberjack Stout", "Magic Stone Dog (w/Magic Rock & Stone Brewing Co.)",
"Mandarina Bavaria - IPA Is Dead", "Mango Gose - B-Sides", "Melon And Cucumber IPA - B-Sides",
"Misspent Youth", "Morag's Mojito - B-Sides", "Moshi Moshi 15",
"Motueka", "Movember", "Mr.Miyagi's Wasabi Stout", "Nanny State",
"Nelson Sauvin", "Neon Overlord", "Never Mind The Anabolics",
"No Label", "Nuns With Guns", "Old World India Pale Ale", "Old World Russian Imperial Stout",
"Orange Blossom - B-Sides", "Pale - Russian Doll", "Paradox Islay",
"Paradox Islay 2.0", "Paradox Jura", "Peroxide Punk", "Pilsen Lager",
"Pioneer - IPA Is Dead", "Prototype 27", "Prototype Helles",
"Prototype Pils 2.0", "Pumpkin King", "Punk IPA 2007 - 2010",
"Punk IPA 2010 - Current", "Restorative Beverage For Invalids And Convalescents",
"Rhubarb Saison - B-Sides", "Riptide", "Russian Doll â0“ India Pale Ale",
"Rye Hammer", "San Diego Scotch Ale (w/Ballast Point)", "Santa Paws",
"Shareholder Black IPA 2011", "Ship Wreck", "Shipwrecker Circus (w/ Oskar Blues)",
"Simcoe", "Sink The Bismarck!", "Skull Candy", "Sorachi Ace",
"Sorachi Bitter - B-Sides", "Spiced Cherry Sour - B-Sides", "Stereo Wolf Stout - Prototype Challenge",
"Storm", "Sub Hop", "Sunk Punk", "Sunmaid Stout", "Sunshine On Rye - B-Sides",
"The Physics", "This. Is. Lager", "TM10", "Trashy Blonde", "Truffle and Chocolate Stout - B-Sides",
"U-Boat (w/ Victory Brewing)", "Vagabond Pale ALe - Prototype Challenge",
"Vagabond Pilsner", "Vic Secret", "Waimea - IPA Is Dead", "Whisky Sour - B-Sides",
"Zephyr"), class = "factor"), ABV = c(4.5, 4.1, 4.2, 6.3, 7.2,
NA, 4.7, 7.5, 7.3, 5.3, 4.5, 4.5, 6.1, 11.2, 6, 8.2, 12.5, 8,
4.7, 3.5, 15, 6.7, 7.8, 6.7, 0.5, 7.5, 5.8, 3.6, 10.5, 12.5,
7.2, 8.2, 10.7, 9.2, 7.1, 5, 16.5, 12.8, 6.7, 10, NA, 10, 4.5,
7.4, 7.2, 9.5, 9.2, 9, 7.2, 7.5, NA, 10.43, 7.1, 8, 5, 5.4, 4.1,
10.2, 4, 7, 12.7, 6.5, 7.5, 4.2, 11.8, 7.6, 15, 4.4, 6.3, 7.2,
NA, 4.5, 4.5, 7.5, 10, 3.8, 6.4, NA, 4, 15.2, 5.4, 8.3, 6.5,
8, 12, 8.2, 5.6, 7.2, 6.3, 10, 5.6, 4.5, 8.2, 8.4, 6, 6.7, 6.5,
11.5, 8.5, 5.2, 7.1, 4.7, 6.7, 9, 6.5, 6.7, 5, 5.8, 7.5, 4.5,
9, 41, 15, 8.5, 7.2, 9, 3.8, 5.7, 6.3, 7.5, 4.4, 18, 10.5, 11.3,
NA, 5.2, 4.5, 9.5, 7.2, 2.7, 6.4, 17.2, 8.5, 4.9, 4.7, 7.2, 10,
4.5, 7.2, 7.2, 6.7, 7.2, 4.4, 9, 7.5, 16.1, 6.7, 2.5, 7.4, 2.8,
4.2, 5.8, 5.2, 10, 12.8, 8.3, 6.5, 6, 3, 7.6, 5.5, 8.8, 5.2,
5.2, 8, 6.7, 15, 11.5, 7.1, NA, 7.5, 7.2, 5.2, 6.8, 5.5, 5.2,
6.7, 5, 9, 9.2, 13.8, 4.5, 3.2, 16.1, 4.7, 14.2, 13, 7.2, 9.2,
4.9, 7.2, 7.2, 4.5, 4.5, 4.5, 7.6), IBU = c(60, 41.5, 8, 55,
59, 38, 40, 75, 30, 60, 50, 42, 45, 150, 70, 70, 100, 60, 45,
33, 90, 67, 70, 70, 55, 75, 35, 8, 85, 125, 70, 70, 100, 125,
65, 47, 20.5, 50, 70, 35, 20, 55, 35, 65, 70, 85, 149, 65, 100,
30, 30, 65, 68, 35, 50, 35, 65, 50, 35, 20, 85, 35, 50, 50, 80,
70, 80, 35, 85, 70, 9, 35, 30, 70, 85, 35, 40, 45, 40, 20, 20,
70, 60, 45, 85, 42, 40, 70, 55, 85, 30, 55, 42, 50, 50, 40, 35,
80, 65, 45, 90, 45, 67, 85, 20, 67, 30, 40, 90, 38, 50, 1085,
90, 85, 100, 80, 20, 35, 130, 75, 35, 70, 14, 50, 25, 65, 25,
80, 70, 36, 50, 75, 100, 30, 37, 100, 80, 55, 50, 250, 67, 100,
70, 70, 80, 85, 70, 35, 70, 30, 25, 40, 50, 55, 70, 70, 55, 60,
8, 175, 35, 40, 45, 55, 85, 70, 90, 50, 80, 45, 0, 130, 55, 30,
60, 40, 70, 50, 85, 65, 60, 40, 8, 100, 25, 20, 100, 250, 50,
18, 250, 250, 40, 40, 40, 70), OG = c(1044, 1041.7, 1040, 1060,
1069, 1045, 1046, 1068, 1079, 1052, 1047, 1046, 1067, 1098, 1058,
1076, 1093, 1082, 1047, 1038, 1120, 1013, 1074, 1066, 1007, 1068,
1049, 1040, 1102, 1087, 1067, 1076, 1105, 1085, 1065, 1048.5,
1112, 1096, 1066, 1080, 1048, 1090, 1048, 1069, 1067, 1095, 1083,
1080, 1064, 1080, 1043, 1095, 1056, 1077, 1049, 1050, 1042, 1026,
1041, 1081, 1113.5, 1050, 1070, 1042, 1096, 1073, 1113, 1040,
1063, 1067, 1032, 1048, 1045, 1068, 1098, 1040, 1057, 1081, 1039,
1110, 1055, 1076, 1060, 1075, 1130, 1078, 1055, 1067, 1060, 1098,
1058, 1046, 1078, 1080, 1050, 1063, 1068, 1096, 1078, 1049, 1067,
1055, 1013, 1094, 1060, 1013, 1050, 1053, 1072, 1042.9, 1084,
1085, 1120, 1072, 1064, 1083, 1039, 1053, 1060, 1068, 1045, 1150,
1093, 1098, 1052, 1048, 1043, 1075, 1067, 1033, 1061, 1156, 1068,
1047, 1043, 1064, 1097, 1045, 1068, 1065, 1064, 1064, 1045, 1090,
1069, 1125, 1063, 1027, 1069, 1032.5, 1044, 1060, 1050, 1128,
1108, 1076, 1059, 1056, 1007, 1072, 1053, 1084, 1048, 1053, 1074,
1066, 1120, 1104, 1067, 1089, 1069, 1065, 1052, 1068, 1062, 1048,
1066, 1053, 1094, 1069, 1088, 1045, 1007, 1015, 1008, 1025, 1015,
1065, 1016, 1010, 1065, 1065, 1045, 1045, 1045, 1067), EBC = c(20,
15, 8, 30, 10, 15, 12, 22, 120, 200, 140, 62, 219, 70, 25, NA,
36, 12, 8, 50, 100, 19, 90, 30, 30, 30, 44, NA, 64, 40, 30, 16,
300, 40, 13, 65, 20, 111, 30, 80, 14, 300, 40, 60, 30, 250, 19.5,
97, 12, 46, 15, 23, 14, 15, 110, 11.5, 17, 197, 45, 12, 250,
23, 40, 30, 115, 59, 400, 12, 24, 30, 2, 44, 25, 30, 130, 25,
10, 15, 18, 158, 30, 30, 25, 240, 24, 90, 15, 30, 30, 30, 54,
25, 70, 200, 8, 15, 250, 115, 31.2, 45, 15, 200, 19, 400, NA,
19, 60, 177.3, 200, 18, 20, 40, 100, 15, 12, 180, 6, 25, 14,
30, 30, 57, NA, 164, 10, 16, 10, 195, 30, 57, 20, 128, 15, 12,
10, 12, 65, 20, 150, 15, 19, 12, 30, 190, 50, 400, 30, 10, 30,
42, 19, 35, 17, 300, 79, 30, 50, 17, 9, 40, 25, 190, 35, 165,
35, 30, 100, 38, 71, 15, 50, 14, 200, 86, 230, 13, 30, 200, 400,
60, 25, 18, 8, 500, 25, 67, 300, 15, 78.8, 13, 17, 104, 18, 18,
18, 20), PH = c(4.4, 4.4, 3.2, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.2, 5.2, 4.4, 4.4, 4.4, 5.2, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 3.2, 4.4, 4.4, 4.4, 4.4, 4.3, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.2, 4.4, 4.4, 4.2, 4.4, 4.4, 4.4, 4.4,
4.4, 4.5, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 3.2, 5.2,
4.4, 4.4, 4.4, 5.2, 4.4, 4, 4.4, 4.2, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 3.5, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 5.2, 4.2, 4.4, 4.4, 4.2,
4.4, 4.4, 4.4, 4.3, 3.2, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 5.2, 5.2, 4.4, 5.2, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 5.2,
4.2, 4.5, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.2, 4.4, 4.4, 4.2, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.3, 4.4, 4.2, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 3.2, 4.4, 4.4, 4.5, 4.4, 5.2, 5.2,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 5.2, 4.4, 4.4, 4.4, 4.4, 4.4,
4.3, 4.2, 4.4, 4.2, 3.2, 4.4, 4.2, 4, 4.4, 4.4, 4.2, 4.2, 4.4,
4.4, 4.2, 4.2, 4.2, 4.4), AttenuationLevel = c(75, 76, 83, 80,
67, 88.9, 78, 80.9, 74.7, 77, 74.5, 72.8, 70.1, 87, 79.3, 83,
68, 86, 79, 68.4, 98, 79.7, 79.7, 77.3, 28.6, 82.1, 90, 83, 102,
81.2, 82.1, 83, 76.2, 81.2, 85, 79.4, 100, 79.17, 77.3, 85, 89.6,
84.4, 72.9, 82.6, 82.1, 76.8, 83, 76, 84, 70, 81.4, 83.2, 82.1,
79.2, 79, 84, 76.2, 74.5, 75.6, 74, 76.8, 76, 81.4, 76.2, 79.2,
79.5, 84.1, 79.5, 82.6, 82.1, 88, 72.9, 75.6, 82.1, 79.6, 70,
87, 93.8, 76.9, 82, 74.6, 82.9, 83.3, 81.3, 102.3, 83.3, 78,
82.1, 80, 70, 74, 73.9, 83.3, 81.3, 87, 84, 70.6, 79.2, 84.6,
81.6, 80.6, 70, 79.7, 73.4, 87, 79.7, 76, 84.9, 79.2, 81, 82.1,
81.2, 98, 90.3, 84, 83.1, 87, 79.3, 83, 82.1, 73.3, 93.3, 80,
79.6, 87, 79, 79.1, 81.3, 82.1, 70.8, 80.3, 80.8, 95.6, 80.7,
83.7, 84, 79.4, 73.9, 78.6, 84.6, 79.7, 84, 82.9, 80, 82.6, 84,
81, 70.4, 82.6, 63.1, 72.7, 76.7, 80, 89, 81.5, 82.9, 81.4, 82.14,
82.5, 80.6, 79.3, 79.8, 77.1, 75.5, 82.4, 77.3, 98, 85, 79, 94.4,
81.1, 87, 73.1, 76.5, 67.7, 79.2, 77.3, 73.6, 73.4, 82.6, 83,
75.6, 78, 84, 75.6, 75.6, 84.4, 84.6, 81, 78.7, 84.6, 84.6, 75.6,
75.6, 75.6, 82), FermentationTempCelsius = c(19L, 18L, 21L, 9L,
10L, 22L, 10L, 19L, 19L, 19L, 19L, 22L, 18L, 17L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 18L, 19L, 19L, 19L, 19L, 21L, 21L, 21L,
19L, 21L, 21L, 21L, 9L, 19L, 20L, 21L, 19L, 19L, 22L, 21L, 19L,
18L, 19L, 18L, 19L, 19L, 19L, 12L, 23L, 21L, 10L, 9L, 19L, 19L,
19L, 21L, 19L, 19L, 18L, 18L, 21L, 19L, 20L, 20L, 21L, 10L, 19L,
19L, 21L, 19L, 19L, 19L, 21L, 19L, 20L, 23L, 19L, 21L, 19L, 21L,
19L, 20L, 21L, 21L, 19L, 19L, 19L, 21L, 19L, 9L, 22L, 14L, 20L,
19L, 19L, 20L, 18L, 14L, 19L, 19L, 19L, 21L, 20L, 19L, 19L, 19L,
21L, 10L, 21L, 21L, 19L, 18L, 19L, 21L, 20L, 17L, 20L, 19L, 19L,
22L, 19L, 20L, 20L, 19L, 15L, 19L, 19L, 19L, 19L, 21L, 21L, 10L,
12L, 19L, 21L, 19L, 19L, 21L, 19L, 19L, 20L, 21L, 22L, 21L, 99L,
19L, 19L, 22L, 16L, 19L, 19L, 21L, 18L, 21L, 19L, 19L, 19L, 21L,
17L, 21L, 19L, 19L, 19L, 19L, 19L, 21L, 19L, 23L, 19L, 20L, 19L,
19L, 19L, 19L, 19L, 19L, 21L, 18L, 21L, 19L, 21L, 21L, 12L, 21L,
21L, 21L, 21L, 12L, 21L, 21L, 19L, 19L, 19L, 21L), Yeast = structure(c(1L,
1L, 1L, 3L, 3L, 4L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L,
2L, 3L, 1L, 2L, 2L, 1L, 2L, 4L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
3L, 4L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L,
2L, 2L, 3L, 1L, 1L, 4L, 1L, 1L, 1L, 2L, 1L, 1L, 4L, 1L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 3L, 2L, 3L, 1L, 1L, 1L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 2L, 2L,
2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 4L, 1L, 1L, 2L, 1L,
1L, 1L, 2L, 2L, 3L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 1L, 2L, 1L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 1L,
1L, 1L, 2L), .Label = c("Wyeast 1056 - American Ale", "Wyeast 1272 - American Ale II",
"Wyeast 2007 - Pilsen Lager", "Wyeast 3711 - French Saison"), class = "factor")), class = "data.frame", row.names = c(NA,
-196L))
已更新
正如@dcarlson 所建议的，您可以在整个数据帧上 运行 mice，然后您可以使用 complete 来获取整个输出数据帧。然后，您可以将新数据与原始数据框合并。
library(tidyverse)
library(mice)
imi <- mice(data, m=5, maxit=10)
imi_complete <- complete(imi)
res <- data %>%
dplyr::left_join(., imi_complete %>% dplyr::select(Name, ABV, EBC), by = "Name") %>%
dplyr::select(-c(ABV.x, EBC.x)) %>%
dplyr::rename("ABV" = ABV.y, "EBC" = EBC.y)
输出
head(res)
Name IBU OG PH AttenuationLevel FermentationTempCelsius Yeast ABV EBC
1 Buzz 60.0 1044.0 4.4 75.0 19 Wyeast 1056 - American Ale 4.5 20
2 Trashy Blonde 41.5 1041.7 4.4 76.0 18 Wyeast 1056 - American Ale 4.1 15
3 Berliner Weisse With Yuzu - B-Sides 8.0 1040.0 3.2 83.0 21 Wyeast 1056 - American Ale 4.2 8
4 Pilsen Lager 55.0 1060.0 4.4 80.0 9 Wyeast 2007 - Pilsen Lager 6.3 30
5 Avery Brown Dredge 59.0 1069.0 4.4 67.0 10 Wyeast 2007 - Pilsen Lager 7.2 10
6 Electric India 38.0 1045.0 4.4 88.9 22 Wyeast 3711 - French Saison 7.5 15
旧
由于新数据框中没有 id 列，您可以 mutate 将原始数据框中的列替换为新数据框中的输出。但是，更好的做法是直接对原始数据框进行估算（如@dcarlson 和@r2evans 所建议的那样），这样您就可以确保数据位于正确的行上。
library(tidyverse)
df_orig %>%
dplyr::mutate(ABV = df_new$ABV, EBC = df_new$EBC)
输出
id ABV EBC third
1 1 -61 -58 37.94029
2 2 -80 -67 47.81479
3 3 -62 -66 48.85903
4 4 -69 -78 23.18026
5 5 -51 -77 29.91952
数据
df_orig <-
structure(
list(
id = c(1, 2, 3, 4, 5),
ABV = c(
38.9932923251763,
20.0923723727465,
37.640398349613,
31.4673039061017,
49.192731983494
),
EBC = c(
42.341671793256,
32.936319950968,
33.8184517389163,
21.5938150603324,
22.8182014194317
),
third = c(
37.9402944352478,
47.8147878032178,
48.8590325415134,
23.1802612892352,
29.9195193173364
)
),
class = "data.frame",
row.names = c(NA,-5L)
)
df_new <-
structure(
list(
ABV = c(-61,-80,-62,-69,-51),
EBC = c(-58,-67,-66,-78,-77)
),
class = c("rowwise_df", "tbl_df", "tbl",
"data.frame"),
row.names = c(NA,-5L),
groups = structure(
list(.rows = structure(
list(1L, 2L, 3L, 4L, 5L),
ptype = integer(0),
class = c("vctrs_list_of",
"vctrs_vctr", "list")
)),
row.names = c(NA,-5L),
class = c("tbl_df",
"tbl", "data.frame")
)
)
我运行多重插补为数据框的2个变量插补缺失数据，然后我得到了一个新的数据框（2列用于2个插补变量）。
现在，我想用新数据框中的两个新估算的列替换原始数据框中的 2 列。 我该怎么办？
Original data frame new data frame for imputed variables
这是我使用的代码。此数据框中只有 2 列缺少数据，所以我只估算了这两列。那样行吗？你能给我一个更好的方法吗？
library("mice")
imi<-mice(subset(data,select=c('ABV','EBC')),m=5,maxit=10)
数据
structure(list(Name = structure(c(58L, 188L, 40L, 155L, 32L,
88L, 92L, 55L, 135L, 31L, 139L, 26L, 126L, 10L, 166L, 104L, 75L,
180L, 35L, 175L, 77L, 99L, 4L, 71L, 141L, 176L, 53L, 39L, 172L,
196L, 123L, 107L, 16L, 96L, 82L, 185L, 30L, 15L, 94L, 129L, 187L,
151L, 33L, 23L, 28L, 44L, 157L, 69L, 132L, 83L, 131L, 11L, 182L,
181L, 54L, 115L, 116L, 183L, 150L, 195L, 45L, 144L, 1L, 110L,
17L, 114L, 9L, 117L, 112L, 70L, 34L, 169L, 27L, 66L, 3L, 73L,
133L, 91L, 154L, 130L, 160L, 105L, 90L, 165L, 67L, 100L, 162L,
98L, 29L, 68L, 189L, 192L, 102L, 190L, 134L, 136L, 52L, 12L,
81L, 59L, 63L, 122L, 93L, 109L, 178L, 138L, 5L, 43L, 140L, 95L,
2L, 174L, 76L, 51L, 156L, 60L, 149L, 128L, 177L, 142L, 103L,
7L, 8L, 14L, 164L, 74L, 145L, 148L, 113L, 86L, 108L, 48L, 163L,
6L, 186L, 89L, 36L, 191L, 125L, 120L, 62L, 65L, 124L, 168L, 147L,
79L, 173L, 84L, 193L, 25L, 146L, 121L, 127L, 153L, 13L, 106L,
119L, 161L, 49L, 97L, 101L, 61L, 137L, 24L, 85L, 194L, 78L, 41L,
170L, 47L, 118L, 184L, 179L, 72L, 42L, 111L, 87L, 57L, 38L, 37L,
171L, 22L, 50L, 80L, 159L, 18L, 152L, 64L, 56L, 158L, 167L, 46L,
19L, 21L, 20L, 143L), .Label = c("#Mashtag 2013", "#Mashtag 2014",
"#Mashtag 2015", "10 Heads High", "5am Saint", "77 Lager", "AB:02",
"AB:03", "AB:04", "AB:06", "AB:08", "AB:10", "AB:11", "AB:13",
"AB:15", "AB:17", "AB:18", "AB:20", "Ace Of Chinook", "Ace Of Citra",
"Ace Of Equinox", "Ace Of Simcoe", "Albino Squid Assasin", "Alice Porter",
"All Day Long - Prototype Challenge", "Alpha Dog", "Alpha Pop",
"Amarillo - IPA Is Dead", "American Ale", "Anarchist Alchemist",
"Arcade Nation", "Avery Brown Dredge", "Baby Dogma", "Baby Saison - B-Sides",
"Bad Pixie", "Barley Wine - Russian Doll", "Barrel Aged Albino Squid Assassin",
"Barrel Aged Hinterland", "Berliner Weisse With Raspberries And Rhubarb - B-Sides",
"Berliner Weisse With Yuzu - B-Sides", "Bitch Please (w/ 3 Floyds)",
"Black Dog", "Black Eye Joe (w/ Stone Brewing Co)", "Black Eyed King Imp",
"Black Eyed King Imp - Vietnamese Coffee Edition", "Black Hammer",
"Black Jacques", "Black Tokyo Horizon (w/Nøgne Ã0 & Mikkeller)",
"Blitz Berliner Weisse", "Blitz Series", "Born To Die", "Bounty Hunter - Shareholder Brew",
"Bourbon Baby", "Bracken's Porter", "Bramling X", "Brewdog Vs Beavertown",
"Brixton Porter", "Buzz", "Candy Kaiser", "Cap Dog (w/ Cap Brewery)",
"Catherine's Pony (w/ Beavertown)", "Challenger", "Chaos Theory",
"Chili Hammer", "Chinook - IPA Is Dead", "Citra", "Clown King",
"Cocoa Psycho", "Coffee Imperial Stout", "Comet", "Dana - IPA Is Dead",
"Dead Metaphor", "Dead Pony Club", "Deaf Mermaid - B-Sides",
"Devine Rebel (w/ Mikkeller)", "Dog A", "Dog B", "Dog C", "Dog D",
"Dog E", "Dog Fight (w/ Flying Dog)", "Dog Wired (w/8 Wired)",
"Dogma", "Doodlebug", "Double IPA - Russian Doll", "Edge", "El Dorado - IPA Is Dead",
"Electric India", "Ella - IPA Is Dead", "Elvis Juice V2.0 - Prototype Challenge",
"Everday Anarchy", "Fake Lager", "Galaxy", "Goldings - IPA Is Dead",
"Growler", "Hardcore IPA", "Hardkogt IPA", "HBC 366 - IPA Is Dead",
"HBC 369", "Hello My Name Is Beastie", "Hello My Name Is Holy Moose",
"Hello My Name Is Ingrid", "Hello My Name Is Little Ingrid",
"Hello My Name Is Mette-Marit", "Hello My Name Is PaÌ0ivi",
"Hello My Name is Sonja (w/ Evil Twin)", "Hello My Name is Vladimir",
"Hello My Name Is ZeÌ1 (w/ 2Cabeças)", "Hinterland", "Hobo Pop",
"Hop Fiction - Prototype Challenge", "Hopped-Up Brown Ale - Prototype Challenge",
"Hoppy Christmas", "Hops Kill Nazis", "Hunter Foundation Pale Ale",
"Hype", "India Session Lager - Prototype Challenge", "International Arms Race (w/ Flying Dog)",
"Interstellar", "Jack Hammer", "Jasmine IPA", "Jet Black Heart",
"Kohatu - IPA Is Dead", "Konnichiwa Kitsune", "Libertine Black Ale",
"Libertine Porter", "Lichtenstein Pale Ale", "Lizard Bride - Prototype Challenge",
"Lost Dog (w/Lost Abbey)", "Lumberjack Stout", "Magic Stone Dog (w/Magic Rock & Stone Brewing Co.)",
"Mandarina Bavaria - IPA Is Dead", "Mango Gose - B-Sides", "Melon And Cucumber IPA - B-Sides",
"Misspent Youth", "Morag's Mojito - B-Sides", "Moshi Moshi 15",
"Motueka", "Movember", "Mr.Miyagi's Wasabi Stout", "Nanny State",
"Nelson Sauvin", "Neon Overlord", "Never Mind The Anabolics",
"No Label", "Nuns With Guns", "Old World India Pale Ale", "Old World Russian Imperial Stout",
"Orange Blossom - B-Sides", "Pale - Russian Doll", "Paradox Islay",
"Paradox Islay 2.0", "Paradox Jura", "Peroxide Punk", "Pilsen Lager",
"Pioneer - IPA Is Dead", "Prototype 27", "Prototype Helles",
"Prototype Pils 2.0", "Pumpkin King", "Punk IPA 2007 - 2010",
"Punk IPA 2010 - Current", "Restorative Beverage For Invalids And Convalescents",
"Rhubarb Saison - B-Sides", "Riptide", "Russian Doll â0“ India Pale Ale",
"Rye Hammer", "San Diego Scotch Ale (w/Ballast Point)", "Santa Paws",
"Shareholder Black IPA 2011", "Ship Wreck", "Shipwrecker Circus (w/ Oskar Blues)",
"Simcoe", "Sink The Bismarck!", "Skull Candy", "Sorachi Ace",
"Sorachi Bitter - B-Sides", "Spiced Cherry Sour - B-Sides", "Stereo Wolf Stout - Prototype Challenge",
"Storm", "Sub Hop", "Sunk Punk", "Sunmaid Stout", "Sunshine On Rye - B-Sides",
"The Physics", "This. Is. Lager", "TM10", "Trashy Blonde", "Truffle and Chocolate Stout - B-Sides",
"U-Boat (w/ Victory Brewing)", "Vagabond Pale ALe - Prototype Challenge",
"Vagabond Pilsner", "Vic Secret", "Waimea - IPA Is Dead", "Whisky Sour - B-Sides",
"Zephyr"), class = "factor"), ABV = c(4.5, 4.1, 4.2, 6.3, 7.2,
NA, 4.7, 7.5, 7.3, 5.3, 4.5, 4.5, 6.1, 11.2, 6, 8.2, 12.5, 8,
4.7, 3.5, 15, 6.7, 7.8, 6.7, 0.5, 7.5, 5.8, 3.6, 10.5, 12.5,
7.2, 8.2, 10.7, 9.2, 7.1, 5, 16.5, 12.8, 6.7, 10, NA, 10, 4.5,
7.4, 7.2, 9.5, 9.2, 9, 7.2, 7.5, NA, 10.43, 7.1, 8, 5, 5.4, 4.1,
10.2, 4, 7, 12.7, 6.5, 7.5, 4.2, 11.8, 7.6, 15, 4.4, 6.3, 7.2,
NA, 4.5, 4.5, 7.5, 10, 3.8, 6.4, NA, 4, 15.2, 5.4, 8.3, 6.5,
8, 12, 8.2, 5.6, 7.2, 6.3, 10, 5.6, 4.5, 8.2, 8.4, 6, 6.7, 6.5,
11.5, 8.5, 5.2, 7.1, 4.7, 6.7, 9, 6.5, 6.7, 5, 5.8, 7.5, 4.5,
9, 41, 15, 8.5, 7.2, 9, 3.8, 5.7, 6.3, 7.5, 4.4, 18, 10.5, 11.3,
NA, 5.2, 4.5, 9.5, 7.2, 2.7, 6.4, 17.2, 8.5, 4.9, 4.7, 7.2, 10,
4.5, 7.2, 7.2, 6.7, 7.2, 4.4, 9, 7.5, 16.1, 6.7, 2.5, 7.4, 2.8,
4.2, 5.8, 5.2, 10, 12.8, 8.3, 6.5, 6, 3, 7.6, 5.5, 8.8, 5.2,
5.2, 8, 6.7, 15, 11.5, 7.1, NA, 7.5, 7.2, 5.2, 6.8, 5.5, 5.2,
6.7, 5, 9, 9.2, 13.8, 4.5, 3.2, 16.1, 4.7, 14.2, 13, 7.2, 9.2,
4.9, 7.2, 7.2, 4.5, 4.5, 4.5, 7.6), IBU = c(60, 41.5, 8, 55,
59, 38, 40, 75, 30, 60, 50, 42, 45, 150, 70, 70, 100, 60, 45,
33, 90, 67, 70, 70, 55, 75, 35, 8, 85, 125, 70, 70, 100, 125,
65, 47, 20.5, 50, 70, 35, 20, 55, 35, 65, 70, 85, 149, 65, 100,
30, 30, 65, 68, 35, 50, 35, 65, 50, 35, 20, 85, 35, 50, 50, 80,
70, 80, 35, 85, 70, 9, 35, 30, 70, 85, 35, 40, 45, 40, 20, 20,
70, 60, 45, 85, 42, 40, 70, 55, 85, 30, 55, 42, 50, 50, 40, 35,
80, 65, 45, 90, 45, 67, 85, 20, 67, 30, 40, 90, 38, 50, 1085,
90, 85, 100, 80, 20, 35, 130, 75, 35, 70, 14, 50, 25, 65, 25,
80, 70, 36, 50, 75, 100, 30, 37, 100, 80, 55, 50, 250, 67, 100,
70, 70, 80, 85, 70, 35, 70, 30, 25, 40, 50, 55, 70, 70, 55, 60,
8, 175, 35, 40, 45, 55, 85, 70, 90, 50, 80, 45, 0, 130, 55, 30,
60, 40, 70, 50, 85, 65, 60, 40, 8, 100, 25, 20, 100, 250, 50,
18, 250, 250, 40, 40, 40, 70), OG = c(1044, 1041.7, 1040, 1060,
1069, 1045, 1046, 1068, 1079, 1052, 1047, 1046, 1067, 1098, 1058,
1076, 1093, 1082, 1047, 1038, 1120, 1013, 1074, 1066, 1007, 1068,
1049, 1040, 1102, 1087, 1067, 1076, 1105, 1085, 1065, 1048.5,
1112, 1096, 1066, 1080, 1048, 1090, 1048, 1069, 1067, 1095, 1083,
1080, 1064, 1080, 1043, 1095, 1056, 1077, 1049, 1050, 1042, 1026,
1041, 1081, 1113.5, 1050, 1070, 1042, 1096, 1073, 1113, 1040,
1063, 1067, 1032, 1048, 1045, 1068, 1098, 1040, 1057, 1081, 1039,
1110, 1055, 1076, 1060, 1075, 1130, 1078, 1055, 1067, 1060, 1098,
1058, 1046, 1078, 1080, 1050, 1063, 1068, 1096, 1078, 1049, 1067,
1055, 1013, 1094, 1060, 1013, 1050, 1053, 1072, 1042.9, 1084,
1085, 1120, 1072, 1064, 1083, 1039, 1053, 1060, 1068, 1045, 1150,
1093, 1098, 1052, 1048, 1043, 1075, 1067, 1033, 1061, 1156, 1068,
1047, 1043, 1064, 1097, 1045, 1068, 1065, 1064, 1064, 1045, 1090,
1069, 1125, 1063, 1027, 1069, 1032.5, 1044, 1060, 1050, 1128,
1108, 1076, 1059, 1056, 1007, 1072, 1053, 1084, 1048, 1053, 1074,
1066, 1120, 1104, 1067, 1089, 1069, 1065, 1052, 1068, 1062, 1048,
1066, 1053, 1094, 1069, 1088, 1045, 1007, 1015, 1008, 1025, 1015,
1065, 1016, 1010, 1065, 1065, 1045, 1045, 1045, 1067), EBC = c(20,
15, 8, 30, 10, 15, 12, 22, 120, 200, 140, 62, 219, 70, 25, NA,
36, 12, 8, 50, 100, 19, 90, 30, 30, 30, 44, NA, 64, 40, 30, 16,
300, 40, 13, 65, 20, 111, 30, 80, 14, 300, 40, 60, 30, 250, 19.5,
97, 12, 46, 15, 23, 14, 15, 110, 11.5, 17, 197, 45, 12, 250,
23, 40, 30, 115, 59, 400, 12, 24, 30, 2, 44, 25, 30, 130, 25,
10, 15, 18, 158, 30, 30, 25, 240, 24, 90, 15, 30, 30, 30, 54,
25, 70, 200, 8, 15, 250, 115, 31.2, 45, 15, 200, 19, 400, NA,
19, 60, 177.3, 200, 18, 20, 40, 100, 15, 12, 180, 6, 25, 14,
30, 30, 57, NA, 164, 10, 16, 10, 195, 30, 57, 20, 128, 15, 12,
10, 12, 65, 20, 150, 15, 19, 12, 30, 190, 50, 400, 30, 10, 30,
42, 19, 35, 17, 300, 79, 30, 50, 17, 9, 40, 25, 190, 35, 165,
35, 30, 100, 38, 71, 15, 50, 14, 200, 86, 230, 13, 30, 200, 400,
60, 25, 18, 8, 500, 25, 67, 300, 15, 78.8, 13, 17, 104, 18, 18,
18, 20), PH = c(4.4, 4.4, 3.2, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.2, 5.2, 4.4, 4.4, 4.4, 5.2, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 3.2, 4.4, 4.4, 4.4, 4.4, 4.3, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.2, 4.4, 4.4, 4.2, 4.4, 4.4, 4.4, 4.4,
4.4, 4.5, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 3.2, 5.2,
4.4, 4.4, 4.4, 5.2, 4.4, 4, 4.4, 4.2, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 3.5, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 5.2, 4.2, 4.4, 4.4, 4.2,
4.4, 4.4, 4.4, 4.3, 3.2, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 5.2, 5.2, 4.4, 5.2, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 5.2,
4.2, 4.5, 4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.2, 4.4, 4.4, 4.2, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 4.3, 4.4, 4.2, 4.4, 4.4, 4.4, 4.4,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 3.2, 4.4, 4.4, 4.5, 4.4, 5.2, 5.2,
4.4, 4.4, 4.4, 4.4, 4.4, 4.4, 5.2, 5.2, 4.4, 4.4, 4.4, 4.4, 4.4,
4.3, 4.2, 4.4, 4.2, 3.2, 4.4, 4.2, 4, 4.4, 4.4, 4.2, 4.2, 4.4,
4.4, 4.2, 4.2, 4.2, 4.4), AttenuationLevel = c(75, 76, 83, 80,
67, 88.9, 78, 80.9, 74.7, 77, 74.5, 72.8, 70.1, 87, 79.3, 83,
68, 86, 79, 68.4, 98, 79.7, 79.7, 77.3, 28.6, 82.1, 90, 83, 102,
81.2, 82.1, 83, 76.2, 81.2, 85, 79.4, 100, 79.17, 77.3, 85, 89.6,
84.4, 72.9, 82.6, 82.1, 76.8, 83, 76, 84, 70, 81.4, 83.2, 82.1,
79.2, 79, 84, 76.2, 74.5, 75.6, 74, 76.8, 76, 81.4, 76.2, 79.2,
79.5, 84.1, 79.5, 82.6, 82.1, 88, 72.9, 75.6, 82.1, 79.6, 70,
87, 93.8, 76.9, 82, 74.6, 82.9, 83.3, 81.3, 102.3, 83.3, 78,
82.1, 80, 70, 74, 73.9, 83.3, 81.3, 87, 84, 70.6, 79.2, 84.6,
81.6, 80.6, 70, 79.7, 73.4, 87, 79.7, 76, 84.9, 79.2, 81, 82.1,
81.2, 98, 90.3, 84, 83.1, 87, 79.3, 83, 82.1, 73.3, 93.3, 80,
79.6, 87, 79, 79.1, 81.3, 82.1, 70.8, 80.3, 80.8, 95.6, 80.7,
83.7, 84, 79.4, 73.9, 78.6, 84.6, 79.7, 84, 82.9, 80, 82.6, 84,
81, 70.4, 82.6, 63.1, 72.7, 76.7, 80, 89, 81.5, 82.9, 81.4, 82.14,
82.5, 80.6, 79.3, 79.8, 77.1, 75.5, 82.4, 77.3, 98, 85, 79, 94.4,
81.1, 87, 73.1, 76.5, 67.7, 79.2, 77.3, 73.6, 73.4, 82.6, 83,
75.6, 78, 84, 75.6, 75.6, 84.4, 84.6, 81, 78.7, 84.6, 84.6, 75.6,
75.6, 75.6, 82), FermentationTempCelsius = c(19L, 18L, 21L, 9L,
10L, 22L, 10L, 19L, 19L, 19L, 19L, 22L, 18L, 17L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 18L, 19L, 19L, 19L, 19L, 21L, 21L, 21L,
19L, 21L, 21L, 21L, 9L, 19L, 20L, 21L, 19L, 19L, 22L, 21L, 19L,
18L, 19L, 18L, 19L, 19L, 19L, 12L, 23L, 21L, 10L, 9L, 19L, 19L,
19L, 21L, 19L, 19L, 18L, 18L, 21L, 19L, 20L, 20L, 21L, 10L, 19L,
19L, 21L, 19L, 19L, 19L, 21L, 19L, 20L, 23L, 19L, 21L, 19L, 21L,
19L, 20L, 21L, 21L, 19L, 19L, 19L, 21L, 19L, 9L, 22L, 14L, 20L,
19L, 19L, 20L, 18L, 14L, 19L, 19L, 19L, 21L, 20L, 19L, 19L, 19L,
21L, 10L, 21L, 21L, 19L, 18L, 19L, 21L, 20L, 17L, 20L, 19L, 19L,
22L, 19L, 20L, 20L, 19L, 15L, 19L, 19L, 19L, 19L, 21L, 21L, 10L,
12L, 19L, 21L, 19L, 19L, 21L, 19L, 19L, 20L, 21L, 22L, 21L, 99L,
19L, 19L, 22L, 16L, 19L, 19L, 21L, 18L, 21L, 19L, 19L, 19L, 21L,
17L, 21L, 19L, 19L, 19L, 19L, 19L, 21L, 19L, 23L, 19L, 20L, 19L,
19L, 19L, 19L, 19L, 19L, 21L, 18L, 21L, 19L, 21L, 21L, 12L, 21L,
21L, 21L, 21L, 12L, 21L, 21L, 19L, 19L, 19L, 21L), Yeast = structure(c(1L,
1L, 1L, 3L, 3L, 4L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L,
2L, 3L, 1L, 2L, 2L, 1L, 2L, 4L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
3L, 4L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L,
2L, 2L, 3L, 1L, 1L, 4L, 1L, 1L, 1L, 2L, 1L, 1L, 4L, 1L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 3L, 2L, 3L, 1L, 1L, 1L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 2L, 2L,
2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 4L, 1L, 1L, 2L, 1L,
1L, 1L, 2L, 2L, 3L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 1L, 2L, 1L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 1L,
1L, 1L, 2L), .Label = c("Wyeast 1056 - American Ale", "Wyeast 1272 - American Ale II",
"Wyeast 2007 - Pilsen Lager", "Wyeast 3711 - French Saison"), class = "factor")), class = "data.frame", row.names = c(NA,
-196L))
已更新
正如@dcarlson 所建议的，您可以在整个数据帧上 运行 mice，然后您可以使用 complete 来获取整个输出数据帧。然后，您可以将新数据与原始数据框合并。
library(tidyverse)
library(mice)
imi <- mice(data, m=5, maxit=10)
imi_complete <- complete(imi)
res <- data %>%
dplyr::left_join(., imi_complete %>% dplyr::select(Name, ABV, EBC), by = "Name") %>%
dplyr::select(-c(ABV.x, EBC.x)) %>%
dplyr::rename("ABV" = ABV.y, "EBC" = EBC.y)
输出
head(res)
Name IBU OG PH AttenuationLevel FermentationTempCelsius Yeast ABV EBC
1 Buzz 60.0 1044.0 4.4 75.0 19 Wyeast 1056 - American Ale 4.5 20
2 Trashy Blonde 41.5 1041.7 4.4 76.0 18 Wyeast 1056 - American Ale 4.1 15
3 Berliner Weisse With Yuzu - B-Sides 8.0 1040.0 3.2 83.0 21 Wyeast 1056 - American Ale 4.2 8
4 Pilsen Lager 55.0 1060.0 4.4 80.0 9 Wyeast 2007 - Pilsen Lager 6.3 30
5 Avery Brown Dredge 59.0 1069.0 4.4 67.0 10 Wyeast 2007 - Pilsen Lager 7.2 10
6 Electric India 38.0 1045.0 4.4 88.9 22 Wyeast 3711 - French Saison 7.5 15
旧
由于新数据框中没有 id 列，您可以 mutate 将原始数据框中的列替换为新数据框中的输出。但是，更好的做法是直接对原始数据框进行估算（如@dcarlson 和@r2evans 所建议的那样），这样您就可以确保数据位于正确的行上。
library(tidyverse)
df_orig %>%
dplyr::mutate(ABV = df_new$ABV, EBC = df_new$EBC)
输出
id ABV EBC third
1 1 -61 -58 37.94029
2 2 -80 -67 47.81479
3 3 -62 -66 48.85903
4 4 -69 -78 23.18026
5 5 -51 -77 29.91952
数据
df_orig <-
structure(
list(
id = c(1, 2, 3, 4, 5),
ABV = c(
38.9932923251763,
20.0923723727465,
37.640398349613,
31.4673039061017,
49.192731983494
),
EBC = c(
42.341671793256,
32.936319950968,
33.8184517389163,
21.5938150603324,
22.8182014194317
),
third = c(
37.9402944352478,
47.8147878032178,
48.8590325415134,
23.1802612892352,
29.9195193173364
)
),
class = "data.frame",
row.names = c(NA,-5L)
)
df_new <-
structure(
list(
ABV = c(-61,-80,-62,-69,-51),
EBC = c(-58,-67,-66,-78,-77)
),
class = c("rowwise_df", "tbl_df", "tbl",
"data.frame"),
row.names = c(NA,-5L),
groups = structure(
list(.rows = structure(
list(1L, 2L, 3L, 4L, 5L),
ptype = integer(0),
class = c("vctrs_list_of",
"vctrs_vctr", "list")
)),
row.names = c(NA,-5L),
class = c("tbl_df",
"tbl", "data.frame")
)
)